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A Diagnosis Method Based on Linear Interpolation Fuzzy Neural Network

A fuzzy neural network and linear interpolation technology, applied in the field of online monitoring and fault diagnosis of mechanical equipment, can solve problems such as low accuracy and difficult convergence of neural network training, and achieve the effect of improving convergence and accuracy

Active Publication Date: 2018-06-22
江苏集萃复合材料装备研究所有限公司
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Problems solved by technology

But when the learning knowledge is fuzzy, the neural network training is difficult to converge and the accuracy is not high

Method used

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  • A Diagnosis Method Based on Linear Interpolation Fuzzy Neural Network
  • A Diagnosis Method Based on Linear Interpolation Fuzzy Neural Network
  • A Diagnosis Method Based on Linear Interpolation Fuzzy Neural Network

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Embodiment Construction

[0031] Such as image 3 As shown, the technical route proposed by the present invention is further explained and illustrated by taking the fault diagnosis of rolling bearings as an example. The fault types of rolling bearings generally include inner and outer ring faults and rolling element faults. The specific implementation process is as follows:

[0032] 1. Acquire algorithmic learning knowledge through multi-information fusion.

[0033]

[0034]

[0035]

[0036] and σ are the eigenvalues ​​P i The mean and standard deviation of , where

[0037] Eigenvalue P i The probability distribution function of state 1 and state 2 under is μ 1 (p i ) and μ 2 (p i ), then the possibility distribution function of other unknown states is μ un (p i )=max{0,1-[μ 1 (p i )+μ 2 (p i )]}.

[0038] With the possibility distribution function, we can find out its possibility:

[0039]

[0040]

[0041]

[0042] w 1 、w 2 、w un Denotes the possibility of sta...

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Abstract

The invention relates to a diagnosis method based on the linear interpolation type fuzzy neural network. The method comprises the following steps that a BP neural network is trained by utilizing neural network learning knowledge in which the possibility theory is fused with Dempster & Shafer evidence theory information; and linearization is carried out on a sigmoid activation function, and the possibility of a device fault state is predicted to determine the fault state of a device. The diagnosis method is used to effectively discover the relation between the fuzzy characteristic parameter and the device fault type.

Description

technical field [0001] The invention relates to a diagnosis method based on a linear interpolation type fuzzy neural network, and relates to the technical field of on-line monitoring and fault diagnosis of mechanical equipment. Background technique [0002] In the process of actual equipment monitoring and fault diagnosis, it is often only to observe and analyze a certain kind of information in the equipment operation status information, and extract the symptom information about the equipment operation status from it. Any kind of diagnostic information we extract is fuzzy and uncertain, so it is incomplete to use one aspect of information to reflect its state behavior when diagnosing. Introduce the information fusion technology suitable for the field of fault diagnosis to fully mine the connotation of information, and effectively integrate and utilize multiple diagnostic information, so as to improve the accuracy, effectiveness and reliability of fault diagnosis. [0003] B...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/08
Inventor 李可刘义亚赵宇陈鹏王华庆
Owner 江苏集萃复合材料装备研究所有限公司
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