**4. Electrical signature analysis overview**

Electrical Signature Analysis (ESA) is the general term for a set of electrical machine condition monitoring techniques through the analysis of electrical signals such as current and voltage. These techniques are: Current Signature Analysis (CSA), Voltage Signature Analysis (VSA), Extended Park's Vector Approach (EPVA), Instantaneous Power Signature Analysis (IPSA), among others. The electrical motor of the rotating system under analysis is analyzed for the failure diagnosis purposes, acting as a transducer in this process. Variations in the voltage and current signals are analyzed in relation to some failure patterns.

492 Induction Motors – Modelling and Control

distinguished:

distinguished:

the isolation.

failures, and they are shown in Figure 2c.

In one hand, the main source of electrical problems in induction motor is in stator that totalizes 37% of the total of failures. Figure 2b details different type of problems in the motor stators. In the other hand, problems in the motor rotor totalize 10% of the total of motor

Many failures can be deriving of incorrect specifications. The specification of a motor must consider the mechanical and electric conditions, and the environment in which the machine goes to work. The monitored parameters are affected by these operational conditions. In terms of the mechanical conditions, the failures appear as resulted of the behavior of the

Successive overloads that can cause superheating and/or damages to the bearing;

Vibration that can be transmitted to the machine causing damages to the bearing.

In terms of the electric conditions, the failures can result of the electrical power system characteristics or the load feeder by the motor. Amongst the main problems they are

Slow fluctuations of voltage being able to cause loss of stop power and of the machine.

In terms of the environment conditions, the failures can result of the characteristics of the process in which the machine is being used. Amongst the main problems they are

Humidity and pollution that can respectively cause imperfections and contamination of

Thus, it is clear that the failures that occur in electric machines depend on the type of machine and the environment where it is working. What it is really important to observe it is that the failure mechanism happens in gradual way, from an initial defect up to real failure. The time of propagation of the failure depends on some factors. However, the major parts of the failures present initial pointers of its presences and are exactly in these initial

Electrical Signature Analysis (ESA) is the general term for a set of electrical machine condition monitoring techniques through the analysis of electrical signals such as current and voltage. These techniques are: Current Signature Analysis (CSA), Voltage Signature Analysis (VSA), Extended Park's Vector Approach (EPVA), Instantaneous Power Signature

Brusque fluctuations of voltage being able to cause failure in the isolation.

High temperatures that can cause the deterioration of isolation.

indications that the predictive maintenance must act (Bonaldi et al., 2003).

**4. Electrical signature analysis overview** 

**3.2. Relation between motor specification and failure mechanism** 

load. Amongst the main problems they are distinguished:

Pulsing load that can cause damages to the bearing;

Repeated departures that can damage the machine bearing;

The industrial application of ESA techniques aims to improve the equipment reliability once those techniques imply greater robustness to the diagnosis. The expected results are: downtime reduction, increase in the machine availability, maintenance costs reduction, better management and planning of maintenance, etc.

The inherent benefits in ESA are: non-intrusive; it does not demand sensors installed in the rotating drive train; it is not necessary to be suited for classified areas (the sensors can be installed in the motor control centre (MCC) free of explosive mixtures); it presents high capability of remote monitoring, reducing the human exposure to risks; it can be applied to any induction motor without power restriction; it presents sensitivity to detect mechanical failures in the motor and load, electrical failures in the stator and problems in the mains, etc.

For these reasons, one recommends the application of these techniques (together with the mechanical approaches) in order to prevent catastrophic failures; improve the safety and the reliability of the productive process; reduce the downtime, improve the condition monitoring of motors installed in places of difficult access and improve the motor management in the maintenance context for reliability purposes.

Among the several ESA techniques, two of them are considered in this chapter: MCSA and EPVA.

The stator line current spectral analysis has been widely used recently for the purpose of diagnosing problems in induction machines. This technique is known as Motor Current Signature Analysis (MCSA) and the current signal can be easily acquired from one phase of the motor supply without interruption of the machine operation. In MCSA the current signal is processed in order to obtain the frequency spectrum usually referred to as current signature. By means of the motor signature, one can identify the magnitude and frequency of each individual component that constitutes the signal of the motor. This characteristic permits identifying patterns in the signature in order to differentiate healthy motors from unhealthy ones and point where the failures happen. Although it is important to say that the diagnosis is something extremely complicated, e.g., the decision of stopping or not the productive process based on the current spectrum indications is always not elementary and demands experience and knowledge of the process.

## **4.1. Current and voltage signature analysis**

CSA – Current Signature Analysis or VSA – Voltage Signature Analysis techniques are used to generate analyses and trend of electric machines dynamically. They aim to detect predictive problems in a rotating electric machine, such as: problems in the stator winding, rotor problems, problems on the engagement, problems in bound load, efficiency and system load; problems in the bearing, among others. It may initially cause a certain astonishment that the electrical signals contain information in addition to the electrical characteristics of the machine under supervision, but they work for mechanical defects as a transducer, allowing the electrical signals (voltage and/or current) can carry information of electrical and mechanical problems until the power panel of the machine.

Predictive Maintenance by Electrical Signature Analysis to Induction Motors 495

current signal. This allows that patterns in current signature be identified to differentiate "healthy" motors from "unhealthy" ones and even detect in which part of machine failure

However, it is important to note that the diagnosis is something extremely complicated, i.e. the definition of stopping or not the production process in view of the indications of the power spectrum is always difficult and requires experience and knowledge of the process. This time, it is important to consider the expert knowledge and the data history of the behavior of the set (motor, transmission system and load). For this reason, an automatic diagnostic system that combines the data history of the motor to the attention of specialist is a niche market quite promising. This way, the automatic diagnosis and analysis system is no longer as simple as the model shown in Figure 3a and can be represented by the new

The Fast Fourier Transform (FFT) is the main tool employed, however some systems employ in conjunction with other techniques to increase the ability of fault detection since signal acquisition, through processing, up to the diagnostic step. Among the most important issues

a. **Frequency range:** the frequency response is typically required in MCSA 5 kHz. This

b. **Nyquist theorem:** this theorem states that for any signal to be reconstructed without significant losses must be removed samples with twice the maximum frequency of the signal. In practice it uses 10 times the maximum frequency and ensures excellent

c. **Resolution:** spectral lines resolution, i.e. the distance between two spectral is given by (1):

Where *f* is the spectral resolution, *fs* is the sampling frequency used, and *N* is the number of

Other important issues are related to the own operation of induction motors. The first one is

*S <sup>f</sup> <sup>N</sup>*

Where *f*1 represents the power frequency, *Ns* is the velocity of the rotating field, and *p* is the

From the synchronous speed, two important concepts for the current signature analysis can be presented: the slip speed and the slip. In MCSA is important to note that the rotor speed is always less than the synchronous speed. The frequency of the induced currents in the rotor is a function of frequency and power slip. When operating without load, the rotor rotates at a speed close to the synchronous speed. In this case, torque should be just

1

*s f f N*

(1)

*<sup>p</sup>* (2)

way, the bandwith of the transducers used must be at least 10 kHz.

should occur.

elements in Figure 3b.

accuracy.

number of motor pole pairs.

samples.

related to acquisition of signals and the FFT include:

the induction motor synchronous speed that is given by (2):

The signs of current and/or voltage of one or three phases of the machine produce, after analyzed, the *signature of machine*, i.e., its operating pattern. This signature is composed of magnitudes of frequencies of each individual component extracted from their signals of current or voltage. This isolated fact itself is an advantage, as it allows the monitoring of the evolution of the magnitudes of the frequencies, which can denote some sort of evolution of operating conditions of the machinery. The response that the user of such a system needs to know is whether your machine is "healthy" or not, and that part of the machine the failure might occur.

This analysis (diagnosis) is not something easy to be done, because it involves a set of comparisons with previously stored patterns and own "history" of the machine under analysis. In this instant, normally a specialist is called to produce the final diagnosis, generating the command when stopping the machine.
