Diagnosis of broken rotor bar fault in open‐ and closed‐loop controlled wye‐connected induction motors using zero‐sequence voltage

High-efficiency motors are being gradually introduced in many industrial applications because of their positive impacts on the environment by reducing energy consumption and CO 2 emission. In this respect, line start permanent magnet synchronous motors (LS-PMSMs) have been introduced recently. Due to their unique configuration, LS-PMSMs allow the obtaining of super premium efficiency levels, accompanied with a high torque and power factor. However, since the use of LS-PMSMs in the industry is in its infancy, no efficient scheme has yet been reported for broken rotor bar (BRB) fault detection in this type of motor. Accordingly, the main aim of this research is to investigate the fault-related feature for BRB faults on LS-PMSMs. In this regard, a simulation model and experimental setup for the investigation of BRB in LS-PMSM are implemented. The detection strategy for BRB in LS-PMSM proposed here is based on the monitoring of the start-up current signal and discrete wavelet transform. The entropy features are used as fault-related features for BRB faults. Finally, the ability of these features is validated for the detection of BRB in LS-PMSM through statistical analysis. In this research, the importance of the starting load is also considered for BRB detection in LS-PMSMs.

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“…[6][7][8][9][10][11][12][13][14][15][16][17][18][19].53] Na A Na A Approximation (7) [19.53-0] Na Na Na Na A: Applicable; Na: Not applicable.…”

Section: Log-energy Entropymentioning

confidence: 99%

Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

et al. 2017

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“…However, these studies were unable to accurately locate fault positions; they could only indicate the phase or zone of faults. When considering a systematic component [25][26][27][28], the voltage and current of all sequences depend on the unbalanced conditions [25]; however, zero-sequence voltage and current can be used to estimate the fault position in a distribution system [26]. Similarly, the Fourier transform (FT) of zero-sequence voltage and current has been employed to obtain the vectors This work is licensed under a Creative Commons Attribution 4.0 License.…”

Section: Introductionmentioning

confidence: 99%

Discriminating Between Capacitor Bank Faults and External Faults for an Unbalanced Current Protection Relay Using DWT

Lertwanitrot

Ngaopitakkul

2020

IEEE Access

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Capacitor faults are a common issue in modern-day power systems. Such systems employ a traditional mechanism that solely relies on unbalanced relays as an indicator of faults in capacitor banks; however, in the case of a relay trip, operators may find it difficult to identify the cause of these faults. To address this issue, this study aims to detect and discriminate between faults in the capacitor bank (i.e., internal faults) and those in the transmission line (i.e., external faults) by employing discrete wavelet transform (DWT). For this purpose, simulations were conducted using PSCAD software and modelled according to the 115-kV system from the Electricity Generating Authority of Thailand (EGAT). Furthermore, case studies involving faults with different phases, side and branch connections, row connections, inception angles, and blown fuses were considered. Moreover, the phase current, unbalanced current, and unbalanced voltage were analyzed to elucidate fault behaviors and the variation in the coefficient obtained via DWT; the unbalanced current and unbalanced voltage were used as design criteria for the proposed detection and relay operation algorithm. Real-world signals were employed to verify the accuracy of the proposed model. The results indicate that the proposed algorithm achieves satisfactory accuracy in terms of fault detection and the operation of relays in capacitor banks. The proposed algorithm is expected to enable an improvement in the performance of protection systems for capacitor banks in the near future.

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“…Various damage types were found, such as interturn short-circuit [1], broken rotor bar [2], bearing inner ring failure, bearing outer ring failure, ball failure, cage failure [3], and eccentricity [4]. As for fault diagnosis of an induction motor, the literature has also indicated that approximately 30% of motor breakdowns are related to stators, 10% to rotors, 40% to bearings, and 20% to other components [5].…”

Section: Introductionmentioning

confidence: 99%

Induction Motors Condition Monitoring System with Fault Diagnosis Using a Hybrid Approach

et al. 2019

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This study develops a condition monitoring system, which includes operating condition monitoring (OCM) and fault diagnosis analysis (FDA). The OCM uses a vibration detection approach based on the ISO 10816-1 and NEMA MG-1 international standards, and the FDA uses a vibration-electrical hybrid approach based on various indices. The system can acquire real-time vibration and electrical signals. Once an abnormal vibration has been detected by using OCM, the FDA is applied to classify the type of faults. Laboratory results indicate that the OCM can successfully diagnose induction motors healthy condition, and FDA can classify the various damages stator fault, rotor fault, bearing fault and eccentric fault. The FDA with the hybrid approach is more reliable than the traditional approach using electrical detection alone. The proposed condition monitoring system can provide simple and clear maintenance information to improve the reliability of motor operations.

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Diagnosis of broken rotor bar fault in open‐ and closed‐loop controlled wye‐connected induction motors using zero‐sequence voltage

Cited by 25 publications

References 49 publications

Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

Discriminating Between Capacitor Bank Faults and External Faults for an Unbalanced Current Protection Relay Using DWT

Induction Motors Condition Monitoring System with Fault Diagnosis Using a Hybrid Approach

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