Gear Fault Detection under Fluctuating Operating Conditions by Means of Discrepancy Analysis

被引：0
|
作者：
Heyns, Theo [1 ]
Heyns, Stephan [2 ]
机构：
[1] Univ Pretoria, Dept Elect & Comp Engn, Private Bag X20, ZA-0028 Hatfield, South Africa
[2] Univ Pretoria, Dept Mech & Aeronaut Engn, Dynam Syst Grp, ZA-0028 Pretoria, South Africa
来源：
CONDITION MONITORING OF MACHINERY IN NON-STATIONARY OPERATIONS | 2012年
关键词：
condition monitoring; fluctuating operating conditions; discrepancy analysis; change detection; auto-encoder; spectrum; cepstrum;
D O I：
暂无
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
A study is presented where an autoencoder is used to learn non-linear principal components (PCs) which are representative of windowed samples from a vibration signal which are generated by a gearbox in a healthy condition. The PCs are optimized to represent hidden characteristics of the healthy data as experienced over different operating conditions. The auto-encoder may thus be used to detect signal distortions (discrepancies) in a novel signal, where the discrepancies are the result of machine faults. By analyzing the vibration signal piece-wise by means of block windows it is possible to generate a discrepancy signal. The discrepancy signal indicates the time instances and associated severity of individual signal discrepancies. The periodicity of the discrepancy signal, as analyzed by means of its spectrum and cepstrum, allows for insight into which gear components are damaged. The case study assumes that neither any additional transducers, nor any historical fault data are available.
引用
收藏
页码：81 / 88
页数：8
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