Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear Fault
The support vector machine（SVM） can avoid the overlearning phenomenon in the case of small training samples,so that the generalization ability can be maximized. The problem that the SVM parameters cannot be selected adaptively is studied. By using the global search characteristic of the genetic algo...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2018-01-01
|
| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.01.034 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841547410353946624 |
|---|---|
| author | Yu Yang Bai Rui Yang Ping |
| author_facet | Yu Yang Bai Rui Yang Ping |
| author_sort | Yu Yang |
| collection | DOAJ |
| description | The support vector machine（SVM） can avoid the overlearning phenomenon in the case of small training samples,so that the generalization ability can be maximized. The problem that the SVM parameters cannot be selected adaptively is studied. By using the global search characteristic of the genetic algorithm,the parameters of the support vector machine are optimized and the optimal parameters of the support vector machine are obtained. This method is used to study the acoustic emission detection of gear fault,and the experimental system is composed of PCI-2 acoustic emission system and rotary machinery vibration fault simulation test bed. The accuracy of gear fault classification is 10% higher than that before optimization,which is very important for gear fault diagnosis. |
| format | Article |
| id | doaj-art-518e10519b9c4bbb969124f6b9060d92 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2018-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-518e10519b9c4bbb969124f6b9060d922025-01-10T14:43:49ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392018-01-014216316629934194Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear FaultYu YangBai RuiYang PingThe support vector machine（SVM） can avoid the overlearning phenomenon in the case of small training samples,so that the generalization ability can be maximized. The problem that the SVM parameters cannot be selected adaptively is studied. By using the global search characteristic of the genetic algorithm,the parameters of the support vector machine are optimized and the optimal parameters of the support vector machine are obtained. This method is used to study the acoustic emission detection of gear fault,and the experimental system is composed of PCI-2 acoustic emission system and rotary machinery vibration fault simulation test bed. The accuracy of gear fault classification is 10% higher than that before optimization,which is very important for gear fault diagnosis.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.01.034Acoustic emissionSupport vector machineGenetic algorithmOptimization kernel function |
| spellingShingle | Yu Yang Bai Rui Yang Ping Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear Fault Jixie chuandong Acoustic emission Support vector machine Genetic algorithm Optimization kernel function |
| title | Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear Fault |
| title_full | Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear Fault |
| title_fullStr | Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear Fault |
| title_full_unstemmed | Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear Fault |
| title_short | Application of the Support Vector Machine based on Genetic Algorithm Optimization on the Acoustic Emission Detection of Gear Fault |
| title_sort | application of the support vector machine based on genetic algorithm optimization on the acoustic emission detection of gear fault |
| topic | Acoustic emission Support vector machine Genetic algorithm Optimization kernel function |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.01.034 |
| work_keys_str_mv | AT yuyang applicationofthesupportvectormachinebasedongeneticalgorithmoptimizationontheacousticemissiondetectionofgearfault AT bairui applicationofthesupportvectormachinebasedongeneticalgorithmoptimizationontheacousticemissiondetectionofgearfault AT yangping applicationofthesupportvectormachinebasedongeneticalgorithmoptimizationontheacousticemissiondetectionofgearfault |