基于参数优化Morlet小波变换的故障特征提取方法.pdfVIP

学兔兔 第3l卷 第1期 仪 器 仪 表 学 报 Vb1．3lNo．1 2010年1月 Chinese Journal of Scientific Instrument Jan．2010 基于参数优化Morlet 波变换的故障特征提取方法水 蒋永华，汤宝平，刘文艺，董绍江 (重庆大学机械传动国家重点实验室 重庆 400030) 摘 要：针对轴承或齿轮箱等机械元件的故障振动信号表现为冲击衰减波形的特点，提出一种基于参数优化Morlet小波变 换的故障特征提取方法。利用最小Shannon熵方法优化Morlet小波的形状参数，实现与冲击特征成分的最佳匹配，再对小 波变换系数矩阵进行奇异值分解，根据奇异值曲线中主要反映突变信息的过渡阶段所对应的尺度范围求得最佳小波变换尺 度，最后对信号进行Morlet小波变换提取故障特征。仿真试验和实际应用的结果表明，该方法能更有效地从强噪背景中提 取故障特征。 关键词：Morlet小波变换；Shannon熵；奇异值分解 (SVD)；故障特征提取 中图分类号：TH165．3 TN911．2 文献标识码：A 国家标准学科分类代码：510．40 Feature extraction method based on parameter optimized Morlet wavelet transform Jiang Yonghua，Tang Baoping，Liu Wenyi，Dong Sha~iang (The State KeyLaboratoryofMechanical Transmission,Chongqmg University,Chongqing,400030,China) Abstract：According to the fact that the defects of mechanical components such as rolling bearing or gearbox can exci~s vibration with specific impact component，a feature extraction method based on parameter optimized Modet wavelet is proposed．Firstly,minimum Shannon entropy is used to optimize the Morlet wavelet shape factor in order to match with the impact component．Then，an abrupt information detection method based on the transitional stage of singular curve of wavelet coefficient matrix is used to choose the appropriate scale for the wavelet transformation． Finally,the fault feature ofthe signal Can be extracted using this method．Th e experimental results and analysis re— suitsofrollingbeating signals showthattheproposedmethod couldextractfaultfeaturemore effectively． Key words：Morlet wavelet transform；Shannon entropy；singular value decomposition；fault feature extraction