Research Article
Monitoring Method of Permanent Magnet Synchronous Motor Temperature Variation Signal Based on Model Prediction
@INPROCEEDINGS{10.1007/978-3-031-50549-2_13, author={Li Liu and Jintian Yin and Dabing Sun and Hui Li and Qunfeng Zhu}, title={Monitoring Method of Permanent Magnet Synchronous Motor Temperature Variation Signal Based on Model Prediction}, proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part III}, proceedings_a={ADHIP PART 3}, year={2024}, month={3}, keywords={Model prediction Permanent magnet synchronous motor Abnormal temperature signal Monitor Wireless sensor technology}, doi={10.1007/978-3-031-50549-2_13} }- Li Liu
Jintian Yin
Dabing Sun
Hui Li
Qunfeng Zhu
Year: 2024
Monitoring Method of Permanent Magnet Synchronous Motor Temperature Variation Signal Based on Model Prediction
ADHIP PART 3
Springer
DOI: 10.1007/978-3-031-50549-2_13
Abstract
In order to improve the monitoring accuracy and quality of permanent magnet synchronous motor (PMSM) temperature variation signal, and achieve the ideal effect of high-precision monitoring of PMSM temperature variation signal, model prediction is introduced, and the monitoring method of PMSM temperature variation signal based on model prediction is studied. The wireless sensor technology is used to collect the temperature signals of various parts of the motor, integrate, clean, replace and protocol the original data, establish a deep learning network model to predict the characteristics of the motor temperature variation, identify the motor temperature variation signal, combine the variation pruning and variation interval, and use the delayed reporting strategy to monitor the early warning of the motor temperature variation signal, complete the monitoring of temperature variation signal of permanent magnet synchronous motor based on model prediction. The experimental analysis results show that the recall rate and accuracy rate of the design method are above 90%, and maintain detection efficiency above 97%, the monitoring accuracy of the temperature variation signal of the permanent magnet synchronous motor is high.
