Aircraft maintenance outfield aircraft engine fault prediction method based on flight parameter data, terminal and readable storage medium

Abstract

The invention provides an aircraft maintenance outfield aircraft engine fault prediction method based on flight parameter data, a terminal and a readable storage medium. The aircraft maintenance outfield aircraft engine fault prediction method comprises the steps of acquiring a time sequence data set composed of N aircraft parameters sensitive to faults in an aircraft engine; constructing a long-short-term neural network model according to the time sequence data set, and obtaining an actual prediction result of the time sequence data set according to the long-short-term neural network model;determining a fault discrimination model f (x) according to the time sequence data set; obtaining a real data set of part of known aircraft engine fault conditions, and determining a fault threshold value according to the fault discrimination model f (x) and the real data set; and determining probability density of an actual prediction result according to the fault judgment model, and comparing the probability density of the actual prediction result with a fault threshold to judge the health condition of the aircraft engine. According to the method, fault prediction is carried out on the aircraft engine in a mode of combining the long and short term neural network model and the fault discrimination model f (x), and the health condition of the aircraft engine can be effectively predicted.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method for predicting aircraft engine failure in the field of maintenance field based on flight parameter data, a terminal and a readable storage medium of a military 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 the adjustment of military strategy 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 engines is one of the the most fundamental factor. The rapid development of military technology has put forward higher requirements for the guarantee and failure prediction of flight engines. However, in the long-term development, the support technology of aircraft engines always lags behind the techno...

AI Technical Summary

Problems solved by technology

The original aircraft engine 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 aircraft engines lacks quantitative analysis, and the experience and data accumulated in the actual use and maintenance process have not been well combined with the design data, resulting in a separation between theory and practice

There is no early warning mechanism when an aircraft engine fails, and it is difficult for the maintenance personnel of the maintenance field equipment to know the aircraft engine equipped. The predictability is insufficient, and the phenomenon of excessive maintenance and insufficient maintenance coexists, resulting in a decline in the integrity rate of the aircraft engine.

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

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

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