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Rotation mechanical fault feature extraction method and device

A technology of fault characteristics and rotating machinery, applied in the field of mechanical vibration, can solve the problems of non-uniform decomposition scale, low efficiency and long running time of one-dimensional signal processing

Active Publication Date: 2018-05-18
ZHENGZHOU INST OF TECH
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Problems solved by technology

[0008] The purpose of the present invention is to provide a method and device for extracting fault features of rotating machinery to solve the problems of long running time, low efficiency, and non-uniform decomposition scales existing in the current fault identification process of rotating machinery.

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  • Rotation mechanical fault feature extraction method and device
  • Rotation mechanical fault feature extraction method and device
  • Rotation mechanical fault feature extraction method and device

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Embodiment Construction

[0082] The specific implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0083] Aiming at the deficiencies of the prior art, the present invention proposes a binary feature scale decomposition method—complex local feature scale decomposition (CLCD), which is combined with the full vector spectrum technology to directly process the dual-channel signal to ensure It ensures that the signals of each channel have the same decomposition scale, which is convenient for information fusion. Because CLCD uses bilinear transformation, the method has strong adaptability, comprehensive fault feature extraction, fast speed and high efficiency, and has good technical effect. The specific implementation process of the method is as follows.

[0084] The first step is to propose a binary feature scale decomposition method - Complex Local Feature Scale Decomposition (CLCD). The specific ...

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Abstract

The invention relates to a rotation mechanical fault feature extraction method and device. A binary feature scale decomposing method (complex local characteristic-scale decomposition, CLCD) is provided. Vibration signals in a same plane and vertical direction are collected and combined to form a complex signal; through CLCD, the signal is self-adaptively decomposed into multiple intrinsic scale components, and the real part characteristics and the virtual part characteristics are fused by a full vector spectrum technology. The provided CLCD method processes a dual channel signal directly, ensures that each channel signal to have a same decomposition scale, and is benefit for information fusion. Moreover, dual linear transformation is used, thus the self-adaptive property of the method is strong, the fault feature extraction is comprehensive, fast, and efficient, and a good technical effect is achieved.

Description

technical field [0001] The invention relates to a method and device for extracting fault features of rotating machinery, belonging to the technical field of mechanical vibration. Background technique [0002] In recent years, the fault diagnosis of rotating machinery has become a research hotspot. How to accurately extract the characteristics of vibration signals from fault vibration signals is the key to the study of rotating machinery faults. Rotating machinery exhibits different vibration intensities at different times and in different directions. The fault diagnosis method based on single-channel information will split the characteristic information of the rotor vibration signals in different directions, and cannot fully reflect the fault characteristics. Considering that the oscillating trajectory of each harmonic in the direction perpendicular to each other in the same section of the rotor is an ellipse in the steady state, people have proposed fault feature extraction...

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Application Information

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IPC IPC(8): G01M13/00
CPCG01M13/00
Inventor 赵静周万春陈晓黄传金孟雅俊
Owner ZHENGZHOU INST OF TECH
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