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

Time--frequency feature representation using energy concentration: An overview of recent advances

In this paper, the authors propose a method for the diagnosis of rotor bar failures in induction machines, based on the analysis of the stator current during the startup using the discrete wavelet transform (DWT). Unlike other approaches, the study of the high-order wavelet signals resulting from the decomposition is the core of the proposed method. After an introduction of the physical and mathematical bases of the method, a description of the proposed approach is given; for this purpose, a numerical model of induction machine is used in such a way that the effects of a bar breakage can clearly be shown, avoiding the influence of other phenomena not related with the fault. Afterward, the new diagnosis method is validated using a set of commercial induction motors. Several experiments are developed under different machine conditions (healthy machine and machine with different levels of failure) and operating conditions (no load, full load, pulsating load, and fluctuating voltage). In each case, the results are compared with those obtained using the classical approach, based on the analysis of the steady-state current using the Fourier transform. Finally, the results are discussed, and some considerations about the influence of the DWT parameters (type of mother wavelet, order of the mother wavelet, sampling rate, or number of levels of the decomposition) over the diagnosis are done

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Validation of a new method for the diagnosis of rotor bar failures via wavelet transform in industrial induction machines

In this paper, a general methodology based on the application of discrete wavelet transform (DWT) to the diagnosis of the cage motor condition using transient stator currents is exposed. The approach is based on the identification of characteristic patterns introduced by fault components in the wavelet signals obtained from the DWT of transient stator currents. These patterns enable a reliable detection of the corresponding fault as well as a clear interpretation of the physical phenomenon taking place in the machine. The proposed approach is applied to the detection of rotor asymmetries in two alternative ways, i.e., by using the startup current and by using the current during plugging stopping. Mixed eccentricities are also detected by means of the transient-based methodology. This paper shows how the evolution of other non-fault-related components such as the principal slot harmonic (PSH) can be extracted with the proposed technique. A compilation of experimental cases regarding the application of the methodology to the previous cases is presented. Guidelines for the easy application of the methodology by any user are also provided under a didactic perspective.

A General Approach for the Transient Detection of Slip-Dependent Fault Components Based on the Discrete Wavelet Transform

This paper provides a comprehensive list of books, workshops, conferences, and journal papers related to induction motors faults detection and diagnosis.

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Bibliography on induction motors faults detection and diagnosis

Previous work at The Robert Gordon University has shown that
faults within the rotors of large three phase induction motors, such as
broken rotor bars, can be detected by monitoring and analysing the line
current taken by the machine during a no-load starting transient. This
line current has been shown to contain frequency components which are
indicative of these fault conditions. Under transient conditions these
components are however nonstationary in both the time and frequency
domains. A variety of signal processing strategies applicable to time
variant data such as the spectrogram, The Wigner Ville distribution and
wavelet decomposition have been implemented and their success in
detecting these non-stationary components evaluated. The most suitable
of these techniques has been used to determine the occurrence and
severity of motor faults. Preliminary work suggests that these
techniques may also be used to detect frequency components indicative to
the location of the fault

https://ieeexplore.ieee.org/iel3/3896/11325/00515308.pdf

The application of modern signal processing techniques to rotor fault detection and location within three phase induction motors

The application of modern signal processing techniques for use in rotor fault detection and location within three-phase induction motors

This paper shows that it is possible to monitor the supply current to an induction motor during the motors acceleration period and be able to detect the nonstationary frequency components previously monitored whilst stationary during the motors steady state operation Results show that the increase in component amplitude observed with a faulty rotor when monitoring in steady state under full load conditions can clearly be observed when monitoring the transient signal under no load conditions Using a signal processing technique known as wavelet decomposition it is shown that the sidebands may be tracked during the transient period This technique has been simplified and implemented along with a data acquisition system to form a complete current transient health monitoring system which determines the health of the motor from its no load supply current transient signal The software which controls both the acquisition and analysis part of the monitoring system has been developed so that the operator has access to all main parameters used within the analysis

http://ieeexplore.ieee.org/iel3/3529/10613/00497715.pdf

R. Burnett

Papers

The application of modern signal processing techniques to rotor fault detection and location within three phase induction motors

The application of modern signal processing techniques for use in rotor fault detection and location within three-phase induction motors

The current analysis program-a software tool for rotor fault detection in three phase induction motors