Combined failure identification of intermediate bearing in aeroengine based on wavelet transform,second-order difference,and 1D-LBP

Abstract

Intermediate bearing is one of key parts in double-rotor aeroengine, whose running state usually can only be monitored by casing signals. As the fault characteristic information detected from casing is weak and complex, it is generally difficult to be dug correctly. One-dimensional local binary pattern (1D-LBP) can depict failure information from the perspective of local feature extraction. Currently, the study on the application of 1D-LBP in fault identification is mostly based on original signals; due to the influence of component signals irrelevant to fault and noise, the fault information in original signals is weak and complex; besides, 1D-LBP is rather sensitive to noise, which is extremely possible to cause insufficient extraction of local textural features and the difficulty to identify a fault. To solve this problem and make it possible to precisely identify the fault of intermediate bearing of real aeroengine, the paper has proposed the combined method of wavelet transform (WT), second-order difference with 1D-LBP. WT is highly uncertain to determine the decomposition layer number. To solve the difficulty, correlation coefficient was introduced. Meanwhile, casing vibration signal was subjected to WT. Furthermore, because vibration signal often went with impact components in a bearing failure and second-order difference of signals was sensitive to impact feature, component signals obtained by WT were subjected to second-order difference operation. Additionally, taking advantage of 1D-LBP, second-order differences of signals were locally binarized with average value as criterion. Finally, 1D-LBP signals were re-transformed to decimal 1D local texture signals (1D-LTS). These 1D-LTS can embody local feature information of signals. According to the spectrum of 1D-LTS, combined failure type of intermediate bearing was identified. Through the comparison with WT and classical 1D-LBP method, and failure analysis after disassembly of aeroengine, the effectiveness and engineering applicability of proposed method have been verified.

Keywords

1D-LBP wavelet transform intermediate bearing fault identification feature extraction

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