Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters
Intelligent monitoring and fault diagnosis of PV grid-connected inverters are crucial for the operation and maintenance of PV power plants. However, due to the significant influence of weather conditions on the operating status of PV inverters, the accuracy of traditional fault diagnosis methods fac...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/15/4044 |
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| author | Yuxuan Xie Yaoxi He Yong Zhan Qianlin Chang Keting Hu Haoyu Wang |
| author_facet | Yuxuan Xie Yaoxi He Yong Zhan Qianlin Chang Keting Hu Haoyu Wang |
| author_sort | Yuxuan Xie |
| collection | DOAJ |
| description | Intelligent monitoring and fault diagnosis of PV grid-connected inverters are crucial for the operation and maintenance of PV power plants. However, due to the significant influence of weather conditions on the operating status of PV inverters, the accuracy of traditional fault diagnosis methods faces challenges. To address the issue of open-circuit faults in power switching devices, this paper proposes a multi-dimensional feature perception network. This network captures multi-scale fault features under complex operating conditions through a multi-dimensional dilated convolution feature enhancement module and extracts non-causal relationships under different conditions using convolutional feature fusion with a Transformer. Experimental results show that the proposed network achieves fault diagnosis accuracies of 97.3% and 96.55% on the inverter dataset and the generalization performance dataset, respectively. |
| format | Article |
| id | doaj-art-e103bde38bdc44de9a00982cbeab58cb |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-e103bde38bdc44de9a00982cbeab58cb2025-08-20T03:02:48ZengMDPI AGEnergies1996-10732025-07-011815404410.3390/en18154044Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV InvertersYuxuan Xie0Yaoxi He1Yong Zhan2Qianlin Chang3Keting Hu4Haoyu Wang5China Yangtze Power Co., Ltd., Wuhan 430014, ChinaChina Yangtze Power Co., Ltd., Wuhan 430014, ChinaChina Yangtze Power Co., Ltd., Wuhan 430014, ChinaChina Yangtze Power Co., Ltd., Wuhan 430014, ChinaSchool of Electrical Engineering, Southwest Jiaotong University, Chengdu 610032, ChinaSchool of Electrical Engineering, Southwest Jiaotong University, Chengdu 610032, ChinaIntelligent monitoring and fault diagnosis of PV grid-connected inverters are crucial for the operation and maintenance of PV power plants. However, due to the significant influence of weather conditions on the operating status of PV inverters, the accuracy of traditional fault diagnosis methods faces challenges. To address the issue of open-circuit faults in power switching devices, this paper proposes a multi-dimensional feature perception network. This network captures multi-scale fault features under complex operating conditions through a multi-dimensional dilated convolution feature enhancement module and extracts non-causal relationships under different conditions using convolutional feature fusion with a Transformer. Experimental results show that the proposed network achieves fault diagnosis accuracies of 97.3% and 96.55% on the inverter dataset and the generalization performance dataset, respectively.https://www.mdpi.com/1996-1073/18/15/4044PV grid-connected inverterintelligent fault diagnosisopen-circuit fault |
| spellingShingle | Yuxuan Xie Yaoxi He Yong Zhan Qianlin Chang Keting Hu Haoyu Wang Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters Energies PV grid-connected inverter intelligent fault diagnosis open-circuit fault |
| title | Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters |
| title_full | Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters |
| title_fullStr | Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters |
| title_full_unstemmed | Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters |
| title_short | Multi-Dimensional Feature Perception Network for Open-Switch Fault Diagnosis in Grid-Connected PV Inverters |
| title_sort | multi dimensional feature perception network for open switch fault diagnosis in grid connected pv inverters |
| topic | PV grid-connected inverter intelligent fault diagnosis open-circuit fault |
| url | https://www.mdpi.com/1996-1073/18/15/4044 |
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