**8. References**

Bäck, T. (1996). *Evolutionary Algorithms in Theory and Practice*, Oxford University Press, 1996


Bouchhida, O. (2011). *Etude et Optimisation des Performances d'Onduleur Monophasé et Triphasé à Commutation Pré-Calculée*. Habilitation Universitaire, Université Saad D'hleb Blida, Algérie

**Chapter 20** 

© 2012 Bonaldi 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.

© 2012 Bonaldi 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.

**Predictive Maintenance by Electrical** 

Erik Leandro Bonaldi, Levy Ely de Lacerda de Oliveira, Jonas Guedes Borges da Silva, Germano Lambert-Torresm

expensive, forcing the company to operate without a stand-by.

and Luiz Eduardo Borges da Silva

http://dx.doi.org/10.5772/48045

determined (Bonaldi et al, 2007).

**1. Introduction** 

Additional information is available at the end of the chapter

**Signature Analysis to Induction Motors** 

Industries always try to increase the reliability of their productive process. In this context, predictive maintenance performs a fundamental role in order to reach high availability and reliability concerning their pieces of equipment. Predictive maintenance can be understood as the action on the equipment, system or installations based on the previous knowledge about the operation condition or performance, obtained by means of parameters previously

Since the induction motors are the center of the vast majority of the industrial processes, this chapter gives total emphasis to the failure analysis and identification of this kind of electrical machine. Like all the rotating machines, the induction motors are exposed to many different adversities such as thermal and environmental stresses and mechanical damages, which demand maximum attention (Lambert-Torres et al., 2003). Usually, in industries, attention must be even larger since the downtime costs are very high. High and medium voltage induction motors are highly used in industrial processes. Many of them are strategic to the productive process and, because of that, looking for solutions that minimize the failure statistics is mandatory. In most cases, these motors are highly reliable and extremely

Many predictive techniques are applied to these motors to reduce the number of unplanned outage. The most common techniques applied to fault detection in induction motors are: vibration analysis, acoustical analysis, speed oscillations, partial discharges, circuit analysis, etc. The analyses based on mechanical concepts are established, but the techniques based on electrical signature analysis are being introduced only now. Because of that status, the application of Electrical Signature Analysis (ESA) to industries is the concern of this chapter.

Czarkowski, D.; Chudnovsky, D.; Chudnovsky, G. & Selesnick, I. (2002). Solving the optimal PWM problem for Single-phase inverters. *IEEE Transactions Circuits Syst*. I, Vol. 49, (April 2002), 465-475

Davis, L. (1991). *The Handbook of Genetic Algorithms*, Van Nostrand & Reinhold, 1991


**Chapter 20** 
