Modelling Method for Maintenance Decision-Making in Civil Aero Engines Based on Multiple State Parameters

Huiling Cao,Jiahe Miao,Zemin Wu,Bing Xu,Yinong Chen

doi:10.1051/matecconf/201713900013

Huiling Cao, Jiahe Miao + Show 3 more

Open Access

https://doi.org/10.1051/matecconf/201713900013

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Abstract

For airlines, a scientific and effective method for engine maintenance decision-making should be developed for the planning of aero engine maintenance and removal. The mathematical modelling method of maintenance decision-making for civil aero engines based on the currently widely used condition-based maintenance (CBM) strategy was mainly studied in this work, and the effects of multiple state parameters on the system operation were fully considered. Based on historical data for aero engine removal due to performance degradation, statistical regression modelling was used to establish a mathematical model of maintenance decision-making that can reflect a functional relationship between the engine state parameters and the time on wing. The model was based on the proportional hazards-proportional odds (PH-PO) model, combining two commonly used statistical regression models, the proportional hazards model (PHM) and the proportional odds model (POM), into a single new model form; as a result, the scope of application of the model was improved. Finally, the results of a case study of a specific example showed the high practical value of this method.

Highlights

With the increasing growth of airline fleet sizes, engine maintenance decision-making is becoming increasing complex
The widely applied condition-based maintenance (CBM) decision-making method was used to conduct a simple trend analysis of performance degradation for a single performance parameter, such as the exhaust gas temperature margin (EGTM), and a pre-set monitoring threshold was used to determine whether the engine needed to be repaired
A dot at the bottom of the curve indicates that the system between covariates and life on wing, the selected parameters are △△EGT, EGTM, curve, the system’s performance is seriously degraded △△FF, △△N1 and the engine must be repaired [8]

Summary

Introduction

With the increasing growth of airline fleet sizes, engine maintenance decision-making is becoming increasing complex. The widely applied CBM decision-making method was used to conduct a simple trend analysis of performance degradation for a single performance parameter, such as the exhaust gas temperature margin (EGTM), and a pre-set monitoring threshold was used to determine whether the engine needed to be repaired. While this method is simple, it provides a relatively rough estimate and has some difficulty in reflecting the comprehensive effect of multiple influential factors. Regarding the system reliability as a control objective, the maintenance decision-making model of the engine can be obtained and used to determine whether maintenance should be conducted based on the current state of the engine

Typical statistical regression models

Modelling considerations

Covariate processing q

Maximum likelihood estimation of parameters

Conclusion