自适应多小波基函数构造与机械故障诊断应用研究.docVIP

 自适应多小波基函数构造与机械故障诊断 应用研究# 何正嘉，孙海亮，訾艳阳* 5 10 （西安交通大学机械工程学院机械制造系统工程国家重点实验室） 摘要：设备在运行中萌生的故障(即早期故障)，特征信息微弱且往往被机械设备运行过程的 强噪声所淹没，给故障诊断与预示带来困难，已成为国内外本领域研究的热点和难点。本文 深入研究机械故障动态信号与基函数的内积变换原理；提出了若干自适应多小波基函数构造 方法；改进了几种多小波邻域区间和局部阈值降噪方法。利用典型的工程案例分析和阐述了 重油催化裂化装置、连铸连轧机组、空分机、电力机车和船载卫通站传动系统在运行状态下， 微弱动态信号的特征增强和复合故障特征提取的工程应用实效。 关键词：机械故障诊断；内积变换原理；自适应基函数；多小波降噪；故障特征提取 中图分类号：TH17 15 Adaptive construction of multiwavelet basis functions and its applications for mechanical fault diagnosis HE Zhengjia, SUN Hailiang, ZI Yanyang (State Key Laboratory for Manufacturing and Systems Engineering, School of Mechanical 20 25 30 35 40 Engineering,Xi’an Jiaotong University) Abstract: The faults initiated in operation (i.e. incipient fault) with the obscure symptoms and weak features, are always contaminated by a large amount of background noise. Hence, fault diagnosis and prognosis of incipient faults have been the difficulty and focus of the research field. The paper has studied the principle of inner product transform of dynamic signals and basis functions; has proposed several construction methods of adaptive multiwavelet basis functions; has improved several multiwavelet denoising methods with neighborhood and local threshold. The typical engineering cases of the equipment of heavy oil catalytic cracking, the continuous casting and rolling mills, the air compressor, the electric locomotive and the transmission device of satellite comunication on ship have been studied, the results show the effectiveness of enhancement of weak dynamic signals and features extraction of compound faults. Key words: mechanical fault diagnosis; principle of inner product transform; multiwavelet denoising; adaptive basis function; fault feature extraction 0 引言 简机械、运载、能源、冶金、石化、国防等国民经济重要行业的关键机械设备，长期在 重载、疲劳、腐蚀、高温等复杂恶劣的工况下运行，设备中的核心零部件和重要机械结构不 可避免地发生不同程度的故障。机械设备一旦出现事故，将带来巨大的经济损失和人员伤亡。 在工程实践中，期望对事故的发生能够做到防患于未然，因此必须开展对关键机械设备早期 故障和复合故障诊断与预示的研究。为有效开展故障诊断，获取机械设备运行过程中的状态 信息，提取信号特征是实现故障诊断的重要手段，其本质是信号变换和特征提取。 近年来工程中广泛应用的小波变换