摘要
研究了根据自动机机箱的短时冲击振动信号,从信息的定量描述方法出发,通过小波能谱熵、小波奇异谱熵、小波时间熵算法建立信息熵提取模型,实现故障特征提取。针对典型模拟信号的仿真分析,验证了所提出的信息熵指标可以对信号进行多层次特征提取。结合自动机故障诊断试验,进行自动机运动形态分解时域特征与不同空间信息熵指标特征提取。可用于小口径火炮高速自动机的在线监测与故障诊断。
According to the short-term impact vibration signal of the automatic mechanism case,from the viewpoint of the quantitative description method of information,by means of the wavelet energy entropy,wavelet singular spectrum entropy,wavelet time entropy algorithm,the information entropy model was established to achieve the fault feature extraction.Aimed at the simulation and analysis of the typical analog signals,validation of the proposed information entropy index can be the signal of multi level feature extraction.Combined with fault diagnosis experiment of automatic mechanism,decomposition time domain characteristics of automatic mechanism movement morphology and different spatial information entropy feature extraction were realized.The study results can be used for the online monitoring and fault diagnosis of the high speed automatic mechanism of small caliber gun.
出处
《火炮发射与控制学报》
北大核心
2012年第4期74-78,共5页
Journal of Gun Launch & Control
基金
国家自然科学基金资助项目(51175480)
山西省青年科技研究基金资助项目(2012021014-2)
关键词
自动机
信息熵提取
小波奇异谱熵
小波能谱熵
小波时间熵
automatic mechanism
information entropy extraction
wavelet singular entropy
wavelet energy entropy
wavelet time entropy
