FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT)
Aiming at the problem that the vibration signal in diesel engine fault diagnosis is non-stationary and nonlinear, and the original signal is directly input into the Convolutional Neural Network（CNN） for fault diagnosis with poor effect, a new method based on PCA-EDT-CNN is proposed. Firstly, use Pri...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Strength
2022-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.06.01 |
| _version_ | 1797767620571693056 |
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| author | BAI YunJie JIA XiSheng LIANG QingHai MA YunFei WEN Liang |
| author_facet | BAI YunJie JIA XiSheng LIANG QingHai MA YunFei WEN Liang |
| author_sort | BAI YunJie |
| collection | DOAJ |
| description | Aiming at the problem that the vibration signal in diesel engine fault diagnosis is non-stationary and nonlinear, and the original signal is directly input into the Convolutional Neural Network（CNN） for fault diagnosis with poor effect, a new method based on PCA-EDT-CNN is proposed. Firstly, use Principal Component Analysis（PCA） to adaptively reduce the original data collected by the sensor, and construct a qualified Principal Component Eigenvector Matrix（PCEM）; secondly, perform Euclidean Distance Transformation（EDT） on PCEM, calculate the Euclidean distance between each row and construct the Euclidean Distance Matrix（EDM）; finally, flatten PCEM and EDM into one-dimensional vectors and synthesize a one-dimensional sample sequence, input into One-Dimensional Convolutional Neural Network（1 DCNN） to train and diagnosis the model. A diesel engine preset failure test bench was built to verify the effectiveness of the method, and through comparison with traditional methods, the results show that the method has high accuracy in diagnosing different fault states of diesel engines and has practical engineering application value. |
| first_indexed | 2024-03-12T20:42:28Z |
| format | Article |
| id | doaj.art-b2ff2db647144f43b8e4957bd76e51d6 |
| institution | Directory Open Access Journal |
| issn | 1001-9669 |
| language | zho |
| last_indexed | 2024-03-12T20:42:28Z |
| publishDate | 2022-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj.art-b2ff2db647144f43b8e4957bd76e51d62023-08-01T07:54:50ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692022-01-011271127836350066FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT)BAI YunJieJIA XiShengLIANG QingHaiMA YunFeiWEN LiangAiming at the problem that the vibration signal in diesel engine fault diagnosis is non-stationary and nonlinear, and the original signal is directly input into the Convolutional Neural Network（CNN） for fault diagnosis with poor effect, a new method based on PCA-EDT-CNN is proposed. Firstly, use Principal Component Analysis（PCA） to adaptively reduce the original data collected by the sensor, and construct a qualified Principal Component Eigenvector Matrix（PCEM）; secondly, perform Euclidean Distance Transformation（EDT） on PCEM, calculate the Euclidean distance between each row and construct the Euclidean Distance Matrix（EDM）; finally, flatten PCEM and EDM into one-dimensional vectors and synthesize a one-dimensional sample sequence, input into One-Dimensional Convolutional Neural Network（1 DCNN） to train and diagnosis the model. A diesel engine preset failure test bench was built to verify the effectiveness of the method, and through comparison with traditional methods, the results show that the method has high accuracy in diagnosing different fault states of diesel engines and has practical engineering application value.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.06.011DCNN;PCA;EDT;Diesel engine;Fault diagnosis |
| spellingShingle | BAI YunJie JIA XiSheng LIANG QingHai MA YunFei WEN Liang FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT) Jixie qiangdu 1DCNN;PCA;EDT;Diesel engine;Fault diagnosis |
| title | FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT) |
| title_full | FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT) |
| title_fullStr | FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT) |
| title_full_unstemmed | FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT) |
| title_short | FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT) |
| title_sort | fault diagnosis method of diesel engine based on pca edt cnn mt |
| topic | 1DCNN;PCA;EDT;Diesel engine;Fault diagnosis |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.06.01 |
| work_keys_str_mv | AT baiyunjie faultdiagnosismethodofdieselenginebasedonpcaedtcnnmt AT jiaxisheng faultdiagnosismethodofdieselenginebasedonpcaedtcnnmt AT liangqinghai faultdiagnosismethodofdieselenginebasedonpcaedtcnnmt AT mayunfei faultdiagnosismethodofdieselenginebasedonpcaedtcnnmt AT wenliang faultdiagnosismethodofdieselenginebasedonpcaedtcnnmt |