Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric Locomotive
In view of the difficulties and poor efficiency of manual troubleshooting of locomotive faults, this paper proposed a method for correlative analyses of traction converter faults and train level faults. The method is based on a fault diagnosis model that utilizes the expert knowledge of locomotive f...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Control and Information Technology
2020-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
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| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.03.020 |
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| author | GAO Yongqiang |
| author_facet | GAO Yongqiang |
| author_sort | GAO Yongqiang |
| collection | DOAJ |
| description | In view of the difficulties and poor efficiency of manual troubleshooting of locomotive faults, this paper proposed a method for correlative analyses of traction converter faults and train level faults. The method is based on a fault diagnosis model that utilizes the expert knowledge of locomotive fault diagnosis and can realize intelligent diagnosis of locomotive faults. The fault diagnosis expert system of Shenhua electric locomotive traction converter and other subsystems is implemented. Experimental results show that the accuracy of fault diagnosis for the key systems and components of Shenhua electric locomotive can reach 90%, which meets the requirements of intelligent operation and maintenance of railway. |
| format | Article |
| id | doaj-art-8c5c48d2b96c4e7f85b9533d346fd418 |
| institution | Kabale University |
| issn | 2096-5427 |
| language | zho |
| publishDate | 2020-01-01 |
| publisher | Editorial Office of Control and Information Technology |
| record_format | Article |
| series | Kongzhi Yu Xinxi Jishu |
| spelling | doaj-art-8c5c48d2b96c4e7f85b9533d346fd4182025-08-25T06:50:19ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272020-01-01379710282324675Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric LocomotiveGAO YongqiangIn view of the difficulties and poor efficiency of manual troubleshooting of locomotive faults, this paper proposed a method for correlative analyses of traction converter faults and train level faults. The method is based on a fault diagnosis model that utilizes the expert knowledge of locomotive fault diagnosis and can realize intelligent diagnosis of locomotive faults. The fault diagnosis expert system of Shenhua electric locomotive traction converter and other subsystems is implemented. Experimental results show that the accuracy of fault diagnosis for the key systems and components of Shenhua electric locomotive can reach 90%, which meets the requirements of intelligent operation and maintenance of railway.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.03.020real-time monitoringdata transmissiondata collectionfault diagnosiscorrelation analysistraction converter |
| spellingShingle | GAO Yongqiang Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric Locomotive Kongzhi Yu Xinxi Jishu real-time monitoring data transmission data collection fault diagnosis correlation analysis traction converter |
| title | Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric Locomotive |
| title_full | Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric Locomotive |
| title_fullStr | Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric Locomotive |
| title_full_unstemmed | Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric Locomotive |
| title_short | Fault Diagnosis Expert System for Critical Systems and Components of “Shenhua” Electric Locomotive |
| title_sort | fault diagnosis expert system for critical systems and components of shenhua electric locomotive |
| topic | real-time monitoring data transmission data collection fault diagnosis correlation analysis traction converter |
| url | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.03.020 |
| work_keys_str_mv | AT gaoyongqiang faultdiagnosisexpertsystemforcriticalsystemsandcomponentsofshenhuaelectriclocomotive |