基于多传感特征信息融合的采煤机截齿失效诊断

摘要/Abstract

摘要： 针对采煤机截割头截割过程中截齿失效状态不易在线识别的难题，提出了一种基于多传感特征信息融合的采煤机截齿失效诊断方法。通过测试采煤机不同磨损程度状态的截齿在截割过程中的振动信号以及声发射信号，建立截齿损耗和失效的信号特征数据库，采用基于最小模糊隶属度优化模型的多传感信息融合方法诊断采煤机截齿的磨损及失效状态。实验结果表明诊断结果的准确率可达95%以上，证明采用此方法可实现对采煤机截齿磨损程度及失效状态的实时精确诊断。研究结果对及时发现和更换失效截齿、提高采煤机截割头的工作效率和使用寿命具有重要意义。

关键词: 采煤机, 截齿失效, 声发射, 信息融合, 模糊隶属度

Abstract: For the problems that the picks failure states for a shearer's cutting head were not easy to identify in the cutting processes, a method was proposed based on multi sensor feature information fusion. By testing the vibration signals and acoustic emission signals of the picks in different abrasion degrees of a shearer, the signal feature databases of the picks' abrasion and failure were established by using the method of multi sensor feature information fusion of minimum fuzzy membership optimization model to diagnose shearer picks abrasion and failure states. The experimental results show that the accuracy rate of the diagnosis results of picks is more than 95%, which indicates that the method can realize the accurate diagnosis to the states of the shearer's picks .The research results make a great contribution to discover and replace the failure picks, and to improve the service life and work efficiency of the shearer cutting head.

Key words: shearer, pick failure, acoustic emission, information fusion, fuzzy membership

中图分类号:

TP273

张强, 王海舰 , 李立莹, 闻学震, 阮越宣, . 基于多传感特征信息融合的采煤机截齿失效诊断[J]. 中国机械工程.

Zhang Qiang, Wang Haijian, Li Liying , Wen Xuezhen , Nguyen Viet Tuyen, . Failure Diagnosis of Shearer Picks Based on Information Fusion from Multi Sensors[J]. China Mechanical Engineering.

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