Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data
The existing intelligent fault diagnosis methods face challenges, such as model training relying on a large amount of labeled data, difficulty in obtaining fault data with different occurrence probabilities, and insufficient consideration of the impact of operating conditions. To address these chall...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2024-01-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails?columnId=75892667&Fpath=home&index=0 |
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| _version_ | 1841546870390784000 |
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| author | Tian Juan Xie Gang Zhang Shun Wang Yufei |
| author_facet | Tian Juan Xie Gang Zhang Shun Wang Yufei |
| author_sort | Tian Juan |
| collection | DOAJ |
| description | The existing intelligent fault diagnosis methods face challenges, such as model training relying on a large amount of labeled data, difficulty in obtaining fault data with different occurrence probabilities, and insufficient consideration of the impact of operating conditions. To address these challenges, a novel gearbox diagnosis method for adaptive inter-class and intra-class unbalanced fault data under varying working conditions was proposed. Firstly, a gated local connection network was utilized to reduce the reliance on the labeled data and extract intrinsic features directly from the original data. Secondly, a parallel mechanism of external and internal attention was designed to consider the distribution differences among inter-class and intra-class faults under different working conditions, adjusting the weights of extracted features accordingly. Finally, focal loss function was employed to focus on minority and challenging samples, enabling high-quality mining of unbalanced diagnostic information. The proposed method was demonstrated by six unbalanced gearbox datasets, which shows great effectiveness and superiority in identifying unbalanced fault data. |
| format | Article |
| id | doaj-art-04fba4c3437242e9be2ecaef58fa3d66 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2024-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-04fba4c3437242e9be2ecaef58fa3d662025-01-10T15:01:35ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392024-01-0111075892667Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault DataTian JuanXie GangZhang ShunWang YufeiThe existing intelligent fault diagnosis methods face challenges, such as model training relying on a large amount of labeled data, difficulty in obtaining fault data with different occurrence probabilities, and insufficient consideration of the impact of operating conditions. To address these challenges, a novel gearbox diagnosis method for adaptive inter-class and intra-class unbalanced fault data under varying working conditions was proposed. Firstly, a gated local connection network was utilized to reduce the reliance on the labeled data and extract intrinsic features directly from the original data. Secondly, a parallel mechanism of external and internal attention was designed to consider the distribution differences among inter-class and intra-class faults under different working conditions, adjusting the weights of extracted features accordingly. Finally, focal loss function was employed to focus on minority and challenging samples, enabling high-quality mining of unbalanced diagnostic information. The proposed method was demonstrated by six unbalanced gearbox datasets, which shows great effectiveness and superiority in identifying unbalanced fault data.http://www.jxcd.net.cn/thesisDetails?columnId=75892667&Fpath=home&index=0Fault diagnosisInter-class and intra-class imbalancesGated local connection network Attention parallel mechanismFocal loss |
| spellingShingle | Tian Juan Xie Gang Zhang Shun Wang Yufei Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data Jixie chuandong Fault diagnosis Inter-class and intra-class imbalances Gated local connection network Attention parallel mechanism Focal loss |
| title | Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data |
| title_full | Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data |
| title_fullStr | Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data |
| title_full_unstemmed | Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data |
| title_short | Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data |
| title_sort | adaptive diagnosis method based on gearbox unbalanced fault data |
| topic | Fault diagnosis Inter-class and intra-class imbalances Gated local connection network Attention parallel mechanism Focal loss |
| url | http://www.jxcd.net.cn/thesisDetails?columnId=75892667&Fpath=home&index=0 |
| work_keys_str_mv | AT tianjuan adaptivediagnosismethodbasedongearboxunbalancedfaultdata AT xiegang adaptivediagnosismethodbasedongearboxunbalancedfaultdata AT zhangshun adaptivediagnosismethodbasedongearboxunbalancedfaultdata AT wangyufei adaptivediagnosismethodbasedongearboxunbalancedfaultdata |