Interturn short circuit fault diagnosis method of direct-drive permanent magnet synchronous motor based on two-stage PNN

ObjectivesAccurate positioning of early faults is crucial for preventing the deterioration of motor system faults and formulating operation and maintenance strategies after faults.MethodsAiming at the problem that the inter-turn short-circuit fault diagnosis of multi-branch parallel direct-drive permanent magnet synchronous motor (MB-DDPMSM), a novel method of inter-turn short-circuit fault detection and short-circuit coil automatic positioning based on two-stage PNN was proposed. Firstly, according to the special structural characteristics of MB-DDPMSM, the branch difference current (BDC) was selected as the fault branch location characteristic signal, the branch current residual (BRC) was selected as the short-circuit coil location characteristic signal. Secondly, the finite element model of MB-DDPMSM inter-turn short circuit fault state was established, the MB-DDPMSM finite element model was used to analyze the influence of short-circuit coil position on the characteristic signal, and the mapping relationship between BDC and fault branch position, BRC and short-circuit coil position was established. Then, in order to eliminate the influence of fault degree on the characteristic signals and enhance the fault characteristics, the extracted BDC amplitude was normalized by L2 norm to obtain the fault branch location feature vector. The extracted BRC amplitude was normalized by Z-Score to obtain the short-circuit coil positioning feature vector. Finally, a fault diagnosis model based on two-stage PNN was established. The first-stage PNN was used to realize inter-turn short-circuit fault detection and fault branch location, and the second-stage PNN was used to realize short-circuit coil automatic location.ResultsThe simulation and experimental results showed that the proposed method could detect the early inter-turn short-circuit fault in time and realize the accurate positioning of the short-circuit coil, and the recognition accuracy was as high as 100%.ConclusionsThe inter-turn short circuit fault diagnosis model based on two-stage PNN had the advantages of simple modeling, fast convergence speed and high fault diagnosis accuracy.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-03-01
DOI
https://doi.org/10.16186/j.cnki.1673-9787.2023030061
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

Interturn short circuit fault diagnosis method of direct-drive permanent magnet synchronous motor based on two-stage PNN

SHILAP Revista de lepidopterología
Machine Fault Diagnosis Techniques
article

Interturn short circuit fault diagnosis method of direct-drive permanent magnet synchronous motor based on two-stage PNN

article en

Abstract

ObjectivesAccurate positioning of early faults is crucial for preventing the deterioration of motor system faults and formulating operation and maintenance strategies after faults.MethodsAiming at the problem that the inter-turn short-circuit fault diagnosis of multi-branch parallel direct-drive permanent magnet synchronous motor (MB-DDPMSM), a novel method of inter-turn short-circuit fault detection and short-circuit coil automatic positioning based on two-stage PNN was proposed. Firstly, according to the special structural characteristics of MB-DDPMSM, the branch difference current (BDC) was selected as the fault branch location characteristic signal, the branch current residual (BRC) was selected as the short-circuit coil location characteristic signal. Secondly, the finite element model of MB-DDPMSM inter-turn short circuit fault state was established, the MB-DDPMSM finite element model was used to analyze the influence of short-circuit coil position on the characteristic signal, and the mapping relationship between BDC and fault branch position, BRC and short-circuit coil position was established. Then, in order to eliminate the influence of fault degree on the characteristic signals and enhance the fault characteristics, the extracted BDC amplitude was normalized by L2 norm to obtain the fault branch location feature vector. The extracted BRC amplitude was normalized by Z-Score to obtain the short-circuit coil positioning feature vector. Finally, a fault diagnosis model based on two-stage PNN was established. The first-stage PNN was used to realize inter-turn short-circuit fault detection and fault branch location, and the second-stage PNN was used to realize short-circuit coil automatic location.ResultsThe simulation and experimental results showed that the proposed method could detect the early inter-turn short-circuit fault in time and realize the accurate positioning of the short-circuit coil, and the recognition accuracy was as high as 100%.ConclusionsThe inter-turn short circuit fault diagnosis model based on two-stage PNN had the advantages of simple modeling, fast convergence speed and high fault diagnosis accuracy.

SHILAP Revista de lepidopterología
Henan Polytechnic University (CN)
Openalex Percentile: Top 47%
Machine Fault Diagnosis Techniques
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