特黄三级爱爱视频|国产1区2区强奸|舌L子伦熟妇aV|日韩美腿激情一区|6月丁香综合久久|一级毛片免费试看|在线黄色电影免费|国产主播自拍一区|99精品热爱视频|亚洲黄色先锋一区

基于聲信號(hào)的VMD結(jié)合PSO-SVM車輪磨耗識(shí)別方法研究

  • 打印
  • 收藏
收藏成功


打開文本圖片集

中圖分類號(hào):U279.2 文獻(xiàn)標(biāo)志碼:A doi:10.3969/j.issn.1006-0316.2025.06.005

文章編號(hào):1006-0316(2025)06-0031-09

Wheel Wear Recognition Method Combined VMD and PSO-SVM Based on Sound Signals

FENG Qianqian1,LIU Xingqi1,LI Pengzhen1,XU Hairong1,HAN Chungang1 SHI Zouliangl,LIU Yunhang2

(1. China Railway Urumqi Group Co.,Ltd., Urumqi 830000, China; 2.State Key Laboratory of Rail n021 Chin.

Abstract : On-line monitoring and identification of wheel polygon wear is one of the important problems to be solved in high-speed train operation and maintenance.A novel wheel wear identification method combined variational empirical mode decomposition (VMD) and particle swarm optimization support vector machine (PSO-SVM) based onsound signals is proposed in this paper.Firstly,the staticwheel polygon wear level is tested and the in-vehicle noisedataofhigh-speedtrain is collected.Secondly,the datarules ofinterior noise and wheel polygon wear amplitude are analyzed,and the relationship between interior noise and whel polygon is mapped.Thirdly, the PSO algorithm is applied to search the optimal decomposition parameters of VMD,and the redundant noise frequency band is filtered by band pass filtering. Then the time domain and frequency domain feature indexes are extracted.Finaly,thePSO algorithm is used to optimize the optimal model parameter combination of SVM,and the signal decomposition capability of VMD algorithm is effectively combined with the recognition capability of support vector machine.The experimental verification resultsshowed that the proposed wheel wear identification method could efectively identify the maximum wear amplitude of bogie wheels according to the noise signal inside the vehicle.The study provides guidance and help for wheel rotation and repair of high speed train.

Key words ∵ wheel polygon wear i support vector machine ; particle swarm optimization algorithm ; variational empirical mode decomposition

由于與軌道之間的相互作用,列車車輪在運(yùn)行中會(huì)產(chǎn)生周向非均勻磨耗,進(jìn)而導(dǎo)致出現(xiàn)車輪多邊形磨損問題[1-2]。(剩余7827字)

monitor