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

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

Research has picked up a fervent pace in the area of fault diagnosis of electrical machines. Like adjustable speed drives, fault prognosis has become almost indispensable. The manufacturers of these drives are now keen to include diagnostic features in the software to decrease machine down time and improve salability. Prodigious improvement in signal processing hardware and software has made this possible. Primarily, these techniques depend upon locating specific harmonic components in the line current, also known as motor current signature analysis (MCSA). These harmonic components are usually different for different types of faults. However with multiple faults or different varieties of drive schemes, MCSA can become an onerous task as different types of faults and time harmonics may end up generating similar signatures. Thus 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. 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. Keeping in mind the need for future research, this review paper describes different types of faults and the signatures they generate and their diagnostics' schemes.

Condition monitoring and fault diagnosis of electrical machines-a review

Condition monitoring of induction motors is a fast emerging technology for online detection of incipient faults. It avoids unexpected failure of a critical system. Approximately 30-40% of faults of induction motors are stator faults. This work presents a comprehensive review of various stator faults, their causes, detection parameters/techniques, and latest trends in the condition monitoring technology. It is aimed at providing a broad perspective on the status of stator fault monitoring to researchers and application engineers using induction motors. A list of 183 research publications on the subject is appended for quick reference.

A review of stator fault monitoring techniques of induction motors

Detection of rotor slot and other eccentricity related harmonics in the line current of a three phase induction motor is important both from the viewpoint of sensorless speed estimation as well as eccentricity related fault detection. However, it is now clear that not all three phase induction motors are capable of generating such harmonics in the line current. Recent research has shown that the presence of these harmonics is primarily dependent on the number of rotor slots and the number of fundamental pole pairs of the machine. While the number of fundamental pole pairs of a three phase induction motor usually is within one to four (higher pole pairs are generally avoided due to increased magnetizing current), the number of rotor slots can vary widely. The present paper investigates this phenomenon further and obtains a hitherto nebulous theoretical basis for the experimentally verified results. Detailed coupled magnetic circuit simulation results are presented for a four pole, three phase induction motor with 44, 43, and 42 rotor slots under healthy, static, dynamic and mixed eccentricity conditions. The simulation is flexible enough to accommodate other pole numbers also. These simulations are helpful in quantifying the predicted harmonics under different combinations of load, pole pair numbers, rotor slots and eccentricity conditions, thus making the problem easier for drive designers or diagnostic tools' developers. Data from three different induction machines, namely, a 4 pole, 44 bar, 3 hp, a 4 pole, 28 bar, 3 hp and a 2 pole, 39 bar, 100 hp motor have been used to verify the results experimentally. The simulation and the experimental results clearly validate the theoretical findings put forward in this paper.

Detection of Rotor Slot and Other Eccentricity-Related Harmonics in a Three-Phase Induction Motor with Different Rotor Cages

A substantial portion of induction motor faults is eccentricity related. In practice, static as well as dynamic eccentricities happen to exist together. With this point in mind, an analytical approach to evaluate performance of a three-phase induction motor under mixed eccentric condition has been presented in this paper. Clear and step-by-step theoretical analysis, explaining completely the presence of certain harmonics in the line current spectrum in presence of eccentricity, is discussed. More importantly, it is shown for the first time that a link exists between the lowi and the high-frequency elements of these harmonics. It is also shown that these high-frequency components are not very strong in all types of machines. These results will be useful in generating rules and laws to formulate on-line tools for machine condition monitoring. Finite element results to substantiate the inductance values used in the simulation are also included. The analysis is validated by the line current spectrum of the eccentric machine obtained through simulation using modified winding function approach (MWFA) and experimentation.

Performance analysis of a three-phase induction motor under mixed eccentricity condition

A new approach has been proposed in this paper to detect broken rotor bars in induction motors. The motor is disconnected from the supply; and the induced voltage in the stator due to only rotor flux is utilized to detect the fault, If there is any broken bar, it will directly affect the induced voltages in the stator windings. Using this approach the effects of source nonidealities (such as unbalance, presence of time harmonics, etc.) and nonlinearity of machine magnetizing characteristics due to saturation can be avoided.

A novel approach for broken rotor bar detection in cage induction motors

Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis

Traditionally, for medium- and high-voltage motors and generators, condition-based monitoring of stator faults is performed by measuring partial discharge activities. For low-voltage machines, negative-sequence impedance or currents are measured for the same. Such diagnostic schemes should be carefully implemented as supply voltage unbalance, manufacturing-related asymmetry, etc., also produce negative-sequence voltages. A few approaches based on motor current signature analysis have already been proposed to detect stator interturn faults. However, little or no physical insight was provided to explain the occurrence of certain harmonics in the line current or the influence of voltage unbalance on these harmonics. Also, in at least one of these papers, a large portion of the stator winding was shorted to emulate the faults. The method proposed in this paper monitors certain rotor-slot-related harmonics at the terminal voltage of the machine, once it is switched off. In the absence of supply voltage, issues such as voltage unbalance, time harmonics do not influence the measurements except as initial conditions, which is a very desirable feature when the machine is fed from an adjustable-speed drive. Satisfactory simulation and experimental results have been obtained with only about 1.5% (5/324) of the total number of turns shorted.

Subhasis Nandi

Papers

Detection of Rotor Slot and Other Eccentricity-Related Harmonics in a Three-Phase Induction Motor with Different Rotor Cages

Performance analysis of a three-phase induction motor under mixed eccentricity condition

A novel approach for broken rotor bar detection in cage induction motors

Electric Machines: Modeling, Condition Monitoring, and Fault Diagnosis

Novel frequency-domain-based technique to detect stator interturn faults in induction machines using stator-induced voltages after switch-off