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Construction method of morphological filter based on adaptive multi-scale AVG-Hat transformation

A technology of morphological filter and construction method, applied in the direction of impedance network, digital technology network, electrical components, etc., has a strong ability to achieve fault impact characteristics, accurate and reliable filtering results, and overcomes the inability to take into account signal noise reduction and detail retention Effect

Active Publication Date: 2017-03-08
SHIJIAZHUANG TIEDAO UNIV
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However, in the prior art, there are no related technical records that can well solve these two key problems.

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  • Construction method of morphological filter based on adaptive multi-scale AVG-Hat transformation
  • Construction method of morphological filter based on adaptive multi-scale AVG-Hat transformation
  • Construction method of morphological filter based on adaptive multi-scale AVG-Hat transformation

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Embodiment Construction

[0037] Attached below Figure 1 to Figure 6 A method for constructing a morphological filter based on adaptive multi-scale AVG-Hat transformation proposed by the present invention will be described in detail with specific embodiments.

[0038] According to the four basic operations of morphological processing of one-dimensional signals and the characteristics of fault shock characteristics in bearing fault signals, the definition of morphological AVG-Hat transformation and the construction method of morphological AVG-Hat filter are proposed.

[0039] like Figure 1 to Figure 6 As shown, this example describes the method of constructing the morphological filter of the adaptive multi-scale morphological AVG-Hat transformation, and using this method to diagnose the actual fault vibration signal of the outer ring of the rolling bearing.

[0040] The specific process is as follows:

[0041] Step 101: Set the sampling frequency of the acceleration sensor, and collect the fault vib...

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Abstract

The invention discloses a construction method of a morphological filter based on adaptive multi-scale AVG-Hat transformation. The construction method comprises following steps of: 1, determining the number of initial multi-scale structure elements of a signal and an initial structure element value according to a set parameter index based on a bearing fault signal; 2, constructing a set formed by the initial multi-scale structure elements through morphological expansion operation; 3, calculating results of the corresponding morphological AVG-Hat transformation of the bearing fault signal under the initial multi-scale structure elements, and constructing a set of the result; 4, selecting a ratio of the arrangement entropy of the filtered bearing fault signal to sparseness degree of an envelope spectrum as an evaluation index, and adaptively determining an optimal weight coefficient corresponding to the filtered initial multi-scale structure elements; and 5, according to the weight coefficient, constructing an optimal multi-scale morphological AGV-Hat filter. The construction method is advantageous in that the construction method is compatible to signal de-noising and fault feature extraction and accuracy of filtering results can be kept.

Description

technical field [0001] The invention relates to a construction method of a morphological filter based on adaptive multi-scale AVG-Hat transformation, which belongs to the technical field of mechanical fault diagnosis and signal processing. Background technique [0002] In actual engineering, the vibration signal of rolling bearing fault is a typical nonlinear and non-stationary signal, and the fault characteristics in the signal are easily covered by various background noises. Therefore, it is very difficult to diagnose bearing faults under strong background noise. Mathematical morphology is a typical nonlinear signal processing method. It uses specific scale and shape structural elements to fit and modify the local details of the signal time domain waveform. It can effectively eliminate the background while extracting the main waveform features in the signal. noise interference. The key to using morphological methods to process fault signals is to construct a morphological...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H03H17/02
CPCH03H17/0201H03H17/0211
Inventor 邓飞跃杨绍普郭文武潘存治郝如江申永军
Owner SHIJIAZHUANG TIEDAO UNIV
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