Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network
The high correlation between rolling bearing composite faults and single fault samples is prone to misclassification. Therefore, this paper proposes a rolling bearing composite fault diagnosis method based on a deep graph convolutional network. First, the acquired raw vibration signals are pre-proce...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/20/8489 |
| _version_ | 1797572310682566656 |
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| author | Caifeng Chen Yiping Yuan Feiyang Zhao |
| author_facet | Caifeng Chen Yiping Yuan Feiyang Zhao |
| author_sort | Caifeng Chen |
| collection | DOAJ |
| description | The high correlation between rolling bearing composite faults and single fault samples is prone to misclassification. Therefore, this paper proposes a rolling bearing composite fault diagnosis method based on a deep graph convolutional network. First, the acquired raw vibration signals are pre-processed and divided into sub-samples. Secondly, a number of sub-samples in different health states are constructed as graph-structured data, divided into a training set and a test set. Finally, the training set is used as input to a deep graph convolutional neural network (DGCN) model, which is trained to determine the optimal structure and parameters of the network. A test set verifies the feasibility and effectiveness of the network. The experimental result shows that the DGCN can effectively identify compound faults in rolling bearings, which provides a new approach for the identification of compound faults in bearings. |
| first_indexed | 2024-03-10T20:54:26Z |
| format | Article |
| id | doaj.art-1ea62ff798284f5b820e2dfc8efbbef9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T20:54:26Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1ea62ff798284f5b820e2dfc8efbbef92023-11-19T18:03:42ZengMDPI AGSensors1424-82202023-10-012320848910.3390/s23208489Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional NetworkCaifeng Chen0Yiping Yuan1Feiyang Zhao2School of Mechanical Engineering, Xinjiang University, Urumqi 830047, ChinaSchool of Mechanical Engineering, Xinjiang University, Urumqi 830047, ChinaSchool of Mechanical Engineering, Xinjiang University, Urumqi 830047, ChinaThe high correlation between rolling bearing composite faults and single fault samples is prone to misclassification. Therefore, this paper proposes a rolling bearing composite fault diagnosis method based on a deep graph convolutional network. First, the acquired raw vibration signals are pre-processed and divided into sub-samples. Secondly, a number of sub-samples in different health states are constructed as graph-structured data, divided into a training set and a test set. Finally, the training set is used as input to a deep graph convolutional neural network (DGCN) model, which is trained to determine the optimal structure and parameters of the network. A test set verifies the feasibility and effectiveness of the network. The experimental result shows that the DGCN can effectively identify compound faults in rolling bearings, which provides a new approach for the identification of compound faults in bearings.https://www.mdpi.com/1424-8220/23/20/8489intelligent compound fault diagnosisdeep graph convolutional neural networkroller bearing |
| spellingShingle | Caifeng Chen Yiping Yuan Feiyang Zhao Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network Sensors intelligent compound fault diagnosis deep graph convolutional neural network roller bearing |
| title | Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network |
| title_full | Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network |
| title_fullStr | Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network |
| title_full_unstemmed | Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network |
| title_short | Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network |
| title_sort | intelligent compound fault diagnosis of roller bearings based on deep graph convolutional network |
| topic | intelligent compound fault diagnosis deep graph convolutional neural network roller bearing |
| url | https://www.mdpi.com/1424-8220/23/20/8489 |
| work_keys_str_mv | AT caifengchen intelligentcompoundfaultdiagnosisofrollerbearingsbasedondeepgraphconvolutionalnetwork AT yipingyuan intelligentcompoundfaultdiagnosisofrollerbearingsbasedondeepgraphconvolutionalnetwork AT feiyangzhao intelligentcompoundfaultdiagnosisofrollerbearingsbasedondeepgraphconvolutionalnetwork |