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基于FSS-kernel BSS方法的机械故障诊断

杨彦龙 程伟 常洪振

杨彦龙, 程伟, 常洪振等 . 基于FSS-kernel BSS方法的机械故障诊断[J]. 北京航空航天大学学报, 2012, (11): 1557-1561.
引用本文: 杨彦龙, 程伟, 常洪振等 . 基于FSS-kernel BSS方法的机械故障诊断[J]. 北京航空航天大学学报, 2012, (11): 1557-1561.
Yang Yanlong, Cheng Wei, Chang Hongzhenet al. Fault diagnosis based on blind source separation using kernel function with finite support samples[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, (11): 1557-1561. (in Chinese)
Citation: Yang Yanlong, Cheng Wei, Chang Hongzhenet al. Fault diagnosis based on blind source separation using kernel function with finite support samples[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, (11): 1557-1561. (in Chinese)

基于FSS-kernel BSS方法的机械故障诊断

详细信息
  • 中图分类号: TN911

Fault diagnosis based on blind source separation using kernel function with finite support samples

  • 摘要: 机械设备发生故障时,故障特征的提取是很重要的.为了从观测信号中分离出不同的故障特征源信号,并根据分离信号准确地进行故障诊断,从观测信号样本出发,提出了基于有限支持样本核函数的盲源分离(FSS-kernel BSS)方法.此方法利用有限的观测样本估计信号的概率分布,得到了评价函数,具有很好的自适应能力.仿真试验结果表明:此方法能成功地分离超、亚高斯混合信号,与其他盲源分离方法相比,此方法具有更好的分离性能.将该方法用于转子不平衡和支座松动的复合故障信号的盲分离,分离出了各复合故障的主要频谱.分离结果表明:此方法应用于机械设备复合故障诊断中是可行的.

     

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出版历程
  • 收稿日期:  2011-07-28
  • 刊出日期:  2012-11-30

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