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Rotary machine fault detection method of dual-tree complex wavelet transformation with adjustable quality factors

A dual-tree complex wavelet and quality factor technology, applied in the testing of mechanical components, vibration measurement in solids, testing of machine/structural components, etc., can solve problems such as inaccurate periodic information

Inactive Publication Date: 2014-01-08
XI AN JIAOTONG UNIV
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Problems solved by technology

However, in engineering practice, it is found that these real-valued wavelet basis functions have the disadvantage of time-shift variability in the analysis, and inaccurate periodic information may be obtained for periodic shock signals

Method used

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  • Rotary machine fault detection method of dual-tree complex wavelet transformation with adjustable quality factors
  • Rotary machine fault detection method of dual-tree complex wavelet transformation with adjustable quality factors
  • Rotary machine fault detection method of dual-tree complex wavelet transformation with adjustable quality factors

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Embodiment Construction

[0059] combine Figure 1 to Figure 7 , the rotating machinery fault detection method based on the adjustable quality factor dual-tree complex wavelet transform of the present invention, such as figure 1 As shown, its main steps include:

[0060] Step 1: Signal acquisition and preprocessing, including:

[0061] a. Arrange vibration sensors on electromechanical equipment to collect vibration response signals of monitoring objects;

[0062] b. Perform de-average processing on the collected signal x to obtain a preprocessed signal x that eliminates the DC component (1) ,Expressed as:

[0063] x ( 1 ) = x - 1 n Σ i = 1 n x i

[0064] Among them, n is the length of the x sequence, x i for each sequence...

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Abstract

The invention discloses a rotary machine fault detection method of dual-tree complex wavelet transformation with adjustable quality factors. The rotary machine fault detection method of dual-tree complex wavelet transformation with the adjustable quality factors comprises the steps of (1) building a reasonable sampling parameter set, building dual-tree complex wavelet base functions with different quality factors, (2) using each built dual-tree complex wavelet base function to carry out time-scale analysis on a vibration response signal of a rotary machine, calculating kurtosis information entropy of wavelet coefficients of each layer with participation of each dual-tree complex wavelet base function, selecting a dual-tree complex wavelet base function corresponding to the maximum feature kurtosis information entropy as the dual-tree complex wavelet base function which is in optimal matching with an impact component of the vibration signal, and (3) analyzing the vibration signal through the optimal dual-tree complex wavelet base function, and carrying out fault diagnosis. According to the rotary machine fault detection method of dual-tree complex wavelet transformation with the adjustable quality factors, the dual-tree complex wavelet base functions with any frequency-band focusing performance and time-domain oscillation performance can be built, the base function with the optimal matching performance can be selected in a self-adaptation mode, and accurate detection of periodicity impact type fault features and information of the impact period of a rotary machine device can be achieved.

Description

technical field [0001] The invention relates to a fault diagnosis technology for electromechanical equipment, in particular to a method for extracting impact-type fault features of key parts (bearings, gears, rotor rubbing and other rotating machines). Background technique [0002] In the pillar industries of the national economy, large-scale electromechanical equipment operates under complex and harsh working conditions such as heavy load, fatigue, corrosion, and high temperature for a long time. Faults such as peeling, gluing, scratches, cracks, etc., resulting in a decline in the quality of equipment operation and even vicious accidents of machine crashes and fatalities. Therefore, it is of great significance to realize the operation status monitoring and early fault diagnosis of key components of equipment to ensure the safe operation of equipment and the smooth progress of production activities. [0003] When a rotating machine passes through a local damage location, t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/00G01H1/12
Inventor 何正嘉张春林曹宏瑞李兵訾艳阳陈雪峰张周锁陈彬强
Owner XI AN JIAOTONG UNIV
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