Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search Clustering
Intelligent fault diagnosis technology of the rotating machinery is an important way to guarantee the safety of industrial production. To enhance the accuracy of autonomous diagnosis using unlabelled mechanical faults data, a novel intelligent diagnosis algorithm has been developed for rotating mach...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/9936080 |
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| _version_ | 1832554041652019200 |
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| author | Meng Li Yanxue Wang Chuyuan Wei |
| author_facet | Meng Li Yanxue Wang Chuyuan Wei |
| author_sort | Meng Li |
| collection | DOAJ |
| description | Intelligent fault diagnosis technology of the rotating machinery is an important way to guarantee the safety of industrial production. To enhance the accuracy of autonomous diagnosis using unlabelled mechanical faults data, a novel intelligent diagnosis algorithm has been developed for rotating machinery based on adaptive transfer density peak search clustering. Combined with the wavelet packet energy feature extraction algorithm, the proposed algorithm can enhance the computational accuracy and reduce the computational time consumption. The proposed adaptive transfer density peak search clustering algorithm can adaptively adjust the classification parameters and mark the categories of unlabelled experimental data. Results of bearing experimental analysis demonstrated that the proposed technique is suitable for machinery fault diagnosis using unlabelled data, compared with other traditional algorithms. |
| format | Article |
| id | doaj-art-c841d266886846cfb0b9d381f222a0b2 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-c841d266886846cfb0b9d381f222a0b22025-02-03T05:52:30ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/99360809936080Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search ClusteringMeng Li0Yanxue Wang1Chuyuan Wei2School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaIntelligent fault diagnosis technology of the rotating machinery is an important way to guarantee the safety of industrial production. To enhance the accuracy of autonomous diagnosis using unlabelled mechanical faults data, a novel intelligent diagnosis algorithm has been developed for rotating machinery based on adaptive transfer density peak search clustering. Combined with the wavelet packet energy feature extraction algorithm, the proposed algorithm can enhance the computational accuracy and reduce the computational time consumption. The proposed adaptive transfer density peak search clustering algorithm can adaptively adjust the classification parameters and mark the categories of unlabelled experimental data. Results of bearing experimental analysis demonstrated that the proposed technique is suitable for machinery fault diagnosis using unlabelled data, compared with other traditional algorithms.http://dx.doi.org/10.1155/2021/9936080 |
| spellingShingle | Meng Li Yanxue Wang Chuyuan Wei Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search Clustering Shock and Vibration |
| title | Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search Clustering |
| title_full | Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search Clustering |
| title_fullStr | Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search Clustering |
| title_full_unstemmed | Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search Clustering |
| title_short | Intelligent Fault Diagnosis of Machines Based on Adaptive Transfer Density Peaks Search Clustering |
| title_sort | intelligent fault diagnosis of machines based on adaptive transfer density peaks search clustering |
| url | http://dx.doi.org/10.1155/2021/9936080 |
| work_keys_str_mv | AT mengli intelligentfaultdiagnosisofmachinesbasedonadaptivetransferdensitypeakssearchclustering AT yanxuewang intelligentfaultdiagnosisofmachinesbasedonadaptivetransferdensitypeakssearchclustering AT chuyuanwei intelligentfaultdiagnosisofmachinesbasedonadaptivetransferdensitypeakssearchclustering |