Damage Analysis of Rolling Bearings Based on Model Correlation Dimension

2018 4th International Conference on Environmental Science and Material Application

生态环境科学;材料科学

H., Xu ; D., Chen ; X., Wang ; B., Ye

Guangzhou Civil Aviation College, Guangzhou

510470, China^1

Guangzhou Academy of Special Equipment Inspection Testing, Guangzhou

510180, China^2

关键词: Actual conditions;    Auto-regressive;    Correlation dimensions;    Effective analysis;    Model correlation;    Principal Components;    Rolling bearings;    Vibration signal;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/252/2/022111/pdf
DOI  :  10.1088/1755-1315/252/2/022111

来源: IOP

【 摘 要 】

Vibration signals of the rolling bearing are non-stationary, EEMD is occupied to decompose the signals; then ARMA model, which has higher accuracy, is established based on the signal principal components from the EEMD; then correlation dimension of the Auto-regressive (AR) parameters, taken from the ARMA model, serve as the feature vectors to be input to LSSVM for discriminating the actual conditions of rolling bearings. The results demonstrate that: the fault-patterns could be obtained accurately with the presented method, and it is an effective analysis method.