Research on Fault Diagnosis of Ship Propulsion System Based on Improved Residual Network
In ship propulsion, accurately diagnosing faults in permanent magnet synchronous motor is essential but challenging due to limitations in the intuitive characterization and feature extraction of fault signals. This study presents an innovative approach to motor fault detection by integrating phase-c...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/13/1/70 |
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| Summary: | In ship propulsion, accurately diagnosing faults in permanent magnet synchronous motor is essential but challenging due to limitations in the intuitive characterization and feature extraction of fault signals. This study presents an innovative approach to motor fault detection by integrating phase-contrastive current dot patterns with an enhanced residual network, enhancing the diagnostic effect. Initially, the research involves creating a dataset that simulates stator currents. It is achieved through mathematical modeling of two common faults in permanent magnet synchronous motors: inter-turn short circuits and demagnetization. Subsequently, the parameters of the phase-contrastive current dot pattern are optimized using the Hunter-Prey Optimization technique to convert the three-phase stator currents of the motor into grayscale images. Lastly, a residual network, which includes a Squeeze-and-Excitation module, is engineered to boost the identification of crucial fault characteristics. The experimental results show that the proposed method achieves a high accuracy rate of 98.5% in the fault diagnosis task of motors, which can accurately identify the fault information and is significant in enhancing the reliability and safety of ship propulsion systems. |
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| ISSN: | 2077-1312 |