摘要
刀具状态监测的目的是为了开发出实用的刀具状态监测设备。为了降低设备成本和提高监测的准确率,提取监测信号中最能反映刀具状态的特征是至关重要的。对近些年来在学术期刊上公开发表的关于刀具磨损在线监测研究中所采用的信号特征提取方法作简要的回顾与归纳,并得出如下结论:信号的特征提取算法有很多种,不同的信号对应不同的特征提取方法,即使是同一信号也可以用不同的特征提取方法描述它们在不同域内的特征;只有将不同的信号及不同的特征提取方法结合起来,才能实现成本低、可靠性高、安装方便的刀具监测系统。
The aim of the cutting tool condition monitoring is to develop the practical cutting tool condition monitoring facilities.In order to reduce the facility cost and improve the accuracy of monitoring,it＇s important to extract the feature that can respond to the cutting tool condition.A summary of the signal feature extraction methods for tool wear and failure monitoring in metal cutting that have been tested and reported in the literature was presented.The conclusions are that there are many signal feature extraction algorithm,different signals correspond to different feature extraction method,the identical signal can also use the different feature extraction methods to describe their characteristics in different regions.Only combining the different signals with different feature extraction methods can realize tool monitoring systems with low-cost,high reliability and easy installation.
出处
《机床与液压》
北大核心
2010年第17期121-125,共5页
Machine Tool & Hydraulics
关键词
刀具状态监测系统
特征提取
时域分析
频域分析
时-频域分析
Tool condition monitoring system
Feature extraction
Time-domain analysis
Frequency-domain analysis
Time-frequency domain analysis
