Method for collecting and extracting fault feature information of low-speed and heavy-load device
A technology of equipment failure and characteristic information, which is applied in the direction of machine/structural component testing, measuring devices, instruments, etc., can solve problems such as failure to diagnose faults, and achieve the effect of ensuring normal operation
Inactive Publication Date: 2014-07-16
BEIJING UNIV OF TECH
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In the actual mechanical fault diagnosis process, the mechanical fault source signal usually does not meet these assumptions, so the fault diagnosis cannot be carried out
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[0033] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0034] (1) Install the acoustic emission sensor on the bearing seat, and collect the acoustic emission signal of the equipment in the working state through the acoustic emission data acquisition instrument connected with the acoustic emission sensor, figure 2 Shown is the time-domain waveform diagram of the collected acoustic emission signal.
[0035] (2) Apply nonlinear redundant lifting wavelet to preprocess the acoustic emission signal collected in step (1), image 3 Shown is the flow chart of the nonlinear redundant lifting wavelet. Steps for nonlinear redundant lifting wavelet:
[0036] 1) Obtain the initial prediction coefficient and update coefficient of each layer according to the interpolation subdivision method, and then introduce The algorithm performs interpolation and zero-fill operation on the initial coefficients, that is, for the j-th lay...
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The invention discloses a method for collecting and extracting fault feature information of a low-speed and heavy-load device. The method can be used for extracting weak fault signals of the device and includes the steps of collecting an acoustic emission signal of the device in the working state through an acoustic emission sensor installed on a bearing block of the device, pre-processing the collected acoustic emission signal through nonlinear redundancy lifting wavelets, carrying out empirical mode decomposition on the pre-processed acoustic emission signal to obtain a plurality of intrinsic mode functions, forming a mixed signal by the intrinsic mode functions with the obvious impact and the obvious periodicity and the original signal, isolating an independent signal through the independent function analysis technology, carrying out Fourier transformation, and therefore extracting the weak fault features of the device. According to the method, the weak fault feature information of the low-speed and heavy-load device can be effectively extracted, and an effective basis is provided for diagnosing faults of the device.
Description
technical field [0001] The invention relates to a method for collecting and extracting equipment fault feature information, in particular to a method for collecting and extracting weak fault feature information of low-speed heavy-load equipment. Background technique [0002] Low-speed and heavy-duty equipment is prone to failure due to low-speed operation, complex and changeable load, and harsh production environment. Once this type of equipment breaks down suddenly, it may cause production interruption, cause huge economic losses to the enterprise, and even cause casualties. Therefore, it is of great practical significance to discover hidden dangers of equipment failure in time. [0003] The vibration signal energy of low-speed heavy-duty equipment failure is weak, and it is easy to be overwhelmed by the surrounding strong environmental noise, so the commonly used vibration detection methods are difficult to work. In a complex factory environment, the signal picked up by t...
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IPC IPC(8): G01M99/00G01H17/00
Inventor 朱立欢崔杰高立新阳子婧
Owner BEIJING UNIV OF TECH