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A Generator Life Prediction Algorithm Based on Backpropagation Neural Network

A neural network and life prediction technology, applied in biological neural network models, neural learning methods, etc., can solve problems such as waste, replacement and scrapping, and achieve the effects of reduced maintenance costs, strong fault tolerance, and fast reasoning process

Active Publication Date: 2021-08-17
SHENYANG AIRCRAFT DESIGN INST AVIATION IND CORP OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Today's generator production units generally require that after a certain period of flight, the generator must be removed and sent to the infield for renovation, or after a certain period of work, regardless of the actual performance and status, it is artificially considered that the life span has expired. Replace and scrap, which creates huge waste

Method used

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  • A Generator Life Prediction Algorithm Based on Backpropagation Neural Network
  • A Generator Life Prediction Algorithm Based on Backpropagation Neural Network
  • A Generator Life Prediction Algorithm Based on Backpropagation Neural Network

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Embodiment Construction

[0033] In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be described in more detail below with reference to the accompanying drawings in the embodiments of the present invention.

[0034] It should be noted that: in the drawings, the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The described embodiments are a part of the embodiments of the present invention, but not all of the embodiments, and the embodiments of the present application and the features of the embodiments can be combined with each other without conflict. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0035] As used herein, "schematic" mean...

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Abstract

The invention relates to the field of aviation generator test technology, and specifically provides a generator life prediction algorithm based on a backpropagation neural network. The prediction algorithm of the backpropagation neural network is used, and neurons and their directed weighted connections are used to It implicitly deals with the knowledge of the problem, and has the ability of learning, self-learning and strong fault tolerance. At the same time, the calculation between neurons is relatively independent, which is convenient for parallel processing, the reasoning process is fast, and the life prediction effect is good. The maintenance of aero-generators has changed from after-the-fact maintenance or regular maintenance to condition-based maintenance to reduce maintenance costs.

Description

technical field [0001] The invention relates to the technical field of aviation generator tests, in particular to a generator life prediction algorithm based on a back-propagation neural network. Background technique [0002] As one of the important airborne equipment on the aircraft, the generator is of great practical significance and economic value to make real-time prediction and analysis of its health status and find out the possible hidden troubles in time to ensure the safe flight of the aircraft. [0003] Today's generator production units generally require that the generator must be dismantled and sent to the infield for renovation after a certain period of flight, or after a certain period of work, regardless of the actual performance and state, it is artificially considered that the life limit has expired. Replacement scrap, which creates a huge waste. SUMMARY OF THE INVENTION [0004] In order to overcome at least one defect of the above-mentioned prior art, t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/08
CPCG06N3/084
Inventor 董世良刘海港周莹莹邵海滨艾凤明
Owner SHENYANG AIRCRAFT DESIGN INST AVIATION IND CORP OF CHINA
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