A fault diagnosis approach for roller bearing based on Sparse Bandwidth Mode Decomposition under variable speed condition
Pan Haiyang1,2 ,Zheng Jinde1,Tong Baohong1,Zhang Liangan1,2
1. School of Mechanical Engineering, Anhui University of Technology, Ma’anshan 243032
2. Institute of Industrial Robots, Ma'anshan Anhui University of Industrial Technology Research Institute，Ma’anshan 243000
Abstract：Target to the defect of previous signal processing method, a new non-stationary signal analysis method, namely the sparse bandwidth mode decomposition (SBMD) is proposed in this paper. The essence of this method is that signal decomposition is converted into constrained variational problem, and the signal is decomposed into a set of IMFs by SBMD. In addition to, the vibration signals of roller bearing with variable speed usually have more comprehensive status information, SBMD is applied to the working condition problem of rolling bearing fault diagnosis under the condition of variable speed combined with, order tracking analysis and envelope spectrum. The analysis results from experimental that SBMD order envelope spectrum approach can handle the problem of roller bearing fault diagnosis under variable speed condition accurately and effectively.
潘海洋1，郑近德1,2，童宝宏1，张良安1,2. 基于稀疏带宽模态分解的变转速滚动轴承故障诊断[J]. 振动与冲击, 2017, 36(14): 92-97.
Pan Haiyang1,2,Zheng Jinde1,Tong Baohong1,Zhang Liangan1,2. A fault diagnosis approach for roller bearing based on Sparse Bandwidth Mode Decomposition under variable speed condition. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(14): 92-97.
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