Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《China Mechanical Engineering》 2016-19
Add to Favorite Get Latest Update

Online Monitoring of Shearer's Pick Wear Based on ANFIS Fuzzy Information Fusion

Zhang Qiang;Wang Haijian;Li Liying;Liu Zhiheng;Liaoning Technical University;State Key Laboratory of Structural Analysis for Industrial Equipment,Dalian University of Technology;Sichuan University of Science & Engineering,Material Corrosion and Protection Key Laboratory of Sichuan Province;  
In order to realize the realtime and accurate online monitoring of the wear degree in the cutting processes,the vibration signals,acoustic emission signals and temperature signals of different wear degrees were tested and extracted,and the multi feature sample databases of different wear degrees to the cutting signals were established.The optimal fuzzy membership function for each characteristic signal was calculated by the minimum ambiguity optimization model,and the method of the ANFIS multidimensional fuzzy neural network was adopted to realize the fusion of multi sensor feature informations,then the fusion results of the output confidence and weight were higher.According to the results of the random experiments of the fusion system,the identification degree of the cutting wear monitoring system based on ANFIS fuzzy information fusion is high,and the maximum error of the test results is less than 6.5%,and the results show that the system has good fusion effect and higher test accuracy.
【Fund】: 国家自然科学基金资助项目(51504121);; 高等学校博士学科点专项科研基金资助项目(20132121120011);; 工业装备结构分析重点实验室开放基金资助项目(GZ1402);; 辽宁省高等学校杰出青年学者成长计划资助项目(LJQ2014036);; 辽宁省“百千万人才工程”资助项目(2014921070)
【CateGory Index】: TD421.6
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved