Broken rotor bar fault detection using Hilbert transform and neural networks applied to direct torque control of induction motor drive

R, Senthil Kumar; Irudayaraj, Gerald Christopher Raj; Saravanan, S.; Subramaniam, Umashankar

doi:10.1049/iet-pel.2019.1543

Cited by 38 publications

(24 citation statements)

References 37 publications

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“…Another solution to discriminate the sideband harmonics from fundamental current component was proposed in [93][94][95]. This solution was based on applying the Hilbert transform (HT) to the sampled current to calculate the current analytical signal or the current envelop.…”

Section: ) Envelop Spectrum Analysis-based Methodsmentioning

confidence: 99%

Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

2022

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Motors are the higher energy-conversion devices that consume around 40% of the global electrical generated energy. Induction motors are the most popular motor type due to their reliability, robustness, and low cost. Therefore, both condition monitoring and fault diagnosis of induction motor faults have motivated considerable research efforts. In this paper, a comprehensive review of the recent techniques proposed in the literature for broken bar faults detection and diagnosis is presented. This paper mainly investigates the fault detection methods in line-fed and inverter-fed motors proposed after 2015 and published in most relevant journals and conferences. The introduced review has deeply discussed the main features of the reported methods and compared them in many different aspects. Finally, the study has highlighted the main issues and the gaps that require more attention from researchers in this field.

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Section: ) Envelop Spectrum Analysis-based Methodsmentioning

confidence: 99%

Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

2022

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“… Fault Type Causes Input Signal Detection Methods Reference Bearing fabrication defects, incorrect lubrication, overload. Current Continuous Wavelet Transform (CWT) [ 8 ] Broken rotor bars (BRB) Thermal-stresses, corrosion, Poor manufacturing Current Hilbert transform and neural networks [ 9 ] Rotor unbalance Misalignment, bearing wear Current Discrete Wavelet Transform (DWT) [ 10 ] Stator winding Over-heating, mechanical stresses, over-voltages, Current Park's vectors and MCSA [ 11 ] …”

Section: Introductionmentioning

confidence: 99%

An experimental method for diagnostic of incipient broken rotor bar fault in induction machines

Sabir

Ouassaid

Ngote

2022

Heliyon

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“…Furthermore, the Hilbert transform (HT) is a timefrequency signal processing method. It is one of the fastest high-frequency fault detection methods and has been implemented in different applications, especially on motor fault detections [25][26][27]. In [26], the current envelope of the stator is utilised by HT for fault detection inside of motors.…”

Section: Introductionmentioning

confidence: 99%

EMD/HT‐based local fault detection in DC microgrid clusters

et al. 2022

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DC faults can create serious damages if not detected and isolated in a short time. This paper proposes a fault detection technique for DC faults to enhance the protection of DC microgrid clusters. To detect such faults accurately and quickly, a DC fault detection scheme using empirical mode decomposition and Hilbert transform is proposed. Due to the strict time limits for fault interruption caused by fast high‐rising fault currents in DC systems, DC microgrid clusters' protection remains a challenging task. Furthermore, high impedance faults (HIFs) in DC systems cause a small change in the current, which can damage the power electronic converters if not detected in time. Therefore, this paper proposes a local scheme for the fast detection of faults including HIFs in DC microgrid clusters. Both simulation and experimental results using a scaled DC microgrid cluster prototype and considering several scenarios (such as low impedance faults, HIFs, noise, overload, and bad calibration of sensors) demonstrate the successful and fast detection (less than 2 ms) of DC faults by the proposed method. Compared with other techniques, the proposed scheme presents its merits from the viewpoints of accuracy and speed.

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Broken rotor bar fault detection using Hilbert transform and neural networks applied to direct torque control of induction motor drive

Cited by 38 publications

References 37 publications

Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

An experimental method for diagnostic of incipient broken rotor bar fault in induction machines

EMD/HT‐based local fault detection in DC microgrid clusters

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