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Alternative TitleResearch on acoustic emission source localization based on improved multi-output SVM
朱军; 史勃; 张环宇; 荣胜波; 黄益泽
Source Publication传感器与微系统
Volume37Issue:2Pages:64-66, 71
Indexed ByCSCD
Contribution Rank1
Funding Organization沈阳市科技局科技重大攻关(创新专项)基金资助项目(F15-007-2-00)
Keyword声发射 核主成分分析 多输出支持向量机 参数优化
Other AbstractIn order to improve precision of predicting position of coal and gas outburst based on acoustic emission ( AE) phenomena, combined with kernel principal component analysis( KPCA) ,a target positioning method based on improved multi-output least squares ( LS) support vector machine ( SVM) ,KPCA-LSSVM, is proposed. For collected acoustic emission parameter signals,KPCA is used to extract important localization features. Multi-output least squares support vector machine is used to establish positioning model. Memetic algorithm is used to optimize the parameters of the multi-output LSSVM. Simulation experiment is used to test positioning performance. The results show that the algorithm improves precision of acoustic emission localization of test platform and positioning time is less than other positioning algorithms, it has high practical application value.
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Document Type期刊论文
Corresponding Author朱军
Recommended Citation
GB/T 7714
朱军,史勃,张环宇,等. 基于改进多输出支持向量机的声发射源定位研究[J]. 传感器与微系统,2018,37(2):64-66, 71.
APA 朱军,史勃,张环宇,荣胜波,&黄益泽.(2018).基于改进多输出支持向量机的声发射源定位研究.传感器与微系统,37(2),64-66, 71.
MLA 朱军,et al."基于改进多输出支持向量机的声发射源定位研究".传感器与微系统 37.2(2018):64-66, 71.
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