Acoustic emission-based condition monitoring methods: Review and application for low speed slew bearing

被引:131
|
作者
Caesarendra, Wahyu [1 ,2 ]
Kosasih, Buyung [1 ]
Tieu, Anh Kiet [1 ]
Zhu, Hongtao [1 ]
Moodie, Craig A. S. [1 ]
Zhu, Qiang [1 ]
机构
[1] Univ Wollongong, Sch Mech Mat & Mechatron Engn Univ, Wollongong, NSW 2522, Australia
[2] Diponegoro Univ, Dept Mech Engn, Tembalang 50275, Semarang, Indonesia
关键词
Acoustic emission; Condition monitoring; Feature extraction; Largest Lyapunov exponent (LLE) algorithm; Low speed slew bearing; ROLLING ELEMENT BEARINGS; FEATURE-EXTRACTION; FAULT-DIAGNOSIS; APPROXIMATE ENTROPY; SPECTRAL KURTOSIS; DEFECT; VIBRATION; SIGNALS; CAPACITY; DECOMPOSITION;
D O I
10.1016/j.ymssp.2015.10.020
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper presents an acoustic emission-based method for the condition monitoring of low speed reversible slew bearings. Several acoustic emission (AE) hit parameters as the monitoring parameters for the detection of impending failure of slew bearings are reviewed first. The review focuses on: (1) the application of AE in typical rolling element bearings running at different speed classifications, i.e. high speed (>600 rpm), low speed (10-600 rpm) and very low speed (<10 rpm); (2) the commonly used AE hit parameters in rolling element bearings and (3) AE signal processing, feature extraction and pattern recognition methods. In the experiment, impending failure of the slew bearing was detected by the AE hit parameters after the new bearing had run continuously for approximately 15 months. The slew bearing was then dismantled and the evidence of the early defect was analysed. Based on the result, we propose a feature extraction method of the AE waveform signal using the largest Lyapunov exponent (LLE) algorithm and demonstrate that the LLE feature can detect the sign of failure earlier than the AE hit parameters with improved prediction of the progressive trend of the defect. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:134 / 159
页数:26
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