机电设备早期故障微弱信号的非线性检测方法及工程应用  

Theory and applications of weak signal non-linear detection method for incipient fault diagnosis of mechanical equipments

作　　者：胥永刚[1] 马海龙[1] 付胜[1] 张建宇[1] 

机构地区：[1]北京工业大学机械工程与应用电子技术学院北京市先进制造技术重点实验室,北京100124

出　　处：《振动工程学报》2011年第5期529-538,共10页Journal of Vibration Engineering

基　　金：国家自然科学基金资助项目(50705001;51075009);国家高技术研究发展计划(863)资助项目(2009AA04Z417)

摘　　要：阐述了并联随机共振、混沌振子、差分振子的基本原理和数学模型。并联随机共振利用相关分析从多个随机共振输出结果中提取出相同成分,在一定程度上减小了对参数设置的依赖性。当混沌振子从混沌状态向大尺度周期状态转变时,其相图的Hu氏不变矩值将发生明显的跃变,利用Hu氏不变矩的跃变对混沌振子的状态进行自动定量识别。差分振子相图的大小与待检测信号幅值之间呈现出一种线性比例关系,弥补了差分振子不能检测信号幅值的缺陷。将这三种非线性方法应用于机电设备故障诊断中,成功地提取出了设备早期故障的微弱特征信息,取得了理想的效果。The basic theory and mathematic model of parallel stochastic resonance （PSR）, chaotic oscillator and difference res- onance were expounded. The correlation analysis was applied to extract the same components from the output of difference SR in the PSR, thereby reduce the dependence on the system parameters. When the chaotic oscillator changing from chaos state to large-scale periodic state, the Hu moment invariant will have a distinct change. So the nu moment invariant can be used to automatically quantify the phase state of chaotic oscillator. The linear relationship between the phase diagram size and signal amplitude is presented to make up for the shortage that differential oscillator can＇t detect the signal amplitude. Apply- ing the three nonlinear methods to the fault diagnosis of mechanical equipments, the weak feature information of incipient fault was successfully extracted.

关 键 词：并联随机共振 故障诊断 混沌振子 不变矩 差分振子 

分 类 号：O324[理学—一般力学与力学基础] TP206.3[理学—力学]