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Self-learning identification method of equipment natural vibration mode based on online vibration data

An identification method and technology of natural vibration, applied in the measurement of vibration, vibration measurement in solids, measurement devices, etc., can solve the problems of messy vibration modes, difficult to judge the value of the characteristic frequency, difficult to identify the characteristic frequency of parts and so on.

Inactive Publication Date: 2018-04-13
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

[0007] The purpose of the present invention is to provide a self-learning identification method for the natural vibration mode of equipment based on online vibration data, which solves the problem of the calculated vibration in the finite element modal analysis of the prior art, especially when the research object is a relatively complex system. The mode is often too messy, it is difficult to identify the eigenfrequency of the component that is really concerned, and it is difficult to judge the value of the eigenfrequency

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  • Self-learning identification method of equipment natural vibration mode based on online vibration data
  • Self-learning identification method of equipment natural vibration mode based on online vibration data
  • Self-learning identification method of equipment natural vibration mode based on online vibration data

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Embodiment Construction

[0053] The present invention will be described in detail below in combination with specific embodiments. The self-learning identification method of the natural vibration mode of the equipment based on the online vibration data of the present invention is carried out according to the following steps:

[0054] Step 1: The noise background at the working site of the equipment is complex, and the collected vibration signals are easily polluted by these noises, so that the real vibration data in the signal are submerged under the strong background noise, which brings a great deal of trouble to the calculation of the natural frequency of the equipment. Difficulties. Assuming that the equipment vibration signal directly collected by the sensor is x(n), its mathematical model can be expressed as:

[0055] x(n)=f(n)+noise(n)

[0056] Among them, f(n) is the original signal; noise(n) is the noise signal.

[0057] Step 2: Use the wavelet packet transform algorithm to denoise the equip...

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Abstract

The invention discloses a self-learning identification method for the natural vibration mode of equipment based on online vibration data. The wavelet packet transform algorithm is used to denoise the equipment vibration signal x(n) once, and the denoised signal is obtained by using singular value decomposition to denoise the signal twice. First denoising to obtain the vibration signal after the second denoising. Use the windowed discrete Fourier algorithm to analyze the frequency spectrum of the denoised vibration signal, and calculate the vibration spectrum of the equipment; use the self-learning algorithm to train the vibration spectrum of the equipment, and finally get The natural characteristic frequency and amplitude of the equipment. The beneficial effect of the invention is that when the research object is a relatively complex system, the characteristic frequency of the components can be accurately identified.

Description

technical field [0001] The invention belongs to the technical field of on-line monitoring, and relates to a self-learning identification method of a natural vibration mode of equipment based on online vibration data. Background technique [0002] Online monitoring technology is the most basic measure to estimate the health status of equipment, especially for mechanical equipment (or systems), vibration monitoring and analysis is the most practical and effective method. The vibration signal of the equipment is closely related to its mechanical structure, and the condition of its internal mechanical structure during the operation of the equipment can be directly and effectively reflected from the vibration signal. By processing and analyzing the vibration signal of the equipment, the inherent vibration mode of the equipment under normal operating conditions is extracted, which is used to distinguish the vibration mode when the equipment is abnormal or faulty, so as to make tim...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01H1/00
Inventor 赵洪山李浪邓嵩徐樊浩
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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