ADAPTIVE FILTERING OF SOUND PRESSURE SIGNALS FOR MONITORING MACHINERY IN NOISY ENVIRONMENTS

被引：9

作者：

CARNEY, MS

MANN, JA

GAGLIARDI, J

机构：

[1] Department of Aerospace Engineering and Engineering Mechanics, Iowa State University, Ames, IA 50011-2162

[2] US Bureau of Mines, Minneapolis

来源：

APPLIED ACOUSTICS | 1994年 / 43卷 / 04期

关键词：

D O I：

10.1016/0003-682X(94)90032-9

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

An experimental evaluation of the ability of sound pressure microphones to diagnose different machinery conditions in noisy environments was performed. An adaptive filtering (ANC) routine was incorporated to reduce the noise. The detection process utilized frequency spectra of the data, along with cepstrum and kurtosis methods of analysis. Two different machine components were monitored: ball bearings in a ball bearings test stand and milling bits in a milling machine. The effect of the placement of the microphones on the ANC routine to reduce the background noise in the signal was investigated and found to influence the results. The results show that the sound pressure microphones could not reliably diagnose ball bearing condition but could diagnose the milling machine bit condition.

引用

页码：333 / 351

页数：19

共 14 条

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