改进二阶统计量算法在风力机主轴承裂纹识别中的应用

被引:11
作者
周勃 [1 ,2 ]
孟强 [2 ]
刘欢 [2 ]
陈长征 [2 ]
机构
[1] 沈阳工业大学建筑工程学院
[2] 辽宁省振动噪声控制技术工程研究中心
关键词
故障诊断; 风力机; 裂纹识别; 盲源分离; 二阶统计量;
D O I
10.16385/j.cnki.issn.1004-4523.2013.05.012
中图分类号
TH165.3 []; TN911.7 [信号处理];
学科分类号
081002 [信号与信息处理];
摘要
针对风力机主轴承裂纹故障的非平稳信号,提出一种改进二阶统计量的盲源分离算法,利用信号的非平稳性,将传感器数据分成不重叠的时间窗,用广义时滞协方差矩阵代替标准协方差矩阵,然后估计每个窗内的时滞协方差矩阵平均值来提高算法的稳健性和精确度。仿真试验选取了适当的时延系数和加权参数,证明了改进算法在信噪比低于12dB的情况下优于传统SOS算法。最后,采集了某风场带有裂纹故障的风力机主轴承振动信号,根据本文提出的改进算法剔除了噪声干扰,从观测信号中分离出裂纹冲击振动源信号,并通过信号处理结果的频率特征来识别轴承裂纹状态。
引用
收藏
页码:779 / 785
页数:7
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