Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF
Playing an important role in electromechanical systems, hydraulic servo system is crucial to mechanical systems like engineering machinery, metallurgical machinery, ships, and other equipment. Fault diagnosis based on monitoring and sensory signals plays an important role in avoiding catastrophic ac...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/8740989 |
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| author | Yu Ding Fei Wang Zhen-ya Wang Wen-jin Zhang |
| author_facet | Yu Ding Fei Wang Zhen-ya Wang Wen-jin Zhang |
| author_sort | Yu Ding |
| collection | DOAJ |
| description | Playing an important role in electromechanical systems, hydraulic servo system is crucial to mechanical systems like engineering machinery, metallurgical machinery, ships, and other equipment. Fault diagnosis based on monitoring and sensory signals plays an important role in avoiding catastrophic accidents and enormous economic losses. This study presents a fault diagnosis scheme for hydraulic servo system using compressed random subspace based ReliefF (CRSR) method. From the point of view of feature selection, the scheme utilizes CRSR method to determine the most stable feature combination that contains the most adequate information simultaneously. Based on the feature selection structure of ReliefF, CRSR employs feature integration rules in the compressed domain. Meanwhile, CRSR substitutes information entropy and fuzzy membership for traditional distance measurement index. The proposed CRSR method is able to enhance the robustness of the feature information against interference while selecting the feature combination with balanced information expressing ability. To demonstrate the effectiveness of the proposed CRSR method, a hydraulic servo system joint simulation model is constructed by HyPneu and Simulink, and three fault modes are injected to generate the validation data. |
| format | Article |
| id | doaj-art-8cc8e315294f463f80b17d6418a33d11 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-8cc8e315294f463f80b17d6418a33d112025-08-20T02:09:35ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/87409898740989Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefFYu Ding0Fei Wang1Zhen-ya Wang2Wen-jin Zhang3School of Reliability and Systems Engineering, Beihang University, Beijing, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing, ChinaResearch and Development Center, China Academy of Launch Vehicle Technology, Beijing, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing, ChinaPlaying an important role in electromechanical systems, hydraulic servo system is crucial to mechanical systems like engineering machinery, metallurgical machinery, ships, and other equipment. Fault diagnosis based on monitoring and sensory signals plays an important role in avoiding catastrophic accidents and enormous economic losses. This study presents a fault diagnosis scheme for hydraulic servo system using compressed random subspace based ReliefF (CRSR) method. From the point of view of feature selection, the scheme utilizes CRSR method to determine the most stable feature combination that contains the most adequate information simultaneously. Based on the feature selection structure of ReliefF, CRSR employs feature integration rules in the compressed domain. Meanwhile, CRSR substitutes information entropy and fuzzy membership for traditional distance measurement index. The proposed CRSR method is able to enhance the robustness of the feature information against interference while selecting the feature combination with balanced information expressing ability. To demonstrate the effectiveness of the proposed CRSR method, a hydraulic servo system joint simulation model is constructed by HyPneu and Simulink, and three fault modes are injected to generate the validation data.http://dx.doi.org/10.1155/2018/8740989 |
| spellingShingle | Yu Ding Fei Wang Zhen-ya Wang Wen-jin Zhang Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF Complexity |
| title | Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF |
| title_full | Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF |
| title_fullStr | Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF |
| title_full_unstemmed | Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF |
| title_short | Fault Diagnosis for Hydraulic Servo System Using Compressed Random Subspace Based ReliefF |
| title_sort | fault diagnosis for hydraulic servo system using compressed random subspace based relieff |
| url | http://dx.doi.org/10.1155/2018/8740989 |
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