With the continuous increase in complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease, and safety hazards, which greatly necessitates to detect and identify any kinds of potential abnormalities and faults as early as possible and implement real-time fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results have been reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. In this paper, fault diagnosis approaches and their applications are comprehensively reviewed from model- and signal-based perspectives, respectively.

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A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

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

In this paper, an online induction motor diagnosis system using motor current signature analysis (MCSA) with advanced signal-and-data-processing algorithms is proposed. MCSA is a method for motor diagnosis with stator-current signals. The proposed system diagnoses induction motors having four types of faults such as breakage of rotor bars and end rings, short-circuit of stator windings, bearing cracks, and air-gap eccentricity. Although MCSA is one of the most powerful online methods for diagnosing motor faults, it has some shortcomings, which degrade performance and accuracy of a motor-diagnosis system. Therefore, advanced signal-and-data-processing algorithms are proposed. They are composed of an optimal-slip-estimation algorithm, a proper-sample-selection algorithm, and a frequency auto search algorithm for achieving MCSA efficiently. The proposed system is able to ascertain four kinds of motor faults and diagnose the fault status of an induction motor. Experimental results obtained on 3.7-kW and 30-kW three-phase squirrel-cage induction motors and voltage-source inverters with a vector-control technique are discussed

Online Diagnosis of Induction Motors Using MCSA

Medium-voltage (MV) induction motors are widely used in the industry and are essential to industrial processes. The breakdown of these MV motors not only leads to high repair expenses but also causes extraordinary financial losses due to unexpected downtime. To provide reliable condition monitoring and protection for MV motors, this paper presents a comprehensive survey of the existing condition monitoring and protection methods in the following five areas: thermal protection and temperature estimation, stator insulation monitoring and fault detection, bearing fault detection, broken rotor bar/end-ring detection, and air gap eccentricity detection. For each category, the related features of MV motors are discussed; the effectiveness of the existing methods are discussed in terms of their robustness, accuracy, and implementation complexity. Recommendations for the future research in these areas are also presented.

A Survey of Condition Monitoring and Protection Methods for Medium-Voltage Induction Motors

Condition monitoring of rotating electrical machinery has received intense research interest for more than 30 years. However, electrical machinery has been considered reliable and the application of fast-acting digital electrical protection has rather reduced the attention operators pay to the equipment. The area based upon current literature and the author's experience is reviewed. There are three restrictions: only on-line techniques for rotating machines are dealt with; specific problems of variable speed drives are not dealt with, except in passing; conventional rather than emerging brushless, reluctance and permanent magnet machines of unusual topology are concentrated upon. The art of condition monitoring is minimalist, to take minimum measurements from a machine necessary to extract a diagnosis, so that a condition can be rapidly inferred, giving a clear indication of incipient failure modes. The current state of the art is reviewed in the following ways: survey developments in condition monitoring of machines, mechanically and electrically, over the last 30 years; put that work in context alongside the known failure mechanisms; review those developments which have proved successful and identify areas of research which require attention in the future to advance the subject.

Review of condition monitoring of rotating electrical machines

This paper develops a winding-function-based method for modeling polyphase cage induction motors with inter-turn short circuits in the machine stator winding. Analytical consideration which sheds light on some components of the stator current spectra of both healthy and faulty machines is developed. It is shown that, as a result of the nature of the cage rotor, no new frequency components of the line current spectra can appear as a consequence of the fault. Only a rise in some of the frequency components which already exist in the line current spectra of a healthy machine can be observed. An experimental setup comprising a 3 kW delta-connected motor loaded by a generator was used to validate this approach. The experimental results obtained clearly validate the analytical and simulation results.

The detection of inter-turn short circuits in the stator windings of operating motors

The paper describes a method for the dynamic simulation of dynamic rotor eccentricity in squirrel cage rotor induction machines. The method is based on a winding function approach, which allows for all harmonics of magnetomotive force to be taken into account. It is demonstrated how this complex dynamic regime can be modeled using the mutual inductance curves of symmetrical machine using proper scaling techniques. Experimental results demonstrate the effectiveness of the proposed technique and validate the theoretical analysis.

Dynamic simulation of dynamic eccentricity in induction machines-winding function approach

Before applying current-signature-analysis-based monitoring methods, it is necessary to thoroughly analyze the existence of the various harmonics on healthy machines. As such an analysis is only done in very few papers, the objective of this paper is to make a clear and rigorous characterization and classification of the harmonics present in a healthy cage rotor induction motor spectrum as a starting point for diagnosis. Magnetomotive force space harmonics, slot permeance harmonics, and saturation of main magnetic flux path through the virtual air-gap permeance variation are taken into analytical consideration. General rules are introduced giving a connection between the number of stator slots, rotor bars, and pole pairs and the existence of rotor slot harmonics as well as saturation-related harmonics in the current spectrum. For certain combinations of stator and rotor slots, saturation-related harmonics are shown to be most prominent in motors with a pole pair number of two or more. A comparison of predicted and measured current harmonics is given for several motors with different numbers of pole pairs, stator slots, and rotor bars.

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Stator-Current Spectrum Signature of Healthy Cage Rotor Induction Machines

This paper shows that a static eccentricity makes rise a double fundamental frequency ripple in the rotor current of salient-pole synchronous machines. This ripple leads, under conditions ruled by the stator windings, to precise signatures in the no-load voltage spectrum. Both rotor current ripple and voltage harmonics can be used for diagnosis. The fault-related voltage harmonics are theoretically previewed in this paper through analysis of the windings. Simulations performed by using the winding function approach confirm the theoretical predictions. A four-pole 15-kVA generator was used for experiments, featuring an innovative flange with exact and easy regulation of mixed-type eccentricities. Rotor current monitoring has advantages of single-sensor measure and accentuate fault sensitivity. Experiments also showed an additional rotor-rotation frequency ripple in the rotor current, in case of mixed-type fault.

Harmonic Signatures of Static Eccentricities in the Stator Voltages and in the Rotor Current of No-Load Salient-Pole Synchronous Generators

This paper describes a method for the dynamic simulation of a cage induction machine with static and dynamic air gap eccentricity. The method is based on the winding function theory and extension of this theory to the nonuniform air gap case. A method of calculating all inductances in a machine with both static and dynamic air gap eccentricity is presented and a numerical analysis of a machine with specified parameters is presented. Stator line current spectra collected experimentally for both the static and dynamic eccentricity conditions confirm the results obtained by the proposed numerical model.

Gojko Joksimovic

Papers

The detection of inter-turn short circuits in the stator windings of operating motors

Dynamic simulation of dynamic eccentricity in induction machines-winding function approach

Stator-Current Spectrum Signature of Healthy Cage Rotor Induction Machines

Harmonic Signatures of Static Eccentricities in the Stator Voltages and in the Rotor Current of No-Load Salient-Pole Synchronous Generators

Dynamic simulation of cage induction machine with air gap eccentricity