Abstract
A rotor-stator rubbing position identification method based on casing velocity signal is proposed. Considering that velocity is an ideal parameter to reflect vibration, and its effective value is a standard to the measuring of vibration fault diagnosis in the world, firstly, the rotor experiment rig of aero-engine was used to simulate rubbing faults in different rubbing positions, and casing vibration acceleration signal was collected and changed to velocity signal through integral and polynomial least square fitting method. Secondly, low-frequency normalized energy characteristics of velocity signal and normalized mean-square value characteristics of acceleration signal were extracted; finally, normalized characteristic parameters including energy and mean-square value were input to nearest neighbor classifier and support vector machine(SVM) to identify the different rubbing positions. The results show that low-frequency energy characteristics of velocity signal can effectively identify the rotor-stator rubbing positions of aero-engine, and reach to 93 % of recognition rate based on nearest neighbor classification method and 98 % based on SVM, while mean-square value characteristics of acceleration signal recognition rate can only reach 81 % based on nearest neighbor algorithm and 85 % based on SVM.
Highlights
Rubbing is a kind of common and strong nonlinear fault of the aero-engine, which can seriously affect equipment service life, and may cause tremendous economic loss and casualties [1]
There are representative researches about rubbing position identification, such as: Deng Ai-dong [2] et al, proposing a sub-gradient projection method to identify rubbing position based on energy attenuation model according to acoustic emission (AE) feature
The rotor experiment rig of aero-engine is used to simulate rubbing faults in different rubbing positions of turbine casing, and the casing vibration acceleration signal is collected; secondly, the acceleration signal is changed to velocity signal through integral method and the trend terms are eliminated through polynomial least square fitting method at the same time; thirdly, low-frequency normalized energy characteristics of velocity signal and norm-square value characteristics of acceleration signal are extracted and analyzed; normalized characteristics parameters including energy and mean-square value are input into nearest neighbor classifier and SVM to identify the different rubbing positions, and the identification results are compared and analyzed
Summary
Rubbing is a kind of common and strong nonlinear fault of the aero-engine, which can seriously affect equipment service life, and may cause tremendous economic loss and casualties [1]. AERO-ENGINE ROTOR-STATOR RUBBING POSITION IDENTIFICATION BASED ON CASING VELOCITY SIGNAL. The rotor experiment rig of aero-engine is used to simulate rubbing faults in different rubbing positions of turbine casing, and the casing vibration acceleration signal is collected; secondly, the acceleration signal is changed to velocity signal through integral method and the trend terms are eliminated through polynomial least square fitting method at the same time; thirdly, low-frequency normalized energy characteristics of velocity signal and norm-square value characteristics of acceleration signal are extracted and analyzed; normalized characteristics parameters including energy and mean-square value are input into nearest neighbor classifier and SVM to identify the different rubbing positions, and the identification results are compared and analyzed
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