**An Investigation of an Acoustic Wave Velocity in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources**

Noorsuhada Md Nor, Norazura Muhamad Bunnori, Azmi Ibrahim, Hamidah Mohd Saman, Shahiron Shahidan and Soffian Noor Mat Saliah

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54448

## **1. Introduction**

170 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

*Department of Mechanical and Materials Engineering, Faculty of Engineering,* 

for supporting this research through the FRGS grant FRGS/2/2010/SOE/06.

[3] Wambua, P., J., Ivens, and I. Verpoest, Compos Sci Technol 63, 1259 (2003). [4] Yang, H-S., D-J., Kim, and H-J. Kim, Bioresource Technology 86, 117 (2003).

Authors would like to acknowledge the Ministry of Higher Education of Malaysia (MOHE)

[1] Khedari, J., S. Charoenvai and J. Hirunlabh, Building and Environment 38, 435 (2003). Karl, K. H., Katrin, K. *Ergonomics: How To Design For Ease And Efficiency*, 3rd [2] Ed. Prentice

[6] F. –C. Lee, and W.-H. Chen. Acoustic Transmission Analysis of Multi Layer Absorbers.

http://jobaccess.gov.au/Advice/ProductOrSolutionOne/Pages/Sound\_absorption\_panels

http://www.acousticalsurfaces.com/acoustic\_IOI/101\_7.htm [Accessed: 22 May 2011]. [11] Zulkifli, R., Mohd Nor, M.J., Ismail, A.R., Nuawi, M.Z., Abdullah, S., Tahir, M.F.M., Abd. Rahman, M.N. Comparison of Acoustic Properties between Coir Fiber and Oil

[12] Hosseini Fouladi, M., Ayub, Md., Mohd Nor, M.J. Analysis of Coir Fiber Acoustic

[14] Aerias Air Quality Sciences. Fiber Glass And The Indoor Environment, Available at: http://www.aerias.org/DesktopModules/ArticleDetail.aspx?articleId=38&spaceid=1&su

[16] Baranek and Ver www.sdcounty.ca.gov/dplu/.../docs/.../EIR\_Section\_2.11\_\_Noise.pdf

[17] Takeshi Komatsu. Improvement of the Delany-Bazley and Miki models for fibrous

http://www.sae.edu/reference\_material/pages/Coefficient%20Chart.htm [Accessed 14

[7] Puglia, D., J., Biagiotti, and J.M., Kenny, Journal of Natural Fibers 1(3), 23 (2004).

Palm Fiber. *European Journal of Scientific Research* 33 (1), 144-152 (2009).

[15] http://www.thefreedictionary.com/resonance [Accessed 25 April 2012].

sound-absorbing materials. Acoust. Sci & Tech 29 (2) 121-129 (2008).

*Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia* 

Hall: Upper Saddle River, New Jersey, (2001).

Journal of Sound and Vibration, 248(4):621-634 (2001).

[8] Wang C. N., and J.H., Torng, Appl Acoust 62, 447 (2001). [9] Australian Government. Sound Absorption Panel. Available at:

[10] Acoustical Surfaces Inc., Sound absorption, Available at:

Characteristic. *Applied Acoustics* 72 (1), 35-42 (2011).

[13] Absorption Coefficient Chart, Available at:

bid=4 [Accessed: 27 March 2011].

[Acsses 20 April, 2012]

April 2011].

[5] Davern, W.A., Appl Acous 10, 85 (1977).

.aspx [Accessed: 22 May 2011]

Mohd Jailani Mohd Nor

**Acknowledgement** 

**6. References** 

Acoustic Emission (AE) is a phenomenon of a transient stress waves resulting from a sudden release of elastic energy, caused by mechanical deformations, initiation and propagation of microcracks, dislocation movement, and other irreversible changes in material [1]. AE sensors are used to detect the acoustic waves at the surface of a structure, produced by AE events either on the surface or in the bulk of the material [2].

There are two types of signals in the AE system; namely burst and continuous signals. Burst signal is a separate type of signal of a very short duration (in the range of a few microseconds (µs) to a few miliseconds (ms)) and it is a broad frequency domain spectrum. Meanwhile the continuous signal is emitted close to each other or the burst is very high rate. The continuous signal is also occurred very close and sometimes overlaps. When the AE signal or output is transmitted in a structure, an array is identified. The output is always represented in a waveform which has information on a source location. A key to compute a source location is by determination of the wave velocity of the wave propagation. If incorrect wave velocity was used either owing to poor assumption or triggering of the system, it would affect to the determination of the source location [3]. Thus accurate wave velocity is important for the determination of the source location prior to any AE test.

The AE wave velocity can be determined by estimating the time of arrival (TOA) of the wave propagating in the structure; normally based on the threshold level [3] or frequency [4]. Typically, the propagation of wave in concrete can be categorized into three different types; namely dilatation wave (compression waves, longitudinal wave or P-wave for primary), the distortion wave (shear waves or S-wave for secondary) and the Rayleigh wave

(surface wave or R-wave) [5–7]. Longitudinal wave is known as L – wave or P – wave; which the wave travels in the material and Rayleigh wave (R-wave) travels along the surface of the specimen. The initiation time of the P-wave is when the first TOA of the elastic wave reaches to each sensor. If the onset of the S-wave is detected, this information can be used either in combination with P-wave or be considered as P-wave onset [8]. Determining S–wave is challenging because the distance between sensor and receiver is only few wavelengths. Another problem is because the onset of the S–wave is hidden in the P– wave [8]. Generally, an S-wave is normal to the direction of the wave propagation and a Pwave, parallel. Determination of onset time can be done visually or automatically. This depends on the onset definition itself and also by picking algorithm. In relation with the wave velocity, the P-wave travels at a higher velocity than S-wave [9]. In concrete, the Swave velocity is approximately 40% less than of the P-wave velocity and R-wave velocity is 92 % of the S-wave velocity and 56 % of the P-wave velocity [10]. However, only the P-wave would be considered in this study based on the TOA.

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 173

agent (Rheobuild 1100) of cement weight was added in the concrete mix to improve the workability of the fresh concrete. The maximum coarse aggregate of 20 mm was used.

The beams were designed as a singly RC beam with two high yield steels of 16 mm to strengthen the tension part and two mild steels of 8 mm as hanger bars. The bars were bent at both end to form a standard hook of 60 mm at tension part and 30 mm at compression part. In the stirrups, 12 diameter of mild steel with spacing of 100 mm centre to centre was used. In the preparation of each RC beam, the reinforcement was submerged in the standard mould of 150 mm x 150 mm x 750 mm with cover of 20 mm, before the concrete mix was cast. All beams were demoulded after ±24 hours and submerged in the water curing tank for 28 days. In order to ensure the design fulfilled the strength, the cubes were prepared and tested under compression test for 7 and 28 days. The compressive strength for 7 days was

Acoustic emission (AE) was monitored using a MicroSAMOS (µSAMOS) supplied by Physical Acoustic Corporation (PAC). The system consists of integral preamplifier acoustic emission sensors (transducers) R6I (40 – 100 kHz); a notebook acoustic emission system board (8 (channels) x 16 (hubs) bit acoustic emission channels, low peak and high peak filters, 2 MHz bandwidth, auto sensor test (AST), time definition display (TDD), digital signal processor (DSP) and waveform module; personal computer memory card international association (PCMCIA) interface card; cables; internal and external parametric cable set; a notebook personal computer with full suite of AEWin Software; universal serial bus (USB) license key; and magnetic clamps. The acquisition parameters in the AEWin

> Parameter Value Hit definition time (HDT) 2000µs Peak definition time (PDT) 1000µs Hit lockout time (HLT) 500µs Preamplifier (R6I) 40dB Bandpass data acquisition filter 400kHz Sample rate 100ksps Analog filter (lower) 1kHz Pre-trigger 250,000

Prior to the wave velocity test, three pairs of thin plates were prepared to attach the sensors S1, S2 and S3 with the distance of 200 mm and 100 mm between pair of plates. Spacing between two plates is 45 mm. The beam surface was polished smoothly using course sand

found to be 32.35 N/mm2 and 44.65 N/mm2at age of 28 days.

**2.3. AE sensor installation and sensitivity checking** 

**2.2. Acoustic emission system** 

software were summarized in Table 1.

**Table 1.** AE test parameters

In order to determine the wave velocity, AE signals are produced by pencil lead fracture (PLF), known as Hsu-Nielsen technique. In this technique, PLF is the monopoles which is normally applied to the outside of the test sample, and the real AE signal is nearly dipoles in which the AE sources that originated from the points are buried inside the sample [11]. The previous PLF was used to generate simulated acoustic emission signals in an aluminum plate at different angles; 0, 30, 60 and 90 degree with respect to the plane of the plate [12]. Next, it is suggested that the plate wave analysis be used to determine the source orientation of acoustic emission sources. A few researchers have used the same method in the heterogeneous material as well as reinforced concrete (RC) [3, 13]. To verify the wave velocity propagation in the RC beam, corrected signal was used by Muhamad Bunnori [3], by normalizing each signal for peak value of amplitude up to 10 volts. The same method was also utilized for this analysis.

In this study, various threshold levels were performed to determine the TOA and the wave velocity in the RC beams with shorter source-to-sensor distance. Very little attention has been given on the shorter distance between sensor and sensor to source distance. An AE source was specified and focused on out-of plane and in-plane of the arrangement of sensor faces. Three main objectives are addressed. Firstly to study the relationship between wave velocity and sensor distance, secondly to investigate the relationship between wave velocity and threshold level and lastly to observe the relationship between arrival time and sensor distance.

## **2. Experimental procedure**

## **2.1. Preparation of beam specimen**

The test of wave velocity was carried out on a reinforced concrete (RC) beam with dimension of 150 mm x 150 mm x 750 mm; designed in accordance with British Standard [14] for grade C40. The concrete was made up from cement, water, fine aggregate and coarse aggregate with proportion of 1: 0.43: 2.16: 2.60, respectively. Then, 1 % of water reducer agent (Rheobuild 1100) of cement weight was added in the concrete mix to improve the workability of the fresh concrete. The maximum coarse aggregate of 20 mm was used.

The beams were designed as a singly RC beam with two high yield steels of 16 mm to strengthen the tension part and two mild steels of 8 mm as hanger bars. The bars were bent at both end to form a standard hook of 60 mm at tension part and 30 mm at compression part. In the stirrups, 12 diameter of mild steel with spacing of 100 mm centre to centre was used. In the preparation of each RC beam, the reinforcement was submerged in the standard mould of 150 mm x 150 mm x 750 mm with cover of 20 mm, before the concrete mix was cast. All beams were demoulded after ±24 hours and submerged in the water curing tank for 28 days. In order to ensure the design fulfilled the strength, the cubes were prepared and tested under compression test for 7 and 28 days. The compressive strength for 7 days was found to be 32.35 N/mm2 and 44.65 N/mm2at age of 28 days.

## **2.2. Acoustic emission system**

172 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

would be considered in this study based on the TOA.

was also utilized for this analysis.

**2. Experimental procedure** 

**2.1. Preparation of beam specimen** 

distance.

(surface wave or R-wave) [5–7]. Longitudinal wave is known as L – wave or P – wave; which the wave travels in the material and Rayleigh wave (R-wave) travels along the surface of the specimen. The initiation time of the P-wave is when the first TOA of the elastic wave reaches to each sensor. If the onset of the S-wave is detected, this information can be used either in combination with P-wave or be considered as P-wave onset [8]. Determining S–wave is challenging because the distance between sensor and receiver is only few wavelengths. Another problem is because the onset of the S–wave is hidden in the P– wave [8]. Generally, an S-wave is normal to the direction of the wave propagation and a Pwave, parallel. Determination of onset time can be done visually or automatically. This depends on the onset definition itself and also by picking algorithm. In relation with the wave velocity, the P-wave travels at a higher velocity than S-wave [9]. In concrete, the Swave velocity is approximately 40% less than of the P-wave velocity and R-wave velocity is 92 % of the S-wave velocity and 56 % of the P-wave velocity [10]. However, only the P-wave

In order to determine the wave velocity, AE signals are produced by pencil lead fracture (PLF), known as Hsu-Nielsen technique. In this technique, PLF is the monopoles which is normally applied to the outside of the test sample, and the real AE signal is nearly dipoles in which the AE sources that originated from the points are buried inside the sample [11]. The previous PLF was used to generate simulated acoustic emission signals in an aluminum plate at different angles; 0, 30, 60 and 90 degree with respect to the plane of the plate [12]. Next, it is suggested that the plate wave analysis be used to determine the source orientation of acoustic emission sources. A few researchers have used the same method in the heterogeneous material as well as reinforced concrete (RC) [3, 13]. To verify the wave velocity propagation in the RC beam, corrected signal was used by Muhamad Bunnori [3], by normalizing each signal for peak value of amplitude up to 10 volts. The same method

In this study, various threshold levels were performed to determine the TOA and the wave velocity in the RC beams with shorter source-to-sensor distance. Very little attention has been given on the shorter distance between sensor and sensor to source distance. An AE source was specified and focused on out-of plane and in-plane of the arrangement of sensor faces. Three main objectives are addressed. Firstly to study the relationship between wave velocity and sensor distance, secondly to investigate the relationship between wave velocity and threshold level and lastly to observe the relationship between arrival time and sensor

The test of wave velocity was carried out on a reinforced concrete (RC) beam with dimension of 150 mm x 150 mm x 750 mm; designed in accordance with British Standard [14] for grade C40. The concrete was made up from cement, water, fine aggregate and coarse aggregate with proportion of 1: 0.43: 2.16: 2.60, respectively. Then, 1 % of water reducer Acoustic emission (AE) was monitored using a MicroSAMOS (µSAMOS) supplied by Physical Acoustic Corporation (PAC). The system consists of integral preamplifier acoustic emission sensors (transducers) R6I (40 – 100 kHz); a notebook acoustic emission system board (8 (channels) x 16 (hubs) bit acoustic emission channels, low peak and high peak filters, 2 MHz bandwidth, auto sensor test (AST), time definition display (TDD), digital signal processor (DSP) and waveform module; personal computer memory card international association (PCMCIA) interface card; cables; internal and external parametric cable set; a notebook personal computer with full suite of AEWin Software; universal serial bus (USB) license key; and magnetic clamps. The acquisition parameters in the AEWin software were summarized in Table 1.


**Table 1.** AE test parameters

## **2.3. AE sensor installation and sensitivity checking**

Prior to the wave velocity test, three pairs of thin plates were prepared to attach the sensors S1, S2 and S3 with the distance of 200 mm and 100 mm between pair of plates. Spacing between two plates is 45 mm. The beam surface was polished smoothly using course sand

paper to ensure good connectivity between sensors and beam surface. The plates were then fixed to the beam surface using epoxy and hardener.

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 175

A = 20 log (V/Vref) (1)

arrangement on the RC beam using a thin layer of high vacuum grease as a couplant with the same spacing of 200 mm centre to centre for beam 150 mm x 150 mm x 750 mm and 100

In this experiment, four different pre-set threshold levels were chosen namely 40 dB, 45 dB, 65 dB and 70 dB. At each threshold level, 15 replicates of PLF were applied to generate a simulated AE source at the same spot or the same AE source location. When the lead is pressed against the RC beam surface, the applied force produces a local deformation and the stress where the lead touched is suddenly being released. It is important to handle the pencil properly while breaking the lead against the testing specimen to get significant value. Improper handling of the pencil would give imprecise value; which will affect the TOA. The proper breaking of the lead creates a very short-duration, localized impulse that is quite similar to a natural acoustic emission source such as crack [19]. The lead was extended to 0.1 inches and the pencil was slanted down 300 to the plane of the beam surface, as suggested by other researchers [18, 20]. The out-of plane AE source was located at the centre of the cross section of the end beam. As for in-plane AE source, it was located at 100 mm from

In the AE hardware, for in-plane source, Sensor 1 was set as individual and the rest were synchronized. Meanwhile, for out-of plane source, Sensor 3 was set as individual and the rest were synchronized. The same method applied for beam size of 100 mm x 100 mm x 500 mm.

In acoustic emission, waveform parameters normally used are frequency and amplitude [22]. Amplitude of AE signal parameter was used in identification of wave velocity. It is defined as the magnitude of the peak voltage of the largest excursion attained by the signal waveform from single emission event [1]. Amplitude is reported in decibels (dB) to measure signal size and typical AE signal is represented as a voltage versus time curve. Voltage is

Where: *A* is an amplitude (dB), *V* is voltage of peak excursion and *Vref* is the reference voltage. Generally the dB scale runs from 0 to 100 [21]; which depend on the threshold set.

**Figure 1.** Schematic diagram of sensors location on the RC beam 150 mm x 150 mm x 750 mm

mm centre to centre for beam 100 mm x 100 mm x 500 mm.

Sensor 1 as illustrated in Figures 1 and 2.

converted to dB using the following equation:

Three sensors were coupled on the beam surfaces at the selected point using a good couplant such as a thin layer of high performance grease. The thinnest practical layer of couplant is usually the best [15]. The magnetic clamps were used to safeguard the sensors; which sensors held in position in magnetic clamps; then the magnetic clamps properly coupled to the steel plates.

With sensors in good mounting condition, calibration (sensitivity) checking was carried out to recognize the sensitivity of the sensors. In this experiment, a magnetic pencil with a Nielson shoe (Teflon shoe) was used to break a 0.5 mm 2 H lead to generate a simulated acoustic wave against the surface of the beam. The handling method of the magnetic pencil has been presented in ASTM E976 [16]. All sensors would significantly coupled if the wave was generated by at least three or more replicates of pencil lead fracture (PLF). This might produce high amplitude of 99 dB or the sensitivity within ± 3 dB in different [3, 17]. Based on the research done by others, it was found that the amplitude recorded by each sensor should not be permitted to vary more than 4 dB from the average of all sensors [18]. This technique was used to ensure that the sensor and the beam were in a good contact to provide an adequate result throughout the test. If these criteria are not met, the sensors on the beam surface would be remounted and sensitivity check was carried out until the amplitude fulfilled the requirement.

## **2.4. Wave velocity test**

In this experimental work, three integral preamplifier R6I sensors with 55 kHz resonant frequency were used. Acoustic emission sensors are transducers that convert the mechanical waves into electrical signal [19], where the information about the existence and location of possible damage or stress released sources can be obtained. The specification and feature of the sensor is shown in Table 2.


**Table 2.** Specification and feature of the R6I sensor

A schematic diagram of the test set up for beam size of 150 mm x 150 mm x 750 mm and 100 mm x 100 mm x 500 mm in a linear structure is shown in Figure 1 and Figure 2, respectively. The AE sources were identified on the out-of plane and in plane of the sensors arrangement or source parallel to the sensor face. Three sensors were mounted in a symmetrical arrangement on the RC beam using a thin layer of high vacuum grease as a couplant with the same spacing of 200 mm centre to centre for beam 150 mm x 150 mm x 750 mm and 100 mm centre to centre for beam 100 mm x 100 mm x 500 mm.

174 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

fixed to the beam surface using epoxy and hardener.

coupled to the steel plates.

amplitude fulfilled the requirement.

feature of the sensor is shown in Table 2.

**Table 2.** Specification and feature of the R6I sensor

**2.4. Wave velocity test** 

paper to ensure good connectivity between sensors and beam surface. The plates were then

Three sensors were coupled on the beam surfaces at the selected point using a good couplant such as a thin layer of high performance grease. The thinnest practical layer of couplant is usually the best [15]. The magnetic clamps were used to safeguard the sensors; which sensors held in position in magnetic clamps; then the magnetic clamps properly

With sensors in good mounting condition, calibration (sensitivity) checking was carried out to recognize the sensitivity of the sensors. In this experiment, a magnetic pencil with a Nielson shoe (Teflon shoe) was used to break a 0.5 mm 2 H lead to generate a simulated acoustic wave against the surface of the beam. The handling method of the magnetic pencil has been presented in ASTM E976 [16]. All sensors would significantly coupled if the wave was generated by at least three or more replicates of pencil lead fracture (PLF). This might produce high amplitude of 99 dB or the sensitivity within ± 3 dB in different [3, 17]. Based on the research done by others, it was found that the amplitude recorded by each sensor should not be permitted to vary more than 4 dB from the average of all sensors [18]. This technique was used to ensure that the sensor and the beam were in a good contact to provide an adequate result throughout the test. If these criteria are not met, the sensors on the beam surface would be remounted and sensitivity check was carried out until the

In this experimental work, three integral preamplifier R6I sensors with 55 kHz resonant frequency were used. Acoustic emission sensors are transducers that convert the mechanical waves into electrical signal [19], where the information about the existence and location of possible damage or stress released sources can be obtained. The specification and

> Specification Value Dimension (Ø x height) mm 29 x 40 Weight (gm) 98

Operating temperature (0oc) -45 to +85 Shock limit (g) 500 Peak sensitivity (V/m/s) 120 Directionality (dB) +1.5

A schematic diagram of the test set up for beam size of 150 mm x 150 mm x 750 mm and 100 mm x 100 mm x 500 mm in a linear structure is shown in Figure 1 and Figure 2, respectively. The AE sources were identified on the out-of plane and in plane of the sensors arrangement or source parallel to the sensor face. Three sensors were mounted in a symmetrical In this experiment, four different pre-set threshold levels were chosen namely 40 dB, 45 dB, 65 dB and 70 dB. At each threshold level, 15 replicates of PLF were applied to generate a simulated AE source at the same spot or the same AE source location. When the lead is pressed against the RC beam surface, the applied force produces a local deformation and the stress where the lead touched is suddenly being released. It is important to handle the pencil properly while breaking the lead against the testing specimen to get significant value. Improper handling of the pencil would give imprecise value; which will affect the TOA. The proper breaking of the lead creates a very short-duration, localized impulse that is quite similar to a natural acoustic emission source such as crack [19]. The lead was extended to 0.1 inches and the pencil was slanted down 300 to the plane of the beam surface, as suggested by other researchers [18, 20]. The out-of plane AE source was located at the centre of the cross section of the end beam. As for in-plane AE source, it was located at 100 mm from Sensor 1 as illustrated in Figures 1 and 2.

In the AE hardware, for in-plane source, Sensor 1 was set as individual and the rest were synchronized. Meanwhile, for out-of plane source, Sensor 3 was set as individual and the rest were synchronized. The same method applied for beam size of 100 mm x 100 mm x 500 mm.

In acoustic emission, waveform parameters normally used are frequency and amplitude [22]. Amplitude of AE signal parameter was used in identification of wave velocity. It is defined as the magnitude of the peak voltage of the largest excursion attained by the signal waveform from single emission event [1]. Amplitude is reported in decibels (dB) to measure signal size and typical AE signal is represented as a voltage versus time curve. Voltage is converted to dB using the following equation:

$$\mathbf{A} = \mathbf{\mathcal{D}} \log \left( \mathbf{V} / \mathbf{V}\_{\text{ref}} \right) \tag{1}$$

Where: *A* is an amplitude (dB), *V* is voltage of peak excursion and *Vref* is the reference voltage. Generally the dB scale runs from 0 to 100 [21]; which depend on the threshold set.

**Figure 1.** Schematic diagram of sensors location on the RC beam 150 mm x 150 mm x 750 mm

176 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

**Figure 2.** Schematic diagram of sensors location on the RC beam 100 mm x 100 mm x 500 mm

In a relationship between threshold level and amplitude, preamplifier was considered; where equation (2) was used to calculate amplitude:

$$\text{Threshold} = \text{Amplitude} - \text{Preamplifier} \tag{2}$$

The rudimentary determination for location calculation is based on time-distance relationship implied by the velocity of the sound wave [4, 23]; where the absolute arrival time, *t*, of a hit in an event combine with the velocity, *v* (*v* is P-wave velocity [19]), of the sound wave to yield the distance, *d*, from sensor to the source as represented by

$$\mathbf{d} = \mathbf{v} \ \mathbf{t} \tag{3}$$

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 177

Sensitivity checking was used to ensure the sensor and the beam was in a good contact to provide an adequate results. The sensors must have a higher sensitivity [24] in order to get good contact between sensors surface and beam surfaces. In this experimental in order to check the sensitivity, at least ten numbers of 99 dB were considered for each sensor. The responses of the transducer to PLFs are shown in Figure 3. Sensor 1 represents a good sensitivity since almost of all the PLFs produced amplitude of 99 dB. However, Sensor 2 needs several trials to ensure the sensors and the beam surface have a good contact. These scenarios that occurred in Sensors 1 and 2 are related with the signal waveform produced from the PLF. It is typically affected by the source characteristics, the path taken from the source to the sensors, the characteristic of the sensor and the measurement system [25]. The

**3. Results and discussion** 

waveform for Hit 1 and Hit 12 are represented in Figure 4.

**Figure 3.** Response to PLF on reinforced concrete beam for a) Sensor 1 and b) Sensor 2

**Figure 4.** AE waveform for two different AE amplitudes during sensitivity checking

**3.1. Sensitivity checking** 

Generally the distance between the two sensors depends on the geometry of the sample. Determination of TOA (the exact time the event originated) was made by recording many data hits for each AE event. *t1* represents the time of arrival (or arrival of longitudinal wave, P-wave) at Channel 1. Meanwhile *t2* is arrival of P-wave at Channel 2. The arrival time difference between the arrivals of the signal at the two sensors can be written as

$$
\Delta \mathbf{T} = \begin{pmatrix} t\mathbf{i} - t\mathbf{z} \end{pmatrix} \tag{4}
$$

At selected source locations (either out-of plane or in-plane), 10 replicates of PLF were applied from the lower threshold level of 40 dB to the higher 70 dB. Distance for beam 150 mm x 150 mm x 750 mm from sensors 1-2 and sensors 1-3 is 200 mm and 400 mm, respectively. Meanwhile, for beam 100 mm x 100 mm x 500 mm, the distance from sensors 1 to 2 is 100 mm and sensors 1 to 3 is 200 mm.

The relationship between wave velocity and threshold level, and TOA and sensor distance were correlated. Both correlations were then verified by corrected AE signal. Corrected AE signal was used for a particular threshold level, the same temporal position in each waveform which involves the normalizing of each signal up to a peak value of 10 volts. In this research, the corrected signal was used for the evaluation of TOA for each threshold level. The corrected signal can be identified by normalizing the peak signal of a hit to 10 volts followed by other signal in a hit. Then, the TOA for each threshold was then determined.

## **3. Results and discussion**

#### **3.1. Sensitivity checking**

176 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

**Figure 2.** Schematic diagram of sensors location on the RC beam 100 mm x 100 mm x 500 mm

sound wave to yield the distance, *d*, from sensor to the source as represented by

difference between the arrivals of the signal at the two sensors can be written as

where equation (2) was used to calculate amplitude:

to 2 is 100 mm and sensors 1 to 3 is 200 mm.

determined.

In a relationship between threshold level and amplitude, preamplifier was considered;

The rudimentary determination for location calculation is based on time-distance relationship implied by the velocity of the sound wave [4, 23]; where the absolute arrival time, *t*, of a hit in an event combine with the velocity, *v* (*v* is P-wave velocity [19]), of the

Generally the distance between the two sensors depends on the geometry of the sample. Determination of TOA (the exact time the event originated) was made by recording many data hits for each AE event. *t1* represents the time of arrival (or arrival of longitudinal wave, P-wave) at Channel 1. Meanwhile *t2* is arrival of P-wave at Channel 2. The arrival time

At selected source locations (either out-of plane or in-plane), 10 replicates of PLF were applied from the lower threshold level of 40 dB to the higher 70 dB. Distance for beam 150 mm x 150 mm x 750 mm from sensors 1-2 and sensors 1-3 is 200 mm and 400 mm, respectively. Meanwhile, for beam 100 mm x 100 mm x 500 mm, the distance from sensors 1

The relationship between wave velocity and threshold level, and TOA and sensor distance were correlated. Both correlations were then verified by corrected AE signal. Corrected AE signal was used for a particular threshold level, the same temporal position in each waveform which involves the normalizing of each signal up to a peak value of 10 volts. In this research, the corrected signal was used for the evaluation of TOA for each threshold level. The corrected signal can be identified by normalizing the peak signal of a hit to 10 volts followed by other signal in a hit. Then, the TOA for each threshold was then

Threshold = Amplitude – Preamplifier (2)

d = v t (3)

ΔT = (*t1* – *t2*) (4)

Sensitivity checking was used to ensure the sensor and the beam was in a good contact to provide an adequate results. The sensors must have a higher sensitivity [24] in order to get good contact between sensors surface and beam surfaces. In this experimental in order to check the sensitivity, at least ten numbers of 99 dB were considered for each sensor. The responses of the transducer to PLFs are shown in Figure 3. Sensor 1 represents a good sensitivity since almost of all the PLFs produced amplitude of 99 dB. However, Sensor 2 needs several trials to ensure the sensors and the beam surface have a good contact. These scenarios that occurred in Sensors 1 and 2 are related with the signal waveform produced from the PLF. It is typically affected by the source characteristics, the path taken from the source to the sensors, the characteristic of the sensor and the measurement system [25]. The waveform for Hit 1 and Hit 12 are represented in Figure 4.

**Figure 3.** Response to PLF on reinforced concrete beam for a) Sensor 1 and b) Sensor 2

**Figure 4.** AE waveform for two different AE amplitudes during sensitivity checking

Generally, each PLF produces one signal of AE hit or more and in various form or shape of waves. Figure 4 shows different shapes of wave for two hits of PLF from Sensor 1. Hit 1 is a response of PLF that produces amplitude 99 dB and generates high peak wave. Hit 12 is for amplitude 91 dB response from the bounce back of the lead during PLF process and produced lower amplitude. Hit 1 generates high peak wave rather than Hit 12. Figure 3a indicated that Hit 12 occurred at the same time of PLF with other amplitudes. However, for sensitivity checking this will be ignored. The peak signal amplitude can be related to the intensity of the source in the material [21, 25]. Pullin et al. [26] stated that the good sensitivity between sensor and beam surface is enough when the amplitude signal exceeded 95 dB. Hence, sensitivity checking would be better when a higher amplitude is being produced during replicates of PLFs.

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 179

In this experiment, Sensor 1 was set as individual due to close to the AE source and the rest were considered as synchronize. For instance, the threshold was set at 40 dB prior to test. The Sensor 1 would be the first received the waves emitted by PLF at AE source followed by other sensors as depicted in Figure 6. In this figure, the TOA or longitudinal wave (P-wave) for Sensors 1, 2 and 3 were noted as *t1*, *t2* and *t3* respectively. The AE signal for first P-wave, *t1* was examined out to 29 µs after the source initiation time followed by P-wave, *t2* for sensor 2 about 34 µs and P-wave for *t3* is 43 µs. In the test, gain 0 dB and preamplifier 40 dB were used with the sample interval of 10µs. In this case, the thresholds were assumed to be as lower as 40 dB (0.01V) to 70 dB (0.32V). Referring to eq. 1 and eq. 2, amplitude (represented in dB) can be calculated with the *Vref* equals 1µv. Then, volt for each threshold levels can be determined. Volt for each threshold can be used as a guideline determine the

TOA or P-wave at each sensor from AE source.

**Figure 6.** TOA or P-wave for threshold 40 dB at time 35.53 s for each sensor

are apparently depends on the sensor distance and threshold levels.

**3.3. Relationship between wave velocity and sensor distance for RC beam** 

The first method in the determination of wave velocity in 150 mm x 150 mm x 750 mm and 100 mm x 100 mm x 500 mm RC beam is based on the changes of pre-set threshold level in AE hardware or threshold crossing technique. Four different pre-set threshold levels were chosen namely 40 dB (0.01V), 45 dB (0.02V), 65 dB (0.2V) and 70 dB (0.32V). For each pre-set threshold level, 10 replicates of PLF were carried out in-plane and out-of-plane sources. TOA to each sensor for each PLF was analysed and followed by other replicates of PLFs. Figure 7a shows the relationship between the average wave velocity and sensor distance for out-of-plane source at each threshold level. Figure 7b presents the relationship of average wave velocity and sensor distance for in-plane source. Both figures show the wave velocities

## **3.2. Identification of Time of Arrival (TOA)**

Typical AE waveform parameter received by Sensor 1 type R6I from a 150 x 150 x 750 mm RC beam during PLF process, represented in amplitude (v) against time (µs) is shown in Figure 5. As lead breaks (in-plane or out-of-plane) on the surface of the beam, a wave propagates through a solid medium; it carries certain amount of energy. The energy can be consumed by scattering during propagation. The scattering effect principally relies on the defects such as micro-cracks inside the material. In wave velocity determination only several AE parameters would be considered such as time and amplitude. AE amplitude gives the information about the time at which AE signals take place [27]. Wave velocity is one of the methods to be considered for source location. Figure 6 presents the wave of the signal for threshold 40 dB. The first wave crosses the threshold level is known as P-wave.

**Figure 5.** Simple waveform parameter

In this experiment, Sensor 1 was set as individual due to close to the AE source and the rest were considered as synchronize. For instance, the threshold was set at 40 dB prior to test. The Sensor 1 would be the first received the waves emitted by PLF at AE source followed by other sensors as depicted in Figure 6. In this figure, the TOA or longitudinal wave (P-wave) for Sensors 1, 2 and 3 were noted as *t1*, *t2* and *t3* respectively. The AE signal for first P-wave, *t1* was examined out to 29 µs after the source initiation time followed by P-wave, *t2* for sensor 2 about 34 µs and P-wave for *t3* is 43 µs. In the test, gain 0 dB and preamplifier 40 dB were used with the sample interval of 10µs. In this case, the thresholds were assumed to be as lower as 40 dB (0.01V) to 70 dB (0.32V). Referring to eq. 1 and eq. 2, amplitude (represented in dB) can be calculated with the *Vref* equals 1µv. Then, volt for each threshold levels can be determined. Volt for each threshold can be used as a guideline determine the TOA or P-wave at each sensor from AE source.

178 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

produced during replicates of PLFs.

**Figure 5.** Simple waveform parameter

**3.2. Identification of Time of Arrival (TOA)** 

Generally, each PLF produces one signal of AE hit or more and in various form or shape of waves. Figure 4 shows different shapes of wave for two hits of PLF from Sensor 1. Hit 1 is a response of PLF that produces amplitude 99 dB and generates high peak wave. Hit 12 is for amplitude 91 dB response from the bounce back of the lead during PLF process and produced lower amplitude. Hit 1 generates high peak wave rather than Hit 12. Figure 3a indicated that Hit 12 occurred at the same time of PLF with other amplitudes. However, for sensitivity checking this will be ignored. The peak signal amplitude can be related to the intensity of the source in the material [21, 25]. Pullin et al. [26] stated that the good sensitivity between sensor and beam surface is enough when the amplitude signal exceeded 95 dB. Hence, sensitivity checking would be better when a higher amplitude is being

Typical AE waveform parameter received by Sensor 1 type R6I from a 150 x 150 x 750 mm RC beam during PLF process, represented in amplitude (v) against time (µs) is shown in Figure 5. As lead breaks (in-plane or out-of-plane) on the surface of the beam, a wave propagates through a solid medium; it carries certain amount of energy. The energy can be consumed by scattering during propagation. The scattering effect principally relies on the defects such as micro-cracks inside the material. In wave velocity determination only several AE parameters would be considered such as time and amplitude. AE amplitude gives the information about the time at which AE signals take place [27]. Wave velocity is one of the methods to be considered for source location. Figure 6 presents the wave of the signal for

threshold 40 dB. The first wave crosses the threshold level is known as P-wave.

**Figure 6.** TOA or P-wave for threshold 40 dB at time 35.53 s for each sensor

## **3.3. Relationship between wave velocity and sensor distance for RC beam**

The first method in the determination of wave velocity in 150 mm x 150 mm x 750 mm and 100 mm x 100 mm x 500 mm RC beam is based on the changes of pre-set threshold level in AE hardware or threshold crossing technique. Four different pre-set threshold levels were chosen namely 40 dB (0.01V), 45 dB (0.02V), 65 dB (0.2V) and 70 dB (0.32V). For each pre-set threshold level, 10 replicates of PLF were carried out in-plane and out-of-plane sources. TOA to each sensor for each PLF was analysed and followed by other replicates of PLFs. Figure 7a shows the relationship between the average wave velocity and sensor distance for out-of-plane source at each threshold level. Figure 7b presents the relationship of average wave velocity and sensor distance for in-plane source. Both figures show the wave velocities are apparently depends on the sensor distance and threshold levels.

In determination of wave velocity, sensors 1, 2 and 3 was set of 0 m, 0.2 m and 0.4 m, respectively. Figure 7 illustrates that, for RC beams 150 mm x 150 mm x 750 mm with sensor distances 0.2 m, at lower threshold level (40 dB) and higher threshold level (70 dB) for out-of-plane source, the velocity is in the range of 7889 m/s to 4559 m/s and 2409 m/s to 1654 m/s, respectively. Meanwhile in in-plane source, velocities for lower threshold and higher threshold are in the range of 3086 m/s to 2608 m/s and 2619 m/s to 2192 m/s, respectively. It is found that the wave velocity for in-plane source has lower velocity than out-of-plane source. It might be due to the in-plane source location is parallel to the sensor surface and the wave propagates take longer time to reach the sensors. Hence, the source location in linear measurement of sensors for in-plane would prolong the TOA of the wave to reach the sensor and the velocity is reduced. Out-of-plane source is longitudinal to the sensor surface and hence the wave signal propagates inside the RC beam take shorter time to reach the sensors. Thus, it reduces the TOA of the wave to each sensor.

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 181

of 48 dB; however, the initial velocity was 10000 m/s [29]. If resonant sensor of 300 kHz was used, the wave velocity is 4000 m/s [30]. For carbon fibre reinforced polymer (CFRP) the

**Figure 8.** Wave velocity in 100 mm x 100 mm x 500 mm RC beam for a) out-of-plane source and b) in-

Figures 9a and 9b display the velocity propagates in the 150 mm x 150 mm x 750 mm RC beam as threshold levels increased for out-of-plane and in-plane sources. As mentioned earlier, apparently the wave velocities depend on the threshold levels. Thus, the statistical coefficient can be used to enhance the prediction by identification of determination coefficient, R2. For out-of-plane source, for sensors distance 0.2 m (Sensor 3-2), the R2 is 91.3 % and for distance 0.4 m (Sensor 3-1) produced higher R2 of 97.8 %. Thus, both distances have strong correlation between velocities and also the threshold level, where, the wave velocity in the RC beam is influenced by the threshold level crossing. The higher the

For in-plane source, distance between Sensors 1 to 2 and 1 to 3 is 0.2 m and 0.4 m, respectively. It is found that for in-plane source, both distances of sensors have weak correlation of 30.3 % for Sensors 1-2 and 49 % for Sensors 1-3. It is due to the wave velocities for 40 dB are lower than for threshold 45 dB with the approximate different in the range of 2100 m/s to 940 m/s. However, after threshold of 45 dB, the wave velocity seems has good

Figure 10 shows the relationship between wave velocity propagation and threshold level for 100 mm x 100 mm x 500 mm RC beam. Wave velocity for closet distance in Figure 10 shows a good relationship between velocity and threshold levels with the correlation of 83 % and 92 % for out-of-plane and in-plane source, respectively. However the longer distance represents a weak relationship with the correlation of 59 % and 40 % for out-of-plane and inplane source, respectively. Overall the prediction of the wave velocity in short distance is influenced by threshold levels has strong correlation. However, for longer distance, the

correlation, which the threshold increased as the wave velocity decreased.

**3.4. Relationship between wave velocity and threshold level** 

threshold level, the lower of the wave velocity would be.

relationship is seemingly unpredictable.

wave velocity equal to 1000 m/s [13].

plane source

In wave velocity calculation for beam 100 mm x 100 mm x 500 mm, sensors 1, 2 and 3 was set as 0, 0.1 m and 0.2 m, respectively. Figure 8 presents the wave velocity in 100 mm x 100 mm x 500 mm with sensor distances of 0.1 m for out-of-plane. The figure shows that the lower threshold level is in the range of 3430 m/s to 2810 m/s and the higher threshold level is 2765 m/s to 1166 m/s. Velocity propagates in in-plane source is in the range of 5030 m/s to 3150 m/s for threshold 40 dB and 2751 m/s to 2603 m/s for threshold 70 dB. In this case, apparently the velocity in the in-plane source has higher velocity than out-of-plane source. Logically, the pattern of the wave velocity occurred in the both size of beams with different spacing of sensors should be synchronized. However, this phenomenon indicates that the wave velocity in the RC beam or heterogeneous material cannot be predicted.

**Figure 7.** Wave velocity in 150 mm x 150mm x 750 mm RC beam for a) out-of-plane source and b) inplane source

The results of the study were also compared to other research done in heterogeneous material as well as RC structure of the wave velocity of RC beam 100 mm x 150 mm x 2000 mm with the sensor distance of 250 mm, the value was in the range of 4000 m/s to 4500 m/s [3]. For large spectrum with frequency between 50 to 600 kHz, the wave velocity is 2350 m/s [28]. The wave velocity in ceramic matrix composite was 3200 m/s with the threshold level of 48 dB; however, the initial velocity was 10000 m/s [29]. If resonant sensor of 300 kHz was used, the wave velocity is 4000 m/s [30]. For carbon fibre reinforced polymer (CFRP) the wave velocity equal to 1000 m/s [13].

**Figure 8.** Wave velocity in 100 mm x 100 mm x 500 mm RC beam for a) out-of-plane source and b) inplane source

## **3.4. Relationship between wave velocity and threshold level**

180 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

to reach the sensors. Thus, it reduces the TOA of the wave to each sensor.

wave velocity in the RC beam or heterogeneous material cannot be predicted.

**Figure 7.** Wave velocity in 150 mm x 150mm x 750 mm RC beam for a) out-of-plane source and b) in-

The results of the study were also compared to other research done in heterogeneous material as well as RC structure of the wave velocity of RC beam 100 mm x 150 mm x 2000 mm with the sensor distance of 250 mm, the value was in the range of 4000 m/s to 4500 m/s [3]. For large spectrum with frequency between 50 to 600 kHz, the wave velocity is 2350 m/s [28]. The wave velocity in ceramic matrix composite was 3200 m/s with the threshold level

plane source

In determination of wave velocity, sensors 1, 2 and 3 was set of 0 m, 0.2 m and 0.4 m, respectively. Figure 7 illustrates that, for RC beams 150 mm x 150 mm x 750 mm with sensor distances 0.2 m, at lower threshold level (40 dB) and higher threshold level (70 dB) for out-of-plane source, the velocity is in the range of 7889 m/s to 4559 m/s and 2409 m/s to 1654 m/s, respectively. Meanwhile in in-plane source, velocities for lower threshold and higher threshold are in the range of 3086 m/s to 2608 m/s and 2619 m/s to 2192 m/s, respectively. It is found that the wave velocity for in-plane source has lower velocity than out-of-plane source. It might be due to the in-plane source location is parallel to the sensor surface and the wave propagates take longer time to reach the sensors. Hence, the source location in linear measurement of sensors for in-plane would prolong the TOA of the wave to reach the sensor and the velocity is reduced. Out-of-plane source is longitudinal to the sensor surface and hence the wave signal propagates inside the RC beam take shorter time

In wave velocity calculation for beam 100 mm x 100 mm x 500 mm, sensors 1, 2 and 3 was set as 0, 0.1 m and 0.2 m, respectively. Figure 8 presents the wave velocity in 100 mm x 100 mm x 500 mm with sensor distances of 0.1 m for out-of-plane. The figure shows that the lower threshold level is in the range of 3430 m/s to 2810 m/s and the higher threshold level is 2765 m/s to 1166 m/s. Velocity propagates in in-plane source is in the range of 5030 m/s to 3150 m/s for threshold 40 dB and 2751 m/s to 2603 m/s for threshold 70 dB. In this case, apparently the velocity in the in-plane source has higher velocity than out-of-plane source. Logically, the pattern of the wave velocity occurred in the both size of beams with different spacing of sensors should be synchronized. However, this phenomenon indicates that the

Figures 9a and 9b display the velocity propagates in the 150 mm x 150 mm x 750 mm RC beam as threshold levels increased for out-of-plane and in-plane sources. As mentioned earlier, apparently the wave velocities depend on the threshold levels. Thus, the statistical coefficient can be used to enhance the prediction by identification of determination coefficient, R2. For out-of-plane source, for sensors distance 0.2 m (Sensor 3-2), the R2 is 91.3 % and for distance 0.4 m (Sensor 3-1) produced higher R2 of 97.8 %. Thus, both distances have strong correlation between velocities and also the threshold level, where, the wave velocity in the RC beam is influenced by the threshold level crossing. The higher the threshold level, the lower of the wave velocity would be.

For in-plane source, distance between Sensors 1 to 2 and 1 to 3 is 0.2 m and 0.4 m, respectively. It is found that for in-plane source, both distances of sensors have weak correlation of 30.3 % for Sensors 1-2 and 49 % for Sensors 1-3. It is due to the wave velocities for 40 dB are lower than for threshold 45 dB with the approximate different in the range of 2100 m/s to 940 m/s. However, after threshold of 45 dB, the wave velocity seems has good correlation, which the threshold increased as the wave velocity decreased.

Figure 10 shows the relationship between wave velocity propagation and threshold level for 100 mm x 100 mm x 500 mm RC beam. Wave velocity for closet distance in Figure 10 shows a good relationship between velocity and threshold levels with the correlation of 83 % and 92 % for out-of-plane and in-plane source, respectively. However the longer distance represents a weak relationship with the correlation of 59 % and 40 % for out-of-plane and inplane source, respectively. Overall the prediction of the wave velocity in short distance is influenced by threshold levels has strong correlation. However, for longer distance, the relationship is seemingly unpredictable.

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 183

would not receive any signal. This phenomenon occurs because wave attenuation in the RC beam cannot be avoided. Wave attenuation is loss of AE energy as waves travel through in a material [25]. It is also the loss of amplitude with distance as the wave travel through the beam [7]. This is also affected of the time taken path of the signal wave from the AE source to the sensors. The farthest sensor would receive the lower signal wave and hence take longer TOA. For instance, Original 40 dB at fist sensor is 29 µs and the farthest sensor is 40 µs. Thus, TOA takes longer time to reach sensor 1. Other factor causes the waveform amplitude loss such as intrinsic mechanisms and imperfections. It is because the intrinsic mechanism (thermal effects) and imperfections (void and misoriented grains) reduce the amplitude of the wave by using scattering and reflections [4]. Otherwise, RC beam is a heterogeneous material; many obstacles such as aggregates and bars affected to the movement of waves and yet delayed the TOA to the longest distance from the AE source. If the attenuation is too large or size of the structure is too big, the location of the hit cannot be defined. Thus, the attenuation depends on the types of material through which the waves

**Figure 11.** Regression analysis of arrival time against sensor distance for 150 mm x 150 mm x 750 mm

All figures show very good correlation between TOA and sensor distance for out-of-plane source and there is insignificant difference between original signal and corrected signal. All

RC beam (out-of-plane source) at a) 40 dB, b) 45 dB, c) 65 dB and d) 70 dB

are progressing and the source of the waves [7].

**Figure 9.** Relationship between velocity and threshold level on RC beam 150 mm x 150 mm x 750 mm for a) out-of-plane source and b) in-plane source

**Figure 10.** Relationship between velocity and threshold level on RC beam 100 mm x 100 mm x 500 mm for a) out-of-plane source and b) in-plane source

It can be concluded that the relationship of the velocity and threshold level is easy to predict for shorter distance, where the velocity decreases when the threshold level increases. It apparently indicates a good correlation for shorter distance. However, for longer distance the relationship is unpredictable and has weak relationship. This can be related with the material applied, where concrete always has imperfection of the composition such as voids.

## **3.5. Relationship between arrival time and sensor distance**

Figure 11 shows the average of arrival time (µs) against sensor distance for original signal and corrected signal for out-of-plane source at threshold 40 dB, 45 dB, 65 dB and 70 dB on 150 mm x 150 mm x 750 mm RC beam. In the graphs, Cor stands for corrected signal and Ori stands for original signal. The corrected signal has been used to justify the correlation between TOA and distance. Sensor 3 (distance zero) close to the AE source, it receives the first TOA emits by PLF and follows by the other sensors. Sensor 1 would receive the last signal with the higher TOA. In some situation, the farthest sensors from the AE source would not receive any signal. This phenomenon occurs because wave attenuation in the RC beam cannot be avoided. Wave attenuation is loss of AE energy as waves travel through in a material [25]. It is also the loss of amplitude with distance as the wave travel through the beam [7]. This is also affected of the time taken path of the signal wave from the AE source to the sensors. The farthest sensor would receive the lower signal wave and hence take longer TOA. For instance, Original 40 dB at fist sensor is 29 µs and the farthest sensor is 40 µs. Thus, TOA takes longer time to reach sensor 1. Other factor causes the waveform amplitude loss such as intrinsic mechanisms and imperfections. It is because the intrinsic mechanism (thermal effects) and imperfections (void and misoriented grains) reduce the amplitude of the wave by using scattering and reflections [4]. Otherwise, RC beam is a heterogeneous material; many obstacles such as aggregates and bars affected to the movement of waves and yet delayed the TOA to the longest distance from the AE source. If the attenuation is too large or size of the structure is too big, the location of the hit cannot be defined. Thus, the attenuation depends on the types of material through which the waves are progressing and the source of the waves [7].

182 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

for a) out-of-plane source and b) in-plane source

for a) out-of-plane source and b) in-plane source

**Figure 9.** Relationship between velocity and threshold level on RC beam 150 mm x 150 mm x 750 mm

**Figure 10.** Relationship between velocity and threshold level on RC beam 100 mm x 100 mm x 500 mm

It can be concluded that the relationship of the velocity and threshold level is easy to predict for shorter distance, where the velocity decreases when the threshold level increases. It apparently indicates a good correlation for shorter distance. However, for longer distance the relationship is unpredictable and has weak relationship. This can be related with the material applied, where concrete always has imperfection of the composition such as voids.

Figure 11 shows the average of arrival time (µs) against sensor distance for original signal and corrected signal for out-of-plane source at threshold 40 dB, 45 dB, 65 dB and 70 dB on 150 mm x 150 mm x 750 mm RC beam. In the graphs, Cor stands for corrected signal and Ori stands for original signal. The corrected signal has been used to justify the correlation between TOA and distance. Sensor 3 (distance zero) close to the AE source, it receives the first TOA emits by PLF and follows by the other sensors. Sensor 1 would receive the last signal with the higher TOA. In some situation, the farthest sensors from the AE source

**3.5. Relationship between arrival time and sensor distance** 

**Figure 11.** Regression analysis of arrival time against sensor distance for 150 mm x 150 mm x 750 mm RC beam (out-of-plane source) at a) 40 dB, b) 45 dB, c) 65 dB and d) 70 dB

All figures show very good correlation between TOA and sensor distance for out-of-plane source and there is insignificant difference between original signal and corrected signal. All

threshold levels have strong correlation with the determination of coefficient more than 97 % between TOA and sensor distance.

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 185

Overall, the TOA of the wave propagation has good agreement with distance of sensors, where the longer the distance, the higher the time taken to reach the sensor. It can be seen in Figures 8 and 9, the slope of the best straight line drawn through the points are linear. However, other researchers found the relationship between TOA and sensor distance is not linear [3]. Since, the TOA is a good indication of wave velocity travels in the beam, hence the

**Figure 13.** Regression analysis of arrival time against sensor distance for 100 mm x 100 mm x 500 mm

Three sensors were used to determine the TOA and the wave velocity in RC beams. Sensor 1 was set as individual since it is close to the AE source and the first to receive the waves (P-

It can be concluded that AE wave velocities were found dependent on threshold levels and distance of sensor. It is found that the higher the threshold levels, the lower the wave velocity. This is because the threshold level prolonging arrival times of the waves and reducing velocities. Wave velocities for 150 mm x 150 mm x 750 mm were calculated to be in the range of 7889 m/s to 1654 m/s for out-of-plane source and 5229 m/s to 2192 m/s for in-

(in-plane source) at a) 40 dB, b) 45 dB, c) 65 dB and d) 70 dB

Wave) that were emitted by PLF in the solid medium of concrete.

**4. Conclusions** 

wave velocity decreases as the TOA increases.

Figures 12 a), b), c) and d) represent the regression analysis of arrival time against sensor distance for in-plane source at threshold 40 dB, 45 dB, 65 dB and 70 dB, respectively. Similar to the one represented in Figure 11, it shows that all threshold levels have good correlation between time of arrival (TOA) and sensor distance with all the coefficient of determinations more than 96 %. However, threshold level of 40 dB for corrected signal analysis apparently has a perfect fit of linear correlation by representing the coefficient equal to 1. The value indicates that the TOA is absolutely influenced by the sensor distance. Similar to out-of plane source, the relationship also indicates no significant difference between original signal and corrected signal.

Figure 13 represents the regression analysis of TOA against sensor distance for 100 mm x 100 mm x 500 mm in-plane source at all threshold levels. Similarly, it shows that it has good correlation with the regression above 80 % with no significant difference between original signal and corrected signal.

**Figure 12.** Regression analysis of arrival time against sensor distance for 150 mm x 150 mm x 750 mm RC beam (in-plane source) at a) 40 dB, b) 45 dB, c) 65 dB and d) 70 dB

Overall, the TOA of the wave propagation has good agreement with distance of sensors, where the longer the distance, the higher the time taken to reach the sensor. It can be seen in Figures 8 and 9, the slope of the best straight line drawn through the points are linear. However, other researchers found the relationship between TOA and sensor distance is not linear [3]. Since, the TOA is a good indication of wave velocity travels in the beam, hence the wave velocity decreases as the TOA increases.

**Figure 13.** Regression analysis of arrival time against sensor distance for 100 mm x 100 mm x 500 mm (in-plane source) at a) 40 dB, b) 45 dB, c) 65 dB and d) 70 dB

## **4. Conclusions**

184 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

% between TOA and sensor distance.

and corrected signal.

signal and corrected signal.

threshold levels have strong correlation with the determination of coefficient more than 97

Figures 12 a), b), c) and d) represent the regression analysis of arrival time against sensor distance for in-plane source at threshold 40 dB, 45 dB, 65 dB and 70 dB, respectively. Similar to the one represented in Figure 11, it shows that all threshold levels have good correlation between time of arrival (TOA) and sensor distance with all the coefficient of determinations more than 96 %. However, threshold level of 40 dB for corrected signal analysis apparently has a perfect fit of linear correlation by representing the coefficient equal to 1. The value indicates that the TOA is absolutely influenced by the sensor distance. Similar to out-of plane source, the relationship also indicates no significant difference between original signal

Figure 13 represents the regression analysis of TOA against sensor distance for 100 mm x 100 mm x 500 mm in-plane source at all threshold levels. Similarly, it shows that it has good correlation with the regression above 80 % with no significant difference between original

**Figure 12.** Regression analysis of arrival time against sensor distance for 150 mm x 150 mm x 750 mm

RC beam (in-plane source) at a) 40 dB, b) 45 dB, c) 65 dB and d) 70 dB

Three sensors were used to determine the TOA and the wave velocity in RC beams. Sensor 1 was set as individual since it is close to the AE source and the first to receive the waves (P-Wave) that were emitted by PLF in the solid medium of concrete.

It can be concluded that AE wave velocities were found dependent on threshold levels and distance of sensor. It is found that the higher the threshold levels, the lower the wave velocity. This is because the threshold level prolonging arrival times of the waves and reducing velocities. Wave velocities for 150 mm x 150 mm x 750 mm were calculated to be in the range of 7889 m/s to 1654 m/s for out-of-plane source and 5229 m/s to 2192 m/s for in-

plane source. Wave velocities for 100 mm x 100 mm x 500 mm were computed to be in the range of 3430 m/s to 1166 m/s for out-of-plane source and 5030 m/s to 2603 m/s for in-plane source. Wave velocities decreases with the increasing distance between sensors and threshold levels. It was enhanced by the relationship of wave velocities and sensor distance for each threshold level.

An Investigation of an Acoustic Wave Velocity

in a Reinforced Concrete Beam from Out-of Plane and in Plane Sources 187

[3] Muhamad Bunnori N, Pullin R, Holford KM, Lark RJ (2006) A Practical Investigation into Acoustic Wave Propagation in Concrete Structures. Advanced Materials Research.

[4] Ervin BL (2007) Monitoring Corrosion of Rebar Embedded in Mortar using Guided

[5] Liu Z (2007) Evaluation of Reinforced Concrete Beams using Cyclic Load Test, Acoustic Emission and Acousto-Ultrasonics. PhD Thesis, Auburn University, Auburn Alabama. [6] Lovejoy S (2006) Development of Acoustic Emissions Testing Procedures Applicable to Conventionally Reinforced Concrete Deck Girder Bridges Subjected to Diagnoal

[7] ARCHES (2009) Sustainable Development, Global Change and Ecosystems Sustainable

[8] Kurz JH, Köppel S, Linzer LM, Schechinger B, Grosse CU (2008) Source Localization. In: Grosse CU, Ohtsu M, editors. Acoustic Emission Testing. Springer. pp. 101–147. [9] Grosse CU, Linzer LM (2008) Signal-Based AE Analysis. In:Grosse CU, Ohtsu M,

[10] Zein, Abd-Elbaky AS (2005) Nondestructive Evaluation of Reinforced Concrete T-Shaped Beams by Frequency Spectrum Analysis of Impact-Echo Waveforms. PhD

[11] Hamstad MA (2006) Contrasts between the Acoustic Emission Signals Generated by Monopole versus Dipole Sources. Advanced Materials Research, 13–14: 61–68. [12] Gorman MR, Prosser WH (1991) AE Source Orientation by Plate Wave Analysis.

[13] Degala S, Rizzo P, Ramanathan K, Harries KA (2009) Acoustic Emission Monitoring of CFRP Reinforced Concrete Slabs. Construction and Building Materials. 23: 2016–2026. [14] British Standard BS8110 Part 1 (1997) Structural use of Concrete: Part 1. Code of Practice

[15] ASTM E650-97 (2007) Standard Guide for Mounting Piezoelectric Acoustic Emission

[16] ASTM E976-10 (2010) Standard Guide for Determining the Reproducibility of Acoustic

[17] Md Nor N, Muhamad Bunnori N, Ibrahim A, Shahidan S, Mat Saliah SN (2011) An Investigation on Acoustic Wave Velocity of Reinforced Concrete Beam In-Plane Source. 7th International Colloquium on Signal Processing and its Application. IEEE. 19–22. [18] Chotickai P (2001) Acoustic Emission Monitoring of Prestressed Bridge Girders with Premature Concrete Deterioration. Thesis of Master Science in Engineering, The

[19] Physical Acoustic Corporation (2005) Samos AE System; Use's manual. Princeton

[20] ASNT (1996) Nondestructive testing handbook 2nd edition. Columbus, OH: American

[21] Xu J (2008) Nondestructive Evaluation of Prestressed Concrete Structures by means of Acoustic Emissions Monitoring. PhD Thesis, Auburn University, Auburn, Alabama.

Ultrasonics Waves. PhD Thesis, University of Illinois, Urbana-Champaign.

Cracking. PhD Thesis, Oregon State University.

editors. Acoustic Emission Testing. Springer. pp. 53–99.

for Design and Construction. British Standard Institution.

Sensors. ASTM International, Pennsylvania United State.

Emission Sensor Response. ASTM International. 5.

University of Texas, Austin.

Society for Nondestructive Testing.

Junction, NJ.

Surface Transport. ARCHES.

Thesis, University of South Carolina.

Journal of Acoustic Emission. 9: 283-288.

13–14: 205–212.

The relationship between wave velocity and threshold level were identified for each sensor distance and then the coefficient of correlation, R2 was determined. It is found that R2 for beam 100 mm x 100 mm x 500 mm at out-of-plane source has good correlation than in-plane source. Beam 150 mm x 150 mm x 750 mm has weak correlation for longer sensor distance, but it has good correlation for shorter distance.

The relationship of TOA and sensor distance was identified. Its correlation was presented for each original signal and corrected signal. In total, both original signal and corrected signal indicated strong correlation between TOA and sensor distance with domain regression of 90 %.

## **Author details**

Noorsuhada Md Nor and Soffian Noor Mat Saliah *Faculty of Civil Engineering, Universiti Teknologi MARA (UiTM), Permatang Pauh, Pulau Pinang, Malaysia* 

Norazura Muhamad Bunnori and Shahiron Shahidan *School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia (USM), Seri Ampangan, Seberang Perai Selatan, Nibong Tebal, Pulau Pinang, Malaysia* 

Azmi Ibrahim and Hamidah Mohd Saman *Faculty of Civil Engineering, Universiti Teknologi MARA (UiTM), Shah Alam, Selangor, Malaysia* 

## **Acknowledgement**

The authors gratefully acknowledge the support provided by the Universiti Teknologi MARA (for financial support), Universiti Sains Malaysia (for the AE equipment) and Ministry of Higher Education, Malaysia (MOHE). A special thank you to all technicians in the Laboratory of Heavy Structure, Faculty of Civil Engineering, Universiti Teknologi MARA and Universiti Sains Malaysia.

## **5. References**


[3] Muhamad Bunnori N, Pullin R, Holford KM, Lark RJ (2006) A Practical Investigation into Acoustic Wave Propagation in Concrete Structures. Advanced Materials Research. 13–14: 205–212.

186 Modeling and Measurement Methods for Acoustic Waves and for Acoustic Microdevices

for each threshold level.

regression of 90 %.

**Author details** 

**Acknowledgement** 

**5. References** 

*Malaysia* 

but it has good correlation for shorter distance.

Noorsuhada Md Nor and Soffian Noor Mat Saliah

Norazura Muhamad Bunnori and Shahiron Shahidan

Azmi Ibrahim and Hamidah Mohd Saman

MARA and Universiti Sains Malaysia.

ASTM International, 5.

plane source. Wave velocities for 100 mm x 100 mm x 500 mm were computed to be in the range of 3430 m/s to 1166 m/s for out-of-plane source and 5030 m/s to 2603 m/s for in-plane source. Wave velocities decreases with the increasing distance between sensors and threshold levels. It was enhanced by the relationship of wave velocities and sensor distance

The relationship between wave velocity and threshold level were identified for each sensor distance and then the coefficient of correlation, R2 was determined. It is found that R2 for beam 100 mm x 100 mm x 500 mm at out-of-plane source has good correlation than in-plane source. Beam 150 mm x 150 mm x 750 mm has weak correlation for longer sensor distance,

The relationship of TOA and sensor distance was identified. Its correlation was presented for each original signal and corrected signal. In total, both original signal and corrected signal indicated strong correlation between TOA and sensor distance with domain

*Faculty of Civil Engineering, Universiti Teknologi MARA (UiTM), Permatang Pauh, Pulau Pinang,* 

*Faculty of Civil Engineering, Universiti Teknologi MARA (UiTM), Shah Alam, Selangor, Malaysia* 

The authors gratefully acknowledge the support provided by the Universiti Teknologi MARA (for financial support), Universiti Sains Malaysia (for the AE equipment) and Ministry of Higher Education, Malaysia (MOHE). A special thank you to all technicians in the Laboratory of Heavy Structure, Faculty of Civil Engineering, Universiti Teknologi

[1] ASTM E 1316-06 (2006) Standard Terminology for Non-Destructive Examinations.

[2] Theobald P, Dar F (2006) AE Sensor Calibration for Out-of-Plane and In-plane

Displacement Sensitivity. Advanced Materials Research. 13–14: 91–98.

*School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia (USM), Seri* 

*Ampangan, Seberang Perai Selatan, Nibong Tebal, Pulau Pinang, Malaysia* 

	- [22] Kalyanasundaram P, Mukhopadhyay CK, Subba Rao SV (2007) Practical Acoustic Emission. Indian Society for Non-Destructive Testing – National Certification Board Series.

**Chapter 9** 

© 2013 Beghi et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

© 2013 Beghi et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Combination of Acoustic Methods** 

Fabio Di Fonzo, Francisco García Ferré, Dario Gastaldi,

Pasquale Vena and Marco G. Beghi

http://dx.doi.org/10.5772/56815

**1. Introduction** 

compactness of the film.

Additional information is available at the end of the chapter

**for the Measurement of Film Properties** 

New techniques are continuously being developed to produce films and thin films, which have a variety of properties and are exploited by an ever increasing number of technologies. The properties of films typically depend on the preparation process, and can be significantly different from those of the material in bulk form, due to the different micro- and nanostructures obtained by the various production processes. Although new techniques are also introduced to measure the film properties, the characterization of thin layers remains an open issue. A precise knowledge of the mechanical properties is crucial in several cases. Namely, whenever the films have structural functions, as it happens in several micro electro-mechanical systems (MEMS), and when the operation of a device is based on acoustic waves, as it happens in various types of micro-devices, for either sensing or signal processing purposes. But since the mechanical properties depend on the microstructural properties, they are also of more general interest, because they can be a good indicator also for properties which are not strictly mechanical, but for instance depend on the degree of

A full mechanical characterization includes the determination of both the elastic properties, which characterize the reversible deformations, and the properties which characterize the irreversible behaviour. In most cases the elastic behaviour can be completely characterized by the elastic moduli, or equivalently by the components of the elastic tensor. It is well known that also in the simplest case, the homogeneous isotropic continuum, the elastic stiffness cannot be characterized by a single parameter, but needs two independent

and reproduction in any medium, provided the original work is properly cited.

**and the Indentation Technique** 

