Blind source separation (BBS) technology was applied to vibration signal processing of gearbox for separating different fault vibration sources and enhancing fault information. An improved BSS algorithm based on parti...Blind source separation (BBS) technology was applied to vibration signal processing of gearbox for separating different fault vibration sources and enhancing fault information. An improved BSS algorithm based on particle swarm optimization (PSO) was proposed. It can change the traditional fault-enhancing thought based on de-noising. And it can also solve the practical difficult problem of fault location and low fault diagnosis rate in early stage. It was applied to the vibration signal of gearbox under three working states. The result proves that the BSS greatly enhances fault information and supplies technological method for diagnosis of weak fault.展开更多
This paper presents a new blind separation approach of the low order cyclostationary signals based on the cyclic periodicity of the cyclostationary signal.The goal of the method is extracting the hidden periodicity an...This paper presents a new blind separation approach of the low order cyclostationary signals based on the cyclic periodicity of the cyclostationary signal.The goal of the method is extracting the hidden periodicity and reducing the randomicity of cyclostationary signal and it is particularly applicable to the separation of low order cyclostationary signals.The method also demonstrates the importance of extraction of cyclostationary signals from low order to high order in turn.The effectiveness of the proposed method is finally demonstrated by computer simulation and experiment.展开更多
自适应最稀疏时频分析(adaptive and sparsest time-frequency analysis,ASTFA)方法以分解得到的单分量个数最少为优化目标,以单分量的瞬时频率具有物理意义为约束条件,使得到的分量更加合理;结合盲源分离,提出了一种基于ASTFA的盲源分...自适应最稀疏时频分析(adaptive and sparsest time-frequency analysis,ASTFA)方法以分解得到的单分量个数最少为优化目标,以单分量的瞬时频率具有物理意义为约束条件,使得到的分量更加合理;结合盲源分离,提出了一种基于ASTFA的盲源分离方法并应用于齿轮箱复合故障诊断中。该方法首先利用ASTFA将单通道源信号进行分解,然后利用占优特征值法进行源数估计,根据源数重组观测信号,最后对观测信号进行盲源分离得到源信号的估计。实验结果表明,该方法可以有效地对齿轮箱复合故障信号进行分离进而实现齿轮箱的复合故障诊断。展开更多
基金Project(50875247) supported by the National Natural Science Foundation of ChinaProject(2007011070) supported by the Natural Science Foundation of Shanxi Province, China
文摘Blind source separation (BBS) technology was applied to vibration signal processing of gearbox for separating different fault vibration sources and enhancing fault information. An improved BSS algorithm based on particle swarm optimization (PSO) was proposed. It can change the traditional fault-enhancing thought based on de-noising. And it can also solve the practical difficult problem of fault location and low fault diagnosis rate in early stage. It was applied to the vibration signal of gearbox under three working states. The result proves that the BSS greatly enhances fault information and supplies technological method for diagnosis of weak fault.
基金Doctor Foundations of Henan polytechnic university(648391)NSFC(U1304523,51205371)
文摘This paper presents a new blind separation approach of the low order cyclostationary signals based on the cyclic periodicity of the cyclostationary signal.The goal of the method is extracting the hidden periodicity and reducing the randomicity of cyclostationary signal and it is particularly applicable to the separation of low order cyclostationary signals.The method also demonstrates the importance of extraction of cyclostationary signals from low order to high order in turn.The effectiveness of the proposed method is finally demonstrated by computer simulation and experiment.
文摘自适应最稀疏时频分析(adaptive and sparsest time-frequency analysis,ASTFA)方法以分解得到的单分量个数最少为优化目标,以单分量的瞬时频率具有物理意义为约束条件,使得到的分量更加合理;结合盲源分离,提出了一种基于ASTFA的盲源分离方法并应用于齿轮箱复合故障诊断中。该方法首先利用ASTFA将单通道源信号进行分解,然后利用占优特征值法进行源数估计,根据源数重组观测信号,最后对观测信号进行盲源分离得到源信号的估计。实验结果表明,该方法可以有效地对齿轮箱复合故障信号进行分离进而实现齿轮箱的复合故障诊断。
