摘要
设计用振动信号来监控加工过程 .提出了一种基于小波包变换的颤振特征提取方法 ,通过所提取的特征小波包来反映加工过程中的颤振信息 .在此基础上 ,基于主成份分析方法对特征小波包进行重构 ,由主成份得分 (累积贡献率 )来评价重构特征 ,并实现了重构特征自动提取 .更进一步给出了重构特征总体的统一构造形式 ,并基于欧氏距离法 ,建立了颤振的诊断模型 .通过对铣削加工试验中的颤振识别 ,验证了文中提出的方法的可行性 .
Based on wavelet packets transform, a new method was proposed for feature extraction of chatter in milling process by using vibration signal. These packets contain major chatter information of the original signal. Using the principal composition analysis method, a feature was reconstructed from these packets, and a principal composition score was proposed to assess the reconstructed feature. The realization of the procedure of automatic feature selection for a given process was studied. A uniform formula of the feature collectivity was given. A diagnosis model of chatter based on Euclidean distance is established. A practical milling process was employed to show that the proposed method is very effective.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2001年第6期758-762,共5页
Journal of Harbin Institute of Technology
基金
国防科工委预研项目
关键词
颤振
小波包
主成份分析
故障诊断
铣削加工
信号特征提取
重构特征
Failure analysis
Feature extraction
Monitoring
Signal processing
Vibrations (mechanical)
Wavelet transforms
