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Civil aircraft fault prediction system based on neural network

A fault prediction and neural network technology, which is applied in the direction of aircraft component testing, etc., can solve problems such as failure to simulate and prompt fault information, failure to accurately judge fault parameters, missing the best time to deal with faults, etc., to improve waterproof performance and service life Effect

Active Publication Date: 2021-10-22
ZHEJIANG GONGSHANG UNIVERSITY
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AI Technical Summary

Problems solved by technology

[0003] In order to solve the problems raised in the above-mentioned background technology, the object of the present invention is to provide a civil aviation aircraft fault prediction system based on neural network, which has the advantage of being able to quickly predict and prompt, and solves the problems of the existing fault prediction system during use. It is impossible to accurately judge the fault parameters, and at the same time, it is impossible to simulate and prompt the fault information, which will easily cause the user to miss the best time to deal with the fault

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Embodiment Construction

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0024] like figure 1 As shown, a kind of neural network-based civil aviation aircraft fault prediction system provided by the present invention includes a preprocessor, the input end of the preprocessor is electrically connected with an import unit, and the import unit includes a previous fault processing data import module, an aircraft normal data The import module, the past fault data import module and the real-time aircraft sensor data import module, the pa...

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Abstract

The invention discloses a civil aircraft fault prediction system based on a neural network, which comprises a preprocessor, the input end of the preprocessor is electrically connected with an import unit, and the import unit comprises a previous fault processing data import module, an aircraft normal data import module, a previous fault data import module and a real-time aircraft sensor data import module. According to the system, the import unit imports various data into the processor through the preprocessor, and the fault data classification module and the error calculation module calculate and simulate the fault probability through the probability prediction module and the deep neural network calculation simulation module. And the recommendation instruction module exports a corresponding previous processing method through the previous fault processing data import module for a user to watch, so that the system has the advantage of being capable of rapidly predicting and prompting, and solves the problem that in the use process of an existing fault prediction system, fault parameters cannot be accurately judged, and fault information cannot be simulated and prompted.

Description

technical field [0001] The invention relates to the technical field of aircraft failure prediction, in particular to a neural network-based civil aviation aircraft failure prediction system. Background technique [0002] During the operation of the aircraft, various data will be predicted by the fault prediction system, but the existing fault prediction system cannot accurately judge the fault parameters during use, and at the same time cannot simulate and prompt the fault information, which may easily lead to Users miss the best time to deal with failures. Contents of the invention [0003] In order to solve the problems raised in the above-mentioned background technology, the object of the present invention is to provide a civil aviation aircraft fault prediction system based on neural network, which has the advantage of being able to quickly predict and prompt, and solves the problems of the existing fault prediction system during use. It is impossible to accurately ju...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B64F5/60
CPCB64F5/60
Inventor 刘东升陈亚辉刘彦妮
Owner ZHEJIANG GONGSHANG UNIVERSITY
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