Health assessment method of aircraft engine, computer equipment and storage medium

Abstract

The invention relates to a health assessment method of an aircraft engine, computer equipment and a storage medium. The method comprises the steps of obtaining a data set of a to-be-evaluated aircraftengine, wherein the data set comprises multiple engine parameters of multiple sorts of the to-be-evaluated aircraft engine; carrying out anomaly detection by utilizing the data set to obtain an abnormal data set; performing association analysis on the abnormal data set to obtain an abnormal parameter association rule of the to-be-evaluated engine and confidence coefficient information corresponding to the abnormal parameter association rule; and substituting the abnormal parameter association rule and the confidence information into a health scoring function to obtain a health state value ofthe to-be-evaluated aircraft engine. Data anomaly detection and correlation analysis can be combined, the accuracy of predicting aircraft engine health assessment is improved, predictability is achieved, and the phenomena of insufficient overhaul and resource waste caused by excessive overhaul are effectively avoided.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to an aircraft engine health assessment method, computer equipment and storage media. Background technique [0002] With the rapid development of aviation equipment technology, the demand for ground support and fault prediction of aviation equipment is increasing. At present, the common ground support technology lags behind other aviation equipment technologies. For example, the health score of the flight engine is the basis for judging the health status of the engine. It affects the combat efficiency and maintenance support efficiency of military aircraft. It can be seen that providing accurate health information for aircraft engines Scoring is also an urgent technical problem in the field of ground support [0003] At present, the health management of existing aircraft engines lacks quantitative analysis, and the experience and data accumulated in the actual use...

AI Technical Summary

Problems solved by technology

[0003] At present, the health management of existing 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.

On the one hand, there is no early warning mechanism when the aircraft engine fails, and the maintenance personnel of the maintenance field equipment have insufficient predictability for the equipped aircraft engine, and the coexistence of excessive and insufficient inspections leads to a decline in the integrity rate of the aircraft engine

On the other hand, 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 the comprehensive analysis of fault phenomena, reliability data, and index data. It is difficult to find the optimal fault prediction method to replace the aircraft engine; 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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