For centrifugal compressor, blades as the most important part suffer periodic vibration and flow induced excitation mechanism. Blade failure has a serious impact on the operation of the compressor as the safety and reliability of the scene. Therefore, how to effective identify compressor blade crack fault is particularly important. As the signal of blade crack failure belongs to low frequency weak fault, the fault frequency is often modulated to the blade passing frequency. It is difficult to classify the characteristic frequency. In this research, filtering at the blade passing frequency is firstly used for preprocessing. Then, the method of Woods-Saxon and Gaussian Potential stochastic resonance is applied to enhance the fault frequency demonstration. It is helpful for blade crack fault characteristic frequency determination. In this research, pressure pulsation (PP) sensors arranged in close vicinity to crack area are used to monitor the blade crack information. It can be concluded that WSGSR model is an effective tool for blade crack early fault detection on centrifugal compressor. As well, the strain experiment is carried out to verify the blade crack fault frequency.
LI Hongkun
,
ZHANG Xiaowen
,
HE Changbo
,
XU Fujian
,
ZHANG Xuefeng
. Weak Fault Enhancement Method for Blade Crack by Using Stochastic Resonance[J]. Journal of Mechanical Engineering, 2016
, 52(1)
: 94
-101
.
DOI: 10.3901/JME.2016.01.094
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