Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical machines. The manufacturers and users of these drives are now keen to include diagnostic features in the software to improve salability and reliability. Apart from locating specific harmonic components in the line current (popularly known as motor current signature analysis), other signals, such as speed, torque, noise, vibration etc., are also explored for their frequency contents. Sometimes, altogether different techniques, such as thermal measurements, chemical analysis, etc., are also employed to find out the nature and the degree of the fault. In addition, human involvement in the actual fault detection decision making is slowly being replaced by automated tools, such as expert systems, neural networks, fuzzy-logic-based systems; to name a few. It is indeed evident that this area is vast in scope. Hence, keeping in mind the need for future research, a review paper describing different types of faults and the signatures they generate and their diagnostics' schemes will not be entirely out of place. In particular, such a review helps to avoid repetition of past work and gives a bird's eye view to a new researcher in this area.

Condition Monitoring and Fault Diagnosis of Electrical Motors&#8212;A Review

This paper investigates diagnostic techniques for electrical machines with special reference to induction machines and to papers published in the last ten years. A comprehensive list of references is reported and examined, and research activities classified into four main topics: 1) electrical faults; 2) mechanical faults; 3) signal processing for analysis and monitoring; and 4) artificial intelligence and decision-making techniques.

Advances in Diagnostic Techniques for Induction Machines

The state of the art of wind energy conversion systems and technologies: A review

Power electronics plays an important role in a wide range of applications in order to achieve high efficiency and performance. Increasing efforts are being made to improve the reliability of power electronics systems to ensure compliance with more stringent constraints on cost, safety, and availability in different applications. This paper presents an overview of the major failure mechanisms of IGBT modules and their handling methods in power converter systems improving reliability. The major failure mechanisms of IGBT modules are presented first, and methods for predicting lifetime and estimating the junction temperature of IGBT modules are then discussed. Subsequently, different methods for detecting open- and short-circuit faults are presented. Finally, fault-tolerant strategies for improving the reliability of power electronic systems under field operation are explained and compared in terms of performance and cost.

Study and Handling Methods of Power IGBT Module Failures in Power Electronic Converter Systems

A breakdown of the electrical insulation system causes catastrophic failure of the electrical machine and brings large process downtime losses. To determine the conditions of the stator insulation system of motor drive systems, various testing and monitoring methods have been developed. This paper presents an in-depth literature review of testing and monitoring methods, categorizing them into online and offline methods, each of which is further grouped into specific areas according to their physical nature. The main focus of this paper is on testing and monitoring techniques that diagnose the condition of the turn-to-turn insulation of low-voltage machines, which is a rapidly expanding area for both research and product development efforts. In order to give a compact overview, the results are summarized in two tables. In addition to monitoring methods on turn-to-turn insulation, some of the most common methods to assess the stator's phase-to-ground and phase-to-phase insulation conditions are included in the tables as well.

A Survey on Testing and Monitoring Methods for Stator Insulation Systems of Low-Voltage Induction Machines Focusing on Turn Insulation Problems

This paper deals with the problem of detection and diagnosis of induction motor faults. Using the fuzzy logic strategy, a better understanding of heuristics underlying the motor faults detection and diagnosis process can be achieved. The proposed fuzzy approach is based on the stator current Concordia patterns. Induction motor stator currents are measured, recorded, and used for Concordia patterns computation under different operating conditions, particularly for different load levels. Experimental results are presented in terms of accuracy in the detection of motor faults and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis if the input data are processed in an advantageous way, which is the case of the Concordia patterns.

https://hal.archives-ouvertes.fr/hal-01052445/document

Induction motor stator faults diagnosis by a current Concordia pattern-based fuzzy decision system

A novel combined MPPT-pitch angle control for wide range variable speed wind turbine based on neural network

Realization and control of a wind turbine connected to the grid by using PMSG

A robust vector control intended for a doubly fed induction motor (DFIM) mode is considered. The state-all-flux induction machine model with a flux orientation constraint is replaced by a simpler control model. The double-flux orientation leads to orthogonality between the stator and rotor fluxes, resulting in a linear and decoupled machine control and an optimal developed torque. The inner flux controllers are designed using the Lyapunov linearisation approach. This flux control is exponentially stabilised independently of the speed. Associated with sliding-mode control, this solution shows good robustness with respect to parameter variations, measurement errors and noisse. Finally, a speed controller is designed using two methods: the first with a PI controller and the second with the Lyapunov method associated with a backstepping procedure, especially employed for the unknown load torques. This second solution shows good robustness with respect to inertia variation and guarantees torque and speed tracking. The global asymptotic stability of the overall system is proven theoretically. The simulation and experimental results largely confirm the effectiveness of the proposed DFIM system control.

Robust backstepping vector control for the doubly fed induction motor

This paper presents a new design of fuzzy logic controller with fuzzy adapted gains (FLC with FAG) for speed regulation of an indirect field-oriented induction motor (IM). Firstly the speed regulation by classical fuzzy logic controller (FLC) is presented. Secondly speed regulation based on suggested FLC with FAG is proposed. The improvements and the performances of the proposed controller based on IM drive are investigated and compared to those obtained using classical FLC at different dynamic operating conditions such as sudden change in command speed, step change in load and some key parameters deviation. A comparison of simulation results shows that FLC with FAG is more robust even under severe variation of some key parameters such as rotor resistance/self-inductance, and inertia. Hence it is found to be a suitable replacement of the standard FLC in order to improve industrial drive performances and robustness in a wide range of changing conditions.

Mohamed-Said Nait-Said

Papers

Induction motor stator faults diagnosis by a current Concordia pattern-based fuzzy decision system

A novel combined MPPT-pitch angle control for wide range variable speed wind turbine based on neural network

Realization and control of a wind turbine connected to the grid by using PMSG

Robust backstepping vector control for the doubly fed induction motor

A new design of fuzzy logic controller with fuzzy adapted gains based on indirect vector control for induction motor drive