改进FastICA算法在振动筛复合故障诊断中的应用

基金项目:

陕西省教育科学“十二五”规划课题项目(SGH13468)

西京学院科研基金项目（XJ150128）

详细信息

Application of improved FastICA algorithm in compound fault diagnosis of vibrating scree

1.
School of Mechanical and Electrical Technology, Xijing University, Xi''an 710123, China
2.
School of Engineering Machinery, Chang''an University, Xi''an 710064, China

摘要: 针对常见故障特征提取方法不能完全、有效地提取复合故障特征的问题，提出了一种改进快速独立分量分析（FastICA）算法。该算法自适应选择不同的非线性函数进行渐进性分析，提取的数据特征较FastICA算法更准确。将改进FastICA算法应用于振动筛复合故障诊断中，仿真和实测结果表明，该算法可有效提取不同的故障特征，具有较高的分离精度。
- 振动筛 /
- 复合故障诊断 /
- 故障特征提取 /
- 快速独立分量分析
Abstract: In view of problem that common fault characteristic extraction methods could not extract compound fault characteristic completely and effectively, an improved fast independent component analysis(FastICA) algorithm was proposed. The improved FastICA algorithm adaptively selects different nonlinear function to take progressive analysis, so data characteristic extracted by the improved FastICA algorithm is more accurate than that extracted by FastICA algorithm. The improved FastICA algorithm was applied to compound fault diagnosis of vibrating screen. The simulation and actual test results show that the improved FastICA algorithm can extract different fault characteristics effectively with higher separation accuracy.
- vibrating screen /
- compound fault diagnosis /
- fault characteristic extraction /
- fast independent component analysis

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