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自适应非线性BSS及其在齿轮故障诊断中的应用
引用本文:王晓伟,石林锁.自适应非线性BSS及其在齿轮故障诊断中的应用[J].振动与冲击,2012,31(10):45-48.
作者姓名:王晓伟  石林锁
作者单位:第二炮兵工程大学502教研室 西安 710025
摘    要:基于核函数的非线性盲信号处理(BSS)在信号处理中有着广泛的应用,但传统的非线性盲信号处理的学习速率是固定的,如果学习速率选择的不合适,则算法难以收敛或者不能收敛。针对这一不足,结合模拟退火的思想,提出了一种基于核函数的自适应非线性盲信号处理算法。仿真和实验结果表明,该方法改善了原有算法的收敛性能,分离效果良好,算法具有更好的消噪和信号特征提取能力。

关 键 词:盲信号处理    振动信号    非线性混合    核函数    故障诊断  
收稿时间:2011-6-15
修稿时间:2011-8-29

Adaptive nonlinear blind source separation and its application in gear faults diagnosis
WANG Xiao-wei,SHI Lin-suo.Adaptive nonlinear blind source separation and its application in gear faults diagnosis[J].Journal of Vibration and Shock,2012,31(10):45-48.
Authors:WANG Xiao-wei  SHI Lin-suo
Affiliation:No.502 Faculty, The Second Artillery Engineering College, Xi’an 710025
Abstract:The nonlinear blind source separation algorithm based on kernel function has been widely applied in blind signal processing.However,if the learning rate of the traditional kernal function is unsuitable,the algorithm would be difficult in convergency or would never be convergent.So combining with simulated annealing algorithm,an adaptive nonlinear blind source separation based on kernel function was proposed.The results of simulation and experiment indicate that the improved algorithm can improve the convergence performance and the effectiveness of BSS.The improved algorithm has better ability of noise reduction and feature extraction than the fixed rate nonlinear blind source separation.
Keywords:blind source separation  vibration signal  nonlinear mixing  kernel function  fault diagnosis
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