@ARTICLE{Wang_Jianping_Diagnosis_2024,
 author={Wang, Jianping and Ma, Jian and Meng, Dean and Zhao, Xuan and Zhang, Kai and Liu, Qiquan and Xu, Kejie},
 volume={72},
 number={2},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={e148943},
 howpublished={online},
 year={2024},
 abstract={Inter-turn short circuit (ITSC) is a frequent fault of interior permanent magnet synchronous motors (IPMSM). If ITSC faults are not promptly monitored, it may result in secondary faults or even cause extensive damage to the entire motor. To enhance the reliability of IPMSMs, this paper introduces a fault diagnosis method specifically designed for identifying ITSC faults in IPMSMs. The sparse coefficients of phase current and torque are solved by clustering shrinkage stage orthogonal matching tracking (CcStOMP) in the greedy tracking algorithm.The CcStOMP algorithm can extract multiple target atoms at one time, which greatly improves the iterative efficiency. The multiple features are utilized as input parameters for constructing the random forest classifier. The constructed random forest model is used to diagnose ITSC faults with the results showing that the random forest model has a diagnostic accuracy of 98.61% using all features, and the diagnostic accuracy of selecting three of the most important features is still as high as 97.91%. The random forest classification model has excellent robustness that maintains high classification accuracy despite the reduction of feature vectors, which is a great advantage compared to other classification algorithms. The combination of greedy tracing and the random forest is not only a fast diagnostic model but also a model with good generalisation and anti-interference capability. This non-invasive method is applicable to monitoring and detecting failures in industrial PMSMs.},
 type={Article},
 title={Diagnosis of inter-turn short circuit fault in IPMSMs based on the combined use of greedy tracking and random forest},
 URL={http://www.czasopisma.pan.pl/Content/130024/PDF-MASTER/BPASTS_2023_72_2_3659.pdf},
 doi={10.24425/bpasts.2024.148943},
 keywords={Inter-turn short circuit (ITSC), Interior permanent magnet synchronous motors (IPMSM), Matching-Pursuit (CcStOMP) algorithm, sparse coefficients, random forest},
}