FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK
In order to make accurate diagnosis for the scraper conveyor speed reducer failure study. This paper proposes a improved firefly algorithm to optimize neural network based fault diagnosis method. Firstly, the characteristics of the fault characteristic parameters of the blade conveyor are extracted....
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2019-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.007 |
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| author | MAO Jun GUO Hao CHEN HongYue |
| author_facet | MAO Jun GUO Hao CHEN HongYue |
| author_sort | MAO Jun |
| collection | DOAJ |
| description | In order to make accurate diagnosis for the scraper conveyor speed reducer failure study. This paper proposes a improved firefly algorithm to optimize neural network based fault diagnosis method. Firstly, the characteristics of the fault characteristic parameters of the blade conveyor are extracted. The second application feature data sample for fault diagnosis model based on neural network training. Using the improved firefly algorithm to optimize neural network weights and threshold, to speed up the optimum value of, get the optimal model of the network. Preliminary studies suggest that the improved firefly algorithm combined with BP（back propagation） neural network can effectively solve the neural network slow convergence speed, easily falling into the master problem, can make accurate diagnosis for the failure of scraper conveyor speed reducer. |
| format | Article |
| id | doaj-art-5455e528c41745ff85d72af15e5a9b7d |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-5455e528c41745ff85d72af15e5a9b7d2025-01-15T02:29:59ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-014154455030604943FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORKMAO JunGUO HaoCHEN HongYueIn order to make accurate diagnosis for the scraper conveyor speed reducer failure study. This paper proposes a improved firefly algorithm to optimize neural network based fault diagnosis method. Firstly, the characteristics of the fault characteristic parameters of the blade conveyor are extracted. The second application feature data sample for fault diagnosis model based on neural network training. Using the improved firefly algorithm to optimize neural network weights and threshold, to speed up the optimum value of, get the optimal model of the network. Preliminary studies suggest that the improved firefly algorithm combined with BP（back propagation） neural network can effectively solve the neural network slow convergence speed, easily falling into the master problem, can make accurate diagnosis for the failure of scraper conveyor speed reducer.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.007Improved firefly algorithmBP neural networkFault diagnosisScraper conveyorReducer |
| spellingShingle | MAO Jun GUO Hao CHEN HongYue FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK Jixie qiangdu Improved firefly algorithm BP neural network Fault diagnosis Scraper conveyor Reducer |
| title | FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK |
| title_full | FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK |
| title_fullStr | FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK |
| title_full_unstemmed | FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK |
| title_short | FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK |
| title_sort | fault diagnosis of scraper conveyor reducer based on improved firefly algorithm to optimize neural network |
| topic | Improved firefly algorithm BP neural network Fault diagnosis Scraper conveyor Reducer |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.007 |
| work_keys_str_mv | AT maojun faultdiagnosisofscraperconveyorreducerbasedonimprovedfireflyalgorithmtooptimizeneuralnetwork AT guohao faultdiagnosisofscraperconveyorreducerbasedonimprovedfireflyalgorithmtooptimizeneuralnetwork AT chenhongyue faultdiagnosisofscraperconveyorreducerbasedonimprovedfireflyalgorithmtooptimizeneuralnetwork |