摘要
提出了采用线性预测倒谱系数(linear predictive cepstrum coefficient,简称LPCC)监测刀具磨损的方法。使用LPCC作为可听阈内铣削声信号的声谱特征参数,对LPCC进行统计处理,计算LPCC分量的F比,分析LPCC分量与切削时间的关系,寻找LPCC与刀具磨损之间的规律。研究结果表明,铣削声信号的LPCC相关分量加权和可以有效地反映铣刀的磨损变化规律。
A new tool-wear monitoring method is presented by using the linear predictive cepstrum coefficient（LPCC）.Firstly,audible milling sound is characterized by LPCC.In order to discover the law between LPCC and tool wear,statistics are collected including calculation of the F ratio of LPCC components,analysis of the relationship between the relative components of LPCC and cutting time.The results indicate that the weighted sum of the relative LPCC components extracted from audible milling sound can effectively reflect the tool wear.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2010年第3期264-268,共5页
Journal of Vibration,Measurement & Diagnosis
基金
山东省重点学科基金资助项目(编号:XTD0713)
教育部科学技术研究重点资助项目(编号:206088)
