**1. Introduction**

Data acquisition is a function that has a role of fundamental importance in the functions of automatic supervision and control because it relates the system (software and hardware architecture) with the process to be controlled (real world). The field of application ranges from research to automation, from industry to home automation, basically everything that in some way must be performed without human supervision.

Data acquisition systems are primarily used to measure physical phenomena such as: temperature, voltage, current, strain and pressure, shock and vibration, distance and displacement, RPM, angle and discrete events, and weight.

When the engineer is interested in controlling a physical process (light intensity, sound analysis, mass measure, position check, velocity, PID control, etc.) his first problem is to acquire the right information coming from one or more sensors, in some cases we talk about sensor strings or distributed sensors.

The goal is to acquire data that are consistent over time and that correctly describe the shaping of the physical process. All this allows both the correct processing of data and a fast action on the control system through its actuators (motors, LEDs, speakers, etc.).

"Data acquisition" means data exchange in both directions: from the process to the system and vice versa. In all control systems the "heart" of the process is the data acquisition that plays a main role but at the same time it must be accompanied by a simple and intuitive user interface, the HMI-Human Machine Interface. Data acquisition systems are generally referred to by the acronym DAQ (Data AcQuisition).

**78**

*LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use*

[8] P. Abreu, J. S. Valiente, L. De La Torre, and M. T. Restivo, "Remote experiments with pneumatic circuit using a double rod cylinder," in *2019 5th Experiment International Conference (exp. at'19)*, 2019, pp. 410-414.

[9] I. Angulo *et al.*, "RoboBlock: A remote lab for robotics and visual programming," in *2017 4th Experiment@ International Conference (exp. at'17)*,

2017, pp. 109-110.

**References**

966, 2019.

169-185, 2020.

2019, pp. 208-212.

657-664.

pp. 357-358.

2018, pp. 714-720.

[7] D. Galán *et al.*, "Safe

[1] M. Hernández-de-Menéndez, A. V. Guevara, and R. Morales-Menendez, "Virtual reality laboratories: a review of experiences," Int. J. Interact. Des. Manuf., vol. 13, no. 3, pp. 947-

[2] M.-H. Zhang, C.-Y. Su, Y. Li, and Y.-Y. Li, "Factors affecting Chinese university students' intention to continue using virtual and remote labs," Australas. J. Educ. Technol., vol. 36, no. 2, pp.

[3] C. Arguedas-Matarrita *et al.*, "Remote experimentation in the teaching of physics in Costa Rica: First

steps," in *2019 5th Experiment International Conference (exp. at'19)*,

[4] A. Benhamouda, B. Benmounah, N. Baira, and S. Kahmous, "Design and Implementation of a Low-Cost and Modular Remote Lab Framework: Application to Electronic Sensors," in *International Conference on Interactive Collaborative Learning*, 2017, pp.

[5] A. Cardoso, V. Sousa, M. T. Restivo, and P. Gil, "Demonstration of a remote

[6] A. Cardoso, J. Leitão, P. Gil, A. S. Marques, and N. E. Simões, "Using IPython to Demonstrate the Usage of Remote Labs in Engineering Courses–A Case Study Using a Remote Rain Gauge," in *International Conference on Remote Engineering and Virtual Instrumentation*,

Experimentation in Optical Levitation of Charged Droplets Using Remote Labs.," *J. Vis. Exp. JoVE*, no. 143, 2019.

lab based on a vibrating beam apparatus," in *2016 13th International Conference on Remote Engineering and Virtual Instrumentation (REV)*, 2016,

**Figure 1.** *(Acquisition chain) [1].*

**Figure 1** shows the electronic chain to acquire an analog signal. The sensor is the device sensitive to the physical feature, the analog-to-digital conversion system, and the computer on which the SW architecture for managing the information is developed. Both feedback and actuators are missing in this figure as they are not the subject of this chapter.

This chapter is designed to be a guide for beginners, programming amateurs and students who wish to approach the world of automation with LabView using low-cost third-party DAQs such as Arduino.

Arduino is a "machine" capable of working in Stand Alone, it can perform simple industrial control tasks.

In a SCADA (Supervisory Control And Data Acquisition) system there is a Master and many Slaves. The Master device carries out the configuration, supervision and control of the slaves. The slave, a local device very close to the process, is equipped with a processor and a system of ports to interface with the sensors and actuators. In this chapter we will write some code to have LabView in the role of Master and Arduino in the role of Slave.

### **2. Sensor, filtering and multiplexer**

We speak about Data Acquisition process, DAQ, when we refer to the process of making measurements of physical phenomena with a PC (tablet, smartphone, workstation, etc). The signals, to be processed, are converted from the analog domain to the digital domain. Only after the digital acquisition we can process the data acquired (recording, visualization, analysis). For this purpose, an A/D (Analog to Digital) subsystem is used to convert the signal.

We report, below, some theoretical hints of the components visible in **Figure 2**.

At the sensor output, the electronic chain includes a "signal conditioning circuit", a multiplexer, the sampling circuit and finally the A/D converter.

The measurement of a physical phenomenon, such as temperature, sound level, vibration of motion oscillatory, or wind speed, begins with a sensor. A sensor is a device that converts the physical phenomenon into a measurable electrical signal.

For example, an elevator gets to the floor through the installation of positioning sensors; a washing machine is equipped with a sensor that measures the rpm of the motor or the water level in the drum; a twilight light; a TV remote control. The classic mercury thermometer is also a type of sensor that is used to measure temperature. In this case, however, the measure is expressed directly on a graduated scale readable by man and not by the machine: we speak in this case of **human readable** type sensor.

**81**

use an isolation system.

**Figure 2.**

**Figure 3.**

*Detail of the complete acquisition scheme.*

*Signal conditioning, filtering and amplification.*

providing incorrect results.

nominal level, to be easily digitized.

**2.1 Signal conditioner**

**2.2 Multiplexing**

channels **Figure 4**.

*LabView and Connections with Third-Party Hardware DOI: http://dx.doi.org/10.5772/intechopen.96056*

The sensors can produce several kind of electrical outputs such as voltage, current, resistance, or other electrical characteristics modulated from physical phenomenon. When the signal coming from the sensor or from the transmission line is noisy or the ground reference is not at 0 volts (as it should) is preferable to

In "signal conditioning circuit" we propose a section with electrical isolation that allows the separation of the signal from other electrical sources. This aspect is also essential for the measurement of signals with very small amplitude in which external electrical potentials can affect the quality of the signal considerably,

The **signal conditioner** circuits are designed to process the analog signal from the sensors and prepare it to be digitally sampled. The conditioning circuit must linearize the sensor output, eliminate electrical interference that adds to the signal (so-called "noise", as shown in **Figure 3**), and amplify the small signal (mV, μV) to a

**Multiplexing**, on the other hand, is that part of the circuit that allows us to expand the inputs of our DAQ, thus using a single conversion line on multiple input *LabView and Connections with Third-Party Hardware DOI: http://dx.doi.org/10.5772/intechopen.96056*

**Figure 2.** *Detail of the complete acquisition scheme.*

#### **Figure 3.**

*LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use*

subject of this chapter.

*(Acquisition chain) [1].*

**Figure 1.**

simple industrial control tasks.

Arduino in the role of Slave.

low-cost third-party DAQs such as Arduino.

**2. Sensor, filtering and multiplexer**

to Digital) subsystem is used to convert the signal.

**Figure 1** shows the electronic chain to acquire an analog signal. The sensor is the device sensitive to the physical feature, the analog-to-digital conversion system, and the computer on which the SW architecture for managing the information is developed. Both feedback and actuators are missing in this figure as they are not the

This chapter is designed to be a guide for beginners, programming amateurs and students who wish to approach the world of automation with LabView using

Arduino is a "machine" capable of working in Stand Alone, it can perform

In a SCADA (Supervisory Control And Data Acquisition) system there is a Master and many Slaves. The Master device carries out the configuration, supervision and control of the slaves. The slave, a local device very close to the process, is equipped with a processor and a system of ports to interface with the sensors and actuators. In this chapter we will write some code to have LabView in the role of Master and

We speak about Data Acquisition process, DAQ, when we refer to the process of making measurements of physical phenomena with a PC (tablet, smartphone, workstation, etc). The signals, to be processed, are converted from the analog domain to the digital domain. Only after the digital acquisition we can process the data acquired (recording, visualization, analysis). For this purpose, an A/D (Analog

We report, below, some theoretical hints of the components visible in

At the sensor output, the electronic chain includes a "signal conditioning circuit", a multiplexer, the sampling circuit and finally the A/D converter.

The measurement of a physical phenomenon, such as temperature, sound level, vibration of motion oscillatory, or wind speed, begins with a sensor. A sensor is a device that converts the physical phenomenon into a measurable

For example, an elevator gets to the floor through the installation of positioning sensors; a washing machine is equipped with a sensor that measures the rpm of the motor or the water level in the drum; a twilight light; a TV remote control. The classic mercury thermometer is also a type of sensor that is used to measure temperature. In this case, however, the measure is expressed directly on a graduated scale readable by man and not by the machine: we speak in this case of **human** 

**80**

**Figure 2**.

electrical signal.

**readable** type sensor.

*Signal conditioning, filtering and amplification.*

The sensors can produce several kind of electrical outputs such as voltage, current, resistance, or other electrical characteristics modulated from physical phenomenon. When the signal coming from the sensor or from the transmission line is noisy or the ground reference is not at 0 volts (as it should) is preferable to use an isolation system.

In "signal conditioning circuit" we propose a section with electrical isolation that allows the separation of the signal from other electrical sources. This aspect is also essential for the measurement of signals with very small amplitude in which external electrical potentials can affect the quality of the signal considerably, providing incorrect results.

#### **2.1 Signal conditioner**

The **signal conditioner** circuits are designed to process the analog signal from the sensors and prepare it to be digitally sampled. The conditioning circuit must linearize the sensor output, eliminate electrical interference that adds to the signal (so-called "noise", as shown in **Figure 3**), and amplify the small signal (mV, μV) to a nominal level, to be easily digitized.

#### **2.2 Multiplexing**

**Multiplexing**, on the other hand, is that part of the circuit that allows us to expand the inputs of our DAQ, thus using a single conversion line on multiple input channels **Figure 4**.

**Figure 4.** *Example of a 4-input multiplexer.*

The multiplexer (commonly called MUX) is a selector of data lines (analog or digital) able to select different input signals: once selected the channel, the corresponding signal is collected and sent on the output line. There are some particularly performing and expensive devices that do not use the MUX but they have a complete acquisition chain for each input.
