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- Title
基于退化检测和优化粒子滤波的轴承寿命预测方法.
- Authors
许雨晨; 李宏坤; 马 跃; 黄刚劲; 张明亮
- Abstract
Bearings are widely used in various mechanical equipment. In order to avoid sudden damage to the bearing and cause equipment failure, it is of great significance to effectively predict its remaining service life. So a bearing life prediction method based on adaptive degradation detection and particle swarm optimization particle filter (PSO-PF) algorithm is proposed. First, the candidate features are extracted from the bearing vibration signal and screened, the preferred features are weighted and fused to construct a degradation index. Then the adaptive degradation detection method is introduced to determine the first prediction time. Finally, the particle swarm optimization algorithm is introduced to optimize the importance sampling process of the particle filter. The optimized particle filter algorithm is used to predict the remaining life of the bearing from the first prediction time detected. Through the full life experiment of the bearing, the method effectively predicts the remaining life of the bearing, and compared with the conventional particle filter algorithm, the method has higher prediction accuracy.
- Subjects
PARTICLE swarm optimization; ALGORITHMS; MATHEMATICAL optimization; SERVICE life; SAMPLING (Process)
- Publication
Journal of Dalian University of Technology / Dalian Ligong Daxue Xuebao, 2021, Vol 61, Issue 3, p227
- ISSN
1000-8608
- Publication type
Article
- DOI
10.7511/dllgxb202103002