Rotor rub-impact fault feature extraction method based on complex local mean decomposition

A technology of local mean decomposition and fault characteristics, applied in the field of mechanical vibration, which can solve the problems of inaccurate fault identification and low efficiency.

Active Publication Date: 2014-11-26
ZHONGZHOU UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to provide a rotor rubbing fault feature extraction method based on complex local mean value decomposition to solve the problems of low efficiency and inaccurate fault identification caused by one-dimensional signal processing in the current vibration signal fault identification process

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  • Rotor rub-impact fault feature extraction method based on complex local mean decomposition
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  • Rotor rub-impact fault feature extraction method based on complex local mean decomposition

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Embodiment Construction

[0058] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0059] The present invention aims at the deficiencies of the existing technology, integrates the vibration information of the two channels, and uses the two-dimensional digital processing analysis technology - complex local mean value decomposition to directly process and analyze the two-dimensional signals of the two channels, so that the obtained fault characteristic information is more comprehensive and clear , the fault identification result is more accurate and reliable. The specific implementation process of this method is as follows.

[0060] 1. Collect the vibration signal x on the horizontal direction of the same section of the rotor outer surface and the vibration signal y on the vertical direction. In this embodiment, the eddy current sensor is used to obtain the displacement signals of the horizontal and vertical directions throug...

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Abstract

The invention relates to a rotor rub-impact fault feature extraction method based on complex local mean decomposition, and belongs to the technical field of mechanical vibration. According to the method, firstly vibration signals in mutual vertical directions of the same section are obtained, signals of the two channels form a complex signal, then through complex local mean decomposition, the complex signal is decomposed into a sum of a series of complex product functions, and a complex envelope signal is obtained according to the complex product functions; and the complex envelope signals are transformed by adopting complex Fourier transformation, and then real parts and imaginary parts of complex Fourier transformation results are fused to obtain a corresponding vector envelope spectrum, thereby effectively extracting fault features of a rotor. The rotor rub-impact fault feature extraction method based on complex local mean decomposition in the invention fuses vibration information of two channels, directly processes and analyzes two-dimensional signals of the two channels through complex local mean decomposition, and extracted fault feature information is clearer and more comprehensive, thereby providing a basis for rub-impact diagnosis of the rotor.

Description

technical field [0001] The invention relates to a method for extracting rotor rubbing fault features based on complex local mean value decomposition, and belongs to the technical field of mechanical vibration. Background technique [0002] In recent years, fault diagnosis technology has received significant attention at home and abroad. Extracting fault symptoms from operating dynamic signals is a necessary condition for mechanical fault diagnosis. Since most of the fault vibration signals are nonlinear signals, some advanced digital signal processing methods, such as wavelet transform, second-generation wavelet transform, Empirical Mode Decomposition (EMD), local Mean decomposition (Local Mean Decomposition, LMD) and other methods extract symptoms or characteristics reflecting the fault, and provide technical support for equipment fault diagnosis. Wavelet transform, second-generation wavelet transform, and multi-wavelet transform can be said to be based on the inner produc...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/00
Inventor 黄传金宋海军孟雅俊雷文平甄敬然时伟周铜郭欢雷钢陆程陈良
Owner ZHONGZHOU UNIV
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