التفاصيل البيبلوغرافية
| العنوان: |
基于参数优化变分模态分解的变速工况下 轴承故障诊断. (Chinese) |
| Alternate Title: |
Fault Diagnosis for Bearings Operated Under Varing Speed Based on Parameter Optimization VMD. (English) |
| المؤلفون: |
刘前进, 高丙朋, 宋振军, 王维庆 |
| المصدر: |
Bearing; 2022, Issue 8, p71-78, 8p |
| مصطلحات موضوعية: |
ROLLER bearings, ROTATING machinery, FAULT diagnosis, ENTROPY, SPARROWS, SPEED, FEATURE extraction |
| Abstract (English): |
Aimed at varing speed of bearings and difficult extraction of weak fault features during operation of rotating machinery, a feature extraction method based on order tracking and parameter optimization variational mode decomposition is proposed. The non - stationary time domain signal is transformed into a stationary angle domain signal by order tracking. The kernel mutual information is used as fitness function, and the mutation sparrow algorithm is used to search the optimal parameters of VMD. Finally, the bearing faults are classified according to multi - scale sample entropy of modal components. The simulation and experimental results show that this method can effectively extract the weak fault features from fault signals of rolling bearings operated under varing speed, and realize the dynamic diagnosis of bearing faults. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
针对旋转机械运行过程中轴承转速变动, 微弱故障特征不易提取等问题, 提出一种基于阶次跟踪和参数 优化变分模态分解的特征提取方法。通过阶次跟踪将非平稳时域信号转化为平稳的角域信号, 以核互信息为 适应度函数, 采用变异麻雀算法搜索变分模态分解的最优参数, 最后根据模态分量的多尺度样本熵对轴承故障 进行分类。仿真和试验结果表明, 该方法在变转速滚动轴承故障信号中能有效提取微弱故障特征, 实现轴承故 障的动态诊断。 [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
