空军工程大学学报（自然科学版）2013，Vol.14Issue(4)：9-13,5.DOI:10.3969/j.issn.1009-3516.2013.04.003
基于随机共振的振动故障特征提取及可分性分析
Vibration Fault Feature Extraction Based on Stochastic Resonance and Its Separability Research
摘要
Abstract
In order to improve the accuracy of fault feature extraction,the stochastic resonance (SR) method is proposed in the pretreatment of vibration signals,then the fault feature is extracted based on the method.First,the de-noising principle of SR is presented,and the mutable scale SR,which is suitable for large parameter signal,is analyzed.Then a fast optimization method of frequency compression ratio R is put forward.The vibration fault feature sets based on time domain,frequency domain,time-frequency domain are extracted respectively to test the proposed feature extraction method.Finally,the discrete degree index based on between-class and within-class is applied to analyze the classification performance of feature set.The analysis result shows that the classification indexes of the feature sets extracted from SR output signal are obviously superior to those from the original signal,the feature extraction accuracy is improved notably.关键词
故障特征提取/随机共振/预处理/可分性分析Key words
feature extraction/stochastic resonance/pretreatment/separability research分类
航空航天引用本文复制引用
任立通,张建新,谢寿生,王磊,苗卓广,胡金海..基于随机共振的振动故障特征提取及可分性分析[J].空军工程大学学报（自然科学版）,2013,14(4):9-13,5.基金项目
国家自然科学基金资助项目(51105374) （51105374）
