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Method for identifying friction fault between dynamic and static member on the basis of CNN sound emission

A dynamic and static, acoustic emission technology, applied in the field of CNN-based acoustic emission identification of friction faults between dynamic and static components, can solve the problems of poor recognition effect and low recognition rate of friction faults

Active Publication Date: 2016-01-13
HUZHOU TEACHERS COLLEGE
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Problems solved by technology

[0005] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art and provide a method for identifying friction faults between dynamic and static components based on CNN acoustic emission, which aims to solve the problem of low recognition rate and poor recognition effect of friction faults in rotating machinery in the prior art technical issues

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  • Method for identifying friction fault between dynamic and static member on the basis of CNN sound emission
  • Method for identifying friction fault between dynamic and static member on the basis of CNN sound emission

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[0029] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below through the accompanying drawings and embodiments. However, it should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

[0030] refer to figure 1 , the embodiment of the present invention provides a method for identifying frictional faults between dynamic and static components based on CNN acoustic emission, which is based on a feed-forward CNN network, the feed-forward CNN network is based on multi-layer induction with basic Logistic mapping neurons, The feed-forward CNN network includes two parts, a front hidden layer ...

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Abstract

The invention relates to the technical field of friction fault detection, and discloses a method for identifying friction faults between dynamic and static members on the basis of CNN sound emission. The method is based on a feedforward CNN network which is based on multilayer induction of neurons having basic Logistic mapping; the feedforward CNN network comprises a front hidden layer and a back hidden layer; the front hidden layer is composed of neurons F and neurons B in pairs; the neurons F receive weighting from last layer and output; the neurons B receive from itself and output; the back hidden layer is composed of neurons H for receiving the corresponding neurons F and neurons B, and outputs in a hidden manner through a weighting function. The method for identifying friction fault between dynamic and static member on the basis of CNN sound emission has advantages of simple steps, performance better than that of the conventional BP network model, requirement for less nodes and shorter time than the similar theory and identical layer, and high identification rate, and can effectively avoid resulting problems of local minimum value.

Description

【Technical field】 [0001] The invention relates to the technical field of friction fault detection, in particular to a method for identifying friction faults between dynamic and static components based on CNN acoustic emission, which improves the detection efficiency of friction faults caused by dynamic and static components of large rotating machinery in the manufacturing process. 【Background technique】 [0002] Dynamic and static friction is a frequent failure of rotating machinery. When a friction failure occurs, force shock and thermal shock will occur on the rotor at the same time. In order to reduce steam (gas) leakage, the dynamic and static clearance of large rotating machinery is usually designed to be very small. Friction failures not only occur during the start and stop of the unit, but also dynamic and static friction may occur due to slight carelessness during installation, maintenance and operation. After the friction fault occurs, the vibration of the unit may ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08
Inventor 蒋云良成新民申情
Owner HUZHOU TEACHERS COLLEGE
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