摘要
采用声发射技术对滚动轴承进行非接触检测,利用小波分解把故障轴承信号分解在不同频段,然后依照各频带能量重构信号,消除背景噪声,对降噪信号进行EMD分解,对分解后感兴趣的IMF进行边际谱分析,观察特征频率,得到清晰的故障信息,以此诊断轴承故障。
Rolling bearings were inspected using non-contacting acoustic emission technique. The signals of the fault bearings were decomposed using the wavelet analytical method in different frequency bands, then the signals were reconstructed based on the energy of each frequency band to cancel background noises and to de- compose the lowered noise signals in EMD. A Hilbert marginal spectrum analysis was conducted of the interesting intrinsic mode function (IMF) after decomposition, the characteristic frequency bands were observed, and clear fault information was obtained for inspecting bearing faults.
出处
《化工机械》
CAS
2009年第4期326-330,共5页
Chemical Engineering & Machinery
基金
黑龙江省自然科学基金项目资助(E2007-02)
黑龙江省教育厅科学技术研究项目资助(11521004)