基于模糊数据融合的刀具磨损状态辩识  

Cutting Tool Wear State Identification Based on Fuzzy Data Fusion

作　　者：陈希[1] 张兴元[1] 

机构地区：[1]辽宁工程技术大学机械工程学院,辽宁阜新123000

出　　处：《计算机测量与控制》2010年第11期2593-2595,2611,共4页Computer Measurement &Control

摘　　要：选取能够充分反映刀具磨损状态的振动信号和功率信号作为研究对象,采用正交小波变换技术,提取刀具磨损特征信号,利用该特征信号建立了振动幅值变化与刀具磨损量间的关系,计算出基于振动信号的刀具状态特征值,定性地识别出刀具磨损状态;对功率信号,采用统计分析方法,通过均方根处理提取出刀具磨损特征信号,并以信号强度的变化来表征刀具的磨损情况;为了避免单一特征信号提供刀具状态信息的局限性,采用模糊数据融合方法对振动、功率特征信号进行融合,获得更加全面、准确的刀具磨损状态;实验结果表明,基于模糊数据融合的刀具磨损状态识别比单一传感器系统对刀具磨损状态识别更为可靠。Vibration signal and power signal,which can be used to identify the cutting tool＇s wear state,are selected to study on.It adopts the orthogonal wavelet to abstract characteristic signal of cutting tool＇s wear which was used to establish relation between cutting tool wear amount and vibration amplitude.The cutter state characteristic value based on relation curve is counted,and the cutting tool wear state was identified.Be aimed at power signal,it adopts statistic analysis which abstracts cutting tool wear characteristic signal through root-mean-square,attributing cutting tool wear condition through signal intensity alteration.In order to avoid limitation that single characteristic signal supplies cutting tool condition information,it adopts fuzzy data fusion method to fusion vibration and power characteristic signal so that achieves cut condition accurately.The experiment indicated,compared with the single signal identifying method,the cutting tool wear state identification based on fuzzy data fusion can identify cutting tool wear state credibility.

关 键 词：刀具磨损 小波分析 振动信号 功率信号 模糊数据融合 

分 类 号：V240.2[航空宇航科学与技术—飞行器设计]