Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network
A method based on singular value decomposition (SVD) and fuzzy neural network (FNN) was proposed to extract and diagnose the fault features of diesel engine crankshaft bearings efficiently and accurately. Firstly, vibration signals of crankshaft bearings in known state under the same working conditi...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2018/8218657 |
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| _version_ | 1832549278761877504 |
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| author | Jingbo Gai Yifan Hu |
| author_facet | Jingbo Gai Yifan Hu |
| author_sort | Jingbo Gai |
| collection | DOAJ |
| description | A method based on singular value decomposition (SVD) and fuzzy neural network (FNN) was proposed to extract and diagnose the fault features of diesel engine crankshaft bearings efficiently and accurately. Firstly, vibration signals of crankshaft bearings in known state under the same working condition were decomposed by EMD to obtain the modal components containing fault-feature information. Then, the singular values of modal components which include the main fault features were used as the initial vector matrix, where the eigenvectors were decomposed to form a fault characteristic matrix. At last, the fault features matrix was trained by the fuzzy neural network, in order to realize the diagnosis and identification of the crankshaft bearings in different states in the form of numerical values. The experiment showed that the numerical identification of the fuzzy neural network based on the singular value had high fault diagnosis accuracy and stability. This method can also reflect the gradual change of the crankshaft bearings’ fault to some extent, so it has the desired reliability and value. |
| format | Article |
| id | doaj-art-fceba0b06d334abd9aa82f2e92c942d1 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-fceba0b06d334abd9aa82f2e92c942d12025-02-03T06:11:46ZengWileyShock and Vibration1070-96221875-92032018-01-01201810.1155/2018/82186578218657Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural NetworkJingbo Gai0Yifan Hu1College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin, Heilongjiang 150001, ChinaCollege of Aerospace and Civil Engineering, Harbin Engineering University, Harbin, Heilongjiang 150001, ChinaA method based on singular value decomposition (SVD) and fuzzy neural network (FNN) was proposed to extract and diagnose the fault features of diesel engine crankshaft bearings efficiently and accurately. Firstly, vibration signals of crankshaft bearings in known state under the same working condition were decomposed by EMD to obtain the modal components containing fault-feature information. Then, the singular values of modal components which include the main fault features were used as the initial vector matrix, where the eigenvectors were decomposed to form a fault characteristic matrix. At last, the fault features matrix was trained by the fuzzy neural network, in order to realize the diagnosis and identification of the crankshaft bearings in different states in the form of numerical values. The experiment showed that the numerical identification of the fuzzy neural network based on the singular value had high fault diagnosis accuracy and stability. This method can also reflect the gradual change of the crankshaft bearings’ fault to some extent, so it has the desired reliability and value.http://dx.doi.org/10.1155/2018/8218657 |
| spellingShingle | Jingbo Gai Yifan Hu Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network Shock and Vibration |
| title | Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network |
| title_full | Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network |
| title_fullStr | Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network |
| title_full_unstemmed | Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network |
| title_short | Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network |
| title_sort | research on fault diagnosis based on singular value decomposition and fuzzy neural network |
| url | http://dx.doi.org/10.1155/2018/8218657 |
| work_keys_str_mv | AT jingbogai researchonfaultdiagnosisbasedonsingularvaluedecompositionandfuzzyneuralnetwork AT yifanhu researchonfaultdiagnosisbasedonsingularvaluedecompositionandfuzzyneuralnetwork |