An extended Park's vector approach to detect broken bars faults in Induction Motor

Bouslimani, Samir; Drid, Saïd; Chrifi‐Alaoui, Larbi; Bussy, P.; Ouriagli, M.; Delahoche, Laurent

doi:10.1109/sta.2014.7086754

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…After Park vector estimation, various sophisticated methods of signal processing can be used for the detection of fault-related components [ 30 , 35 ]. This approach can be applied for the detection of bearing faults [ 30 , 31 , 35 , 41 , 42 , 43 , 44 , 45 ] as well as other IM faults, such as broken rotor bars [ 46 , 47 , 48 , 49 , 50 , 51 , 52 ] and stator winding faults [ 53 , 54 , 55 , 56 ].…”

Section: Introductionmentioning

confidence: 99%

Novel Investigation of Higher Order Spectral Technologies for Fault Diagnosis of Motor-Based Rotating Machinery

Ciszewski

Gelman

Ball

et al. 2023

Sensors

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In the last decade, research centered around the fault diagnosis of rotating machinery using non-contact techniques has been significantly on the rise. For the first time worldwide, innovative techniques for the diagnosis of rotating machinery, based on electrical motors, including generic, nonlinear, higher-order cross-correlations of spectral moduli of the third and fourth order (CCSM3 and CCSM4, respectively), have been comprehensively validated by modeling and experiments. The existing higher-order cross-correlations of complex spectra are not sufficiently effective for the fault diagnosis of rotating machinery. The novel technology CCSM3 was comprehensively experimentally validated for induction motor bearing diagnosis via motor current signals. Experimental results, provided by the validated technology, confirmed high overall probabilities of correct diagnosis for bearings at early stages of damage development. The novel diagnosis technologies were compared with existing diagnosis technologies, based on triple and fourth cross-correlations of the complex spectra. The comprehensive validation and comparison of the novel cross-correlation technologies confirmed an important non-traditional novel outcome: the technologies based on cross-correlations of spectral moduli were more effective for damage diagnosis than the technologies based on cross-correlations of the complex spectra. Experimental and simulation validations confirmed a high probability of correct diagnosis via the CCSM at the early stage of fault development. The average total probability of incorrect diagnosis for the CCSM3 for all experimental results of 8 tested bearings, estimated via 6528 diagnostic features, was 1.475%. The effectiveness gains in the total probability of incorrect diagnosis for the CCSM3 in comparison with the CCCS3 were 26.8 for the experimental validation and 18.9 for the simulation validation. The effectiveness gains in the Fisher criterion for the CCSM3 in comparison with the CCCS3 were 50.7 for the simulation validation and 104.7 for the experimental validation.

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Section: Introductionmentioning

confidence: 99%

Novel Investigation of Higher Order Spectral Technologies for Fault Diagnosis of Motor-Based Rotating Machinery

Ciszewski

Gelman

Ball

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Then, various sophisticated methods of signal processing [19,26,29] can be used for component fault detection. This approach is used for detection of bearing faults [19,20,29,[37][38][39][40][41], as well as other faults of IMs, such as broken rotor bar [42][43][44][45][46][47][48] and stator winding faults [49][50][51][52].…”

Section: Introductionmentioning

confidence: 99%

Novel Nonlinear High Order Technologies for Damage Diagnosis of Complex Assets

2022

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For the first time worldwide, innovative techniques, generic non-linear higher-order unnormalized cross-correlations of spectral moduli, for the diagnosis of complex assets, are proposed. The normalization of the proposed techniques is based on the absolute central moments, that have been proposed and widely investigated in mathematical works. The existing higher-order, cross-covariances of complex spectral components are not sufficiently effective. The novel technology is comprehensively experimentally validated for induction motor bearing diagnosis via motor current signals. Experimental results, provided by the proposed technique, confirmed high overall probabilities of correct diagnoses for bearings at early stages of damage development. The proposed diagnosis technology is compared with existing diagnosis technology, based on the triple cross-covariance of complex spectral components.

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Gearbox Fault Monitoring Using Induction Machine Electrical Signals

2023

Electrical and Mechanical Fault Diagnosis in Wind Energy Conversion Systems

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An extended Park's vector approach to detect broken bars faults in Induction Motor

Cited by 5 publications

References 8 publications

Novel Investigation of Higher Order Spectral Technologies for Fault Diagnosis of Motor-Based Rotating Machinery

Novel Investigation of Higher Order Spectral Technologies for Fault Diagnosis of Motor-Based Rotating Machinery

Novel Nonlinear High Order Technologies for Damage Diagnosis of Complex Assets

Gearbox Fault Monitoring Using Induction Machine Electrical Signals

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