摘要
对机械设备的振动信号进行采集在检测设备故障方面具有重要意义。由于机械设备使用环境的不同,使得机械设备振动信号存在不定性。传统的故障检测方法主要对机械设备使用环境进行了分析,忽略了机械设备振动信号采集对故障检测结果的影响,导致检测结果不准确、效率低的问题。提出基于小波域维纳滤波的机械设备故障检测方法。先将维纳滤波和小波阕值滤波相结合,组建机械设备振动信号采集模型,得出真实信号与滤波后信号误差,融合于小波阈值滤波原理对含噪声信号进行正交小波变换,并通过快速独立分量分析原理对机械设备振动信号进行分离,组建具有单位方差的信号初始分离矩阵,并求出源信号的估计值,依据估计值完成对机械设备振动信号的采集,实现对机械故障设备故障的检测优化。仿真结果证明,采用所提方法进行信号采集,可提高机械设备故障检测的效率、减小检测误差、鲁棒性较强。
This article proposes a method for fault detection of mechanical equipment based on Wiener filtering of wavelet domain. Firstly, Wiener filtering was combined with wavelet threshold filtering to build acquisition model for vibration signal of mechanical equipment and error between real signal and filtered signal was obtained. Then orthogonal wavelet transform was carried out for noise signal integrated with principle of wavelet threshold filtering and vibration signals were separated via analysis principle of fast independent component. Moreover, the research built an initial disjunction matrix of signals with unit variance and worked out estimated value of origin signal. Finally, the collection of vibration signal according was completed to estimated value and the detection optimization was realized for mechanical failure and equipment failure. Simulation results show that the method can improve efficiency of fault detection and decrease detection error and has strong robustness.
作者
谢世满
XIE Shi - man(College of Mechanical Engineering, North China University of Science and Technology,Tangshan Hebei 063009, Chin)
出处
《计算机仿真》
北大核心
2017年第6期419-422,共4页
Computer Simulation
基金
唐山市科技计划项目(12140202A-3)
关键词
机械设备
振动信号
采集
故障
检测
优化
Mechanical equipment
Vibration signal
Acquisition
Fault
Detection
Optimization
