Optimized statistical parameters of acoustic emission signals for monitoring of rolling element bearings

被引：6

作者：

Hemmati, Farzad ^{[1
]}

Alqaradawi, Mohammed ^{[2
]}

Gadala, Mohamed S. ^{[1
]}

机构：

[1] Univ British Columbia, Dept Mech Engn, 2054-6250 Appl Sci Lane, Vancouver, BC V6T 1Z4, Canada

[2] Qatar Univ, Dept Mech Engn, Doha, Qatar

来源：

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART J-JOURNAL OF ENGINEERING TRIBOLOGY | 2016年 / 230卷 / 08期

关键词：

Design of experiment; acoustic emission; statistical analysis; bearing condition monitoring; VIBRATION ANALYSIS; DEFECT;

D O I：

10.1177/1350650115619611

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Acoustic emission (AE) signal generated from artificial defects in rolling element bearings are investigated using experimental measurements in this paper. Rolling element bearings are crucial parts of many machines and there has been an increasing demand to find effective and reliable health monitoring technique and advanced signal processing to detect and diagnose the size and location of incipient defects. Condition monitoring of rolling element bearings, comprises four main stages which are, statistical analysis, faults diagnostics, defect size calculation, and prognostics. In this paper, the effect of defect size, operating speed, and loading conditions on statistical parameters of AE signals, using design of experiment method, have been investigated to select the most sensitive parameters for diagnosing incipient faults and defect growth on rolling element bearings.

引用

页码：897 / 906

页数：10

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