Maintenance outfield aircraft fuel system fault prediction method based on flight parameter data

Abstract

The invention provides an aircraft fuel system fault prediction method based on flight parameter data. The method comprises the following steps that a time series data set composed of N aircraft parameters sensitive to faults in an aircraft fuel system is obtained; constructing a long-short-term neural network model according to the time series data set, and obtaining an actual prediction result of the time series data set according to the long-short-term neural network model; determining a fault discrimination model f (x) according to the time series data set; acquiring a real data set of fault conditions of a part of known aircraft fuel systems, and determining a fault threshold according to the fault discrimination model f (x) and the real data set; and determining the probability density of an actual prediction result according to the fault discrimination model, and judging the health condition of the aircraft fuel system by comparing the probability density of the actual prediction result with a fault threshold. According to the method, the aircraft fuel system is subjected to fault prediction in a mode of combining the long-term and short-term neural network model and the fault discrimination model f (x), so that the health condition of the aircraft fuel system can be effectively predicted.

Description

technical field [0001] The invention belongs to the field of computer technology, and in particular relates to a method for predicting failures of an aircraft fuel system in the maintenance field based on flight parameter data of a flight big data maintenance field autonomous support information support system. Background technique [0002] From the 1990s to the present, aviation equipment technology has developed rapidly, especially in the context of military strategy adjustments and changes in the combat use of aviation equipment, the requirements for aircraft ground support are getting higher and higher, and the support of aircraft fuel systems is among them. is one of the most fundamental factors. The rapid development of military technology has put forward higher requirements for the guarantee and failure prediction of flight fuel systems. But in the long-term development, the support technology of aircraft fuel system always lags behind the technology of other aerospa...

AI Technical Summary

Problems solved by technology

The original aircraft fuel system support system is facing huge challenges under the new equipment conditions, and if the support is not in place, the combat readiness rate of military aircraft will be greatly reduced

[0003] The health management of the aircraft fuel system lacks quantitative analysis, and the experience and data accumulated in the actual use and maintenance process cannot be well combined with the design data for analysis, resulting in a separation between theory and practice

There is no early warning mechanism when the aircraft fuel system fails, and it is difficult for the maintenance personnel of the maintenance field equipment to know the aircraft fuel system equipped. The predictability is insufficient, and the phenomenon of excessive maintenance and insufficient maintenance coexists, which leads to the unsatisfactory rate of the aircraft fuel system. people are satisfied

[0004] When the aircraft fuel system fails, the fault data at this stage is not structured, and it is difficult for the field maintenance personnel to conduct a clear fault diagnosis based on the comprehensive analysis of the fault phenomenon, reliability data, index data, etc., so it is difficult to find the most Optimal failure prediction method for aircraft fuel system replacement

This increases the maintenance cost of the aircraft fuel system, and at the same time, the faulty fuel system cannot be well maintained, resulting in a waste of resources;

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