基于声发射信号的砂轮钝化在线检测方法  

Acoustic Emission Signals Based On-line Monitoring Method for Wheel Dull

作　　者：刘贵杰[1] 唐婷[1] 刘立静[1] 巩亚东[2] 王宛山[2] 

机构地区：[1]中国海洋大学工程学院,青岛266071 [2]东北大学机械工程学院,沈阳110004

出　　处：《仪器仪表学报》2005年第z1期13-14,共2页Chinese Journal of Scientific Instrument

基　　金：山东省优秀中青年科学家奖励基金(2004BS05012);教育部科学技术研究重点项目(200032)资助项目

摘　　要：提出了一种基于声发射信号的砂轮钝化在线检测方法,该方法利用BP神经网络建立磨削声发射(AE)信号幅值变化特征量与砂轮钝化状况之间的非线性关系模型,并利用实验数据对该模型进行训练测试,训练获得的模型可用于在线检测小批量、多品种磨削条件下砂轮的钝化状况。实验结果表明,该方法能够准确地在线检测砂轮的钝化程度,具有很高的实用价值。An acoustic emission signals based on-line monitoring method for grinding wheel dull is presented.BP neural network is used to build the nun-linear relation between the RMS value of acoustic emission signals produced in grinding process and the state of grinding wheel dull,and the neural network model is trained with grinding test data.The trained model can be used to on-line monitor the grinding wheel state under multi-grinding conditions for the little batch and variety of grinding process.Test results indicate that this method can on-line monitoring grinding wheel state accurately,and has very high application worth.

关 键 词：磨削砂轮 钝化状况 在线检测 声发射信号 

分 类 号：TH7-55[机械工程—仪器科学与技术]