基于小波分析的螺栓联接松动故障诊断  

Fault Diagnosis of the Attachment Bolt Looseness Based on Wavelet Analysis

作　　者：闫航瑞[1] 曾国英[1] 赵登峰[1] 田美子[1] 

机构地区：[1]西南科技大学制造科学与工程学院省部共建教育部重点实验室-制造过程测试技术,绵阳621010

出　　处：《机械科学与技术》2012年第7期1110-1114,共5页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金-中国工程物理研究院联合资金项目(10876034)资助

摘　　要：应用小波分析法兰螺栓联接结构不同测点的振动信号,提取能识别螺栓联接松动状况的特征量并考察不同测点的监测结果。基于NI数据采集设备搭建实验平台,定性地分析了螺栓联接松动的变化过程和响应信号的频谱图,选择合适的小波函数并进行小波分层;在此基础上对响应信号进行小波分解,得到随着预紧力的变化均匀布置的各测点细节系数的等高线图及其幅值大小和范围、敏感层的有效值。结果表明:对法兰盘上均匀分布的各测点的响应信号进行DWT结合统计分析,其特征量均随着预紧力的变化有明显差别,能较好的识别螺栓联接状态。Discrete wavelet transform （DWT） is suggested to analyze the acceleration signals at different testing points, in order to study the characteristic quantity of bolted joints condition and monitor the results of the localized sensor region. The experimental system is built with the NI data acquisition equipment. Based on the qualitative analysis for the loose process of the bolted joints and the spectrum analysis for response signals, an appropriate wavelet function is chosen and the decomposed different measuring points, the contour diagrams levels are determined. According to the amplitude of each level at are drawn, then the maximun, minimun amplitude and range of all levels＇detail coefficients and the RMS of detail coefficients at the sensitive level are calculated. The experimental result shows that through the DWT combined with statistical analysis to analyze the response signals at evenly dis- tributed measuring points, the obtained characteristic quantities have significant difference with the preloading changes and can identify the bolted joints condition in a better way.

关 键 词：螺栓联接 小波分析 特征分析 状态识别 均布测点 

分 类 号：TH131.3[机械工程—机械制造及自动化]