;where the parameter k sets the decay rate of the exponent, and the parameter ω sets the dominant cyclic wavelet frequency; a matrix of wavelet coefficients is formed and a signal scalogram is bui and the dominant eigenfrequencies of the equipment containing shock processes are determined via searching for scaleogram maxima; sets of wavelet coefficients corresponding to the frequencies found on the scalogram are selected; an envelope is constructed for each selected set of wavelet coefficients using the Hilbert transform, that envelope yields the location of shock pulses in the temporal signal; Fourier transformation of the envelope of the set of wavelet coefficients is calculated to search for a set of frequencies of the bearings in the spectrum and a matrix is formed of the bearing frequencies thus found; comparing the totality of the bearing frequencies retrieved with their template, a conclusion is drawn about the technical state of the bearing."/> METHOD FOR VIBRATION DIAGNOSTICS OF ROTARY EQUIPMENT TO DETECT DEFECTS OF ROLLING BEARINGS
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METHOD FOR VIBRATION DIAGNOSTICS OF ROTARY EQUIPMENT TO DETECT DEFECTS OF ROLLING BEARINGS

机译:旋转设备振动诊断检测滚动轴承缺陷的方法

摘要

The invention relates to the field of vibration diagnostics of rotary equipment using systems and methods to process vibration signals and can be used for early detection of defects in industrial equipment that develop in the course of its operation, enabling timely maintenance and repair. The method for vibration diagnostics of rotary equipment to detect defects of rolling bearings by processing vibration signals is proposed, namely, the vibration signal received from the accelerometer installed on the equipment is subjected to wavelet transform using the basis function ψm(t); ;where the parameter k sets the decay rate of the exponent, and the parameter ω sets the dominant cyclic wavelet frequency; a matrix of wavelet coefficients is formed and a signal scalogram is bui and the dominant eigenfrequencies of the equipment containing shock processes are determined via searching for scaleogram maxima; sets of wavelet coefficients corresponding to the frequencies found on the scalogram are selected; an envelope is constructed for each selected set of wavelet coefficients using the Hilbert transform, that envelope yields the location of shock pulses in the temporal signal; Fourier transformation of the envelope of the set of wavelet coefficients is calculated to search for a set of frequencies of the bearings in the spectrum and a matrix is formed of the bearing frequencies thus found; comparing the totality of the bearing frequencies retrieved with their template, a conclusion is drawn about the technical state of the bearing.
机译:本发明涉及旋转设备的振动诊断领域,其使用处理振动信号的系统和方法,并可用于及早检测在其运行过程中发展的工业设备中的缺陷,从而能够及时进行维护和修理。提出了一种通过处理振动信号对旋转设备进行振动诊断的方法,以检测滚动轴承的缺陷,即利用基函数ψ m m将从安装在设备上的加速度计接收到的振动信号进行小波变换。子>(t); <图像文件=“ IMGA0002.GIF” he =“ 23” imgContent =“绘图” imgFormat =“ GIF” wi =“ 103” /> ;其中参数k设置指数的衰减率,参数ω设置主循环小波频率;形成小波系数矩阵并建立信号比例尺。并通过搜索比例尺最大值确定包含冲击过程的设备的主要特征频率。选择与在比例尺图上找到的频率相对应的小波系数集;使用希尔伯特(Hilbert)变换为每个选定的小波系数集构造一个包络,该包络产生冲击脉冲在时间信号中的位置;计算该组小波系数的包络的傅立叶变换,以搜索频谱中轴承的一组频率,并由此找到的轴承频率形成一个矩阵。将检索到的轴承频率的总数与其模板进行比较,得出轴承的技术状态的结论。

著录项

  • 公开/公告号EA034627B1

    专利类型

  • 公开/公告日2020-02-28

    原文格式PDF

  • 申请/专利号EA20180000244

  • 发明设计人 YURY PAVLOVICH;

    申请日2018-03-06

  • 分类号G01M7/02;G01M13/04;

  • 国家 EA

  • 入库时间 2022-08-21 11:17:33

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