【作者】 朱启兵； 杨慧中；

【Author】 Zhu Qibing,Yang Huizhong School of Communications and Control Engineering,Jiangnan University,Wuxi 214122,P.R.China

【机构】 江南大学通信与控制工程学院；

【摘要】 提出了一种基于卷积型小波包分解与奇异值分解方法相结合的故障特征提取方法,该方法利用卷积型小波包变换将原始时域信号分解到和原信号长度相同的不同频带的小波域,以构成时频矩阵,并采用改进的奇异值分解方法对时频矩阵进行奇异值分解,提取的奇异值向量保留了与原有频带的对应关系,利用该奇异向量作为故障特征向量,实现了故障特征的有效提取。更多还原

【Abstract】 A novel approach to extract fault feature parameters is put forward.First,the time signal is transformed to time-frequency signals which keep same length as that of the original signal by using the convolution type of wavelet packet transformation.Second,considering time-frequency signals as the matrix reflect feature of system,singular value decomposition(SVD) is used to convert the multi-dimension time-frequency matrix to one dimension feature vector.Last,effective feature extraction is achieved.At the same time,an improved singular value decomposition metho(dISVD) is employed.ISVD overcomes shortcomings of classical method which can’t determine corresponding relation of singular value with row vectors of input matrix,and ensures precise of feature information.更多还原