欠定盲解卷积用于滚动轴承复合故障声学诊断  

Undertermined Blind Deconvolution in Bearing Combined Failure Detection Acoustical Diagnosis

作　　者：潘楠[1] 伍星[1] 迟毅林[1] 柳小勤[1] 刘畅[1] 

机构地区：[1]昆明理工大学机电工程学院,昆明650093

出　　处：《振动．测试与诊断》2013年第2期284-289,341-342,共6页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(50805071);云南省教育厅科学研究基金资助项目(2010Y380)

摘　　要：针对旋转机械复杂声场中强噪声干扰及故障源未知等难题,提出一种基于盲解卷积的声学诊断方法。该方法采用包络谱余弦测度作为独立分量间距离测度,结合冲击信号峭度指标优选独立分量,进而通过频域稀疏分量分析对估计信号做进一步的分离,最终实现在欠定条件下对滚动轴承复合故障信号的可靠提取。实际声场环境中的滚动轴承复合故障声信号提取试验验证了该方法的有效性。In order to deal with problems of noisy source mixing and unknown number failure sources in complex sound field of rotating machines,an acoustic fault detection method based on blind deconvolution is proposed.The Cosine measure of spectral envelope is employed as distance measure between independent components(ICAs),impulse signal's kurtosis value is applied to optimal selecting the ICAs.Combining with frequency-domain sparse component analysis(FD-SCA),the combined failure signals of rolling bearing are extracted perfectly when the number of observations is less than the number of source signal.Acoustical transient impulse signal extraction of combined failure bearing in real-world situation shows the validity of the proposed method.

关 键 词：欠定盲解卷积 频域稀疏分量分析 复合故障 声学诊断 

分 类 号：TP165.3[自动化与计算机技术—控制理论与控制工程] TP206.3[自动化与计算机技术—控制科学与工程]