Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox
Aiming at the problems of low fault recognition rate， slow convergence speed and difficult parameter selection in the process of fault diagnosis of planetary gearbox based on BP neural network improved by optimization algorithm， a GA-ACO algorithm is proposed to optimize the parameters of neural net...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2021-03-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.03.025 |
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| author | Chang Gao Zhongqing Yu Qiang Zhou |
| author_facet | Chang Gao Zhongqing Yu Qiang Zhou |
| author_sort | Chang Gao |
| collection | DOAJ |
| description | Aiming at the problems of low fault recognition rate， slow convergence speed and difficult parameter selection in the process of fault diagnosis of planetary gearbox based on BP neural network improved by optimization algorithm， a GA-ACO algorithm is proposed to optimize the parameters of neural network. The basic principle and main steps of GA-ACO-BP algorithm are given. At the same time， this method is applied to the fault diagnosis of planetary gearbox. Comparing the performance of ACO-BP neural network algorithm and GA-ACO-BP algorithm， the results show that the convergence speed of ACO Optimized BP neural network is slow and the recognition accuracy is not high， while GA-ACO-BP algorithm can accurately and quickly diagnose and identify the fault of planetary gearbox. |
| format | Article |
| id | doaj-art-8dfe7e79cbed4cb49d06f048d63c7119 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2021-03-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-8dfe7e79cbed4cb49d06f048d63c71192025-01-10T14:54:02ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392021-03-01451531607493183Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary GearboxChang GaoZhongqing YuQiang ZhouAiming at the problems of low fault recognition rate， slow convergence speed and difficult parameter selection in the process of fault diagnosis of planetary gearbox based on BP neural network improved by optimization algorithm， a GA-ACO algorithm is proposed to optimize the parameters of neural network. The basic principle and main steps of GA-ACO-BP algorithm are given. At the same time， this method is applied to the fault diagnosis of planetary gearbox. Comparing the performance of ACO-BP neural network algorithm and GA-ACO-BP algorithm， the results show that the convergence speed of ACO Optimized BP neural network is slow and the recognition accuracy is not high， while GA-ACO-BP algorithm can accurately and quickly diagnose and identify the fault of planetary gearbox.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.03.025GA-ACO-BP algorithmPlanetary gearboxFault diagnosisGenetic algorithmAnt colony optimization algorithmBP neural network |
| spellingShingle | Chang Gao Zhongqing Yu Qiang Zhou Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox Jixie chuandong GA-ACO-BP algorithm Planetary gearbox Fault diagnosis Genetic algorithm Ant colony optimization algorithm BP neural network |
| title | Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox |
| title_full | Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox |
| title_fullStr | Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox |
| title_full_unstemmed | Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox |
| title_short | Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox |
| title_sort | application of ga aco optimized bp neural network in fault diagnosis of planetary gearbox |
| topic | GA-ACO-BP algorithm Planetary gearbox Fault diagnosis Genetic algorithm Ant colony optimization algorithm BP neural network |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.03.025 |
| work_keys_str_mv | AT changgao applicationofgaacooptimizedbpneuralnetworkinfaultdiagnosisofplanetarygearbox AT zhongqingyu applicationofgaacooptimizedbpneuralnetworkinfaultdiagnosisofplanetarygearbox AT qiangzhou applicationofgaacooptimizedbpneuralnetworkinfaultdiagnosisofplanetarygearbox |