Gas Path Analysis as a Tool for the Predictive Maintenance of the Honeywell 331-500 Auxiliary Power Unit

Master thesis (2018)

Authors

K. Ward Mechanical Engineering

Contributors

S.A. Klein (supervisor 1)
Rene Pecnik (supervisor 1)
S.H.H.J. Smit (supervisor 1)
Faculty
Mechanical Engineering
Copyright: © 2018 Keith Ward
Predictive Maintenance Gas Turbines Gas Path Analysis
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Published Date

28-11-2018

Language

English

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Faculty

Mechanical Engineering

Abstract

This study examines Gas Path Analysis (GPA) as a method for the predictive maintenance of the Honeywell 331-500 Auxiliary Power Unit (APU). The 331-500 is used on the Boeing 777 and is susceptible to a sudden failure during operation due to the release of a first stage turbine blade. Investigations found the failure mechanisms of the blade release to be hot corrosion and thermal fatigue. Prolonged operation and the ingestion of environmental contaminants cause corrosion and a loss of material of the first stage Nozzle Guide Vane (NGV) which leads to a reduction in turbine performance. To counter this loss in performance, the APU controller increases the fuel flow, hence Turbine Inlet Temperature (TIT), which leads to under-platform crack growth of the first stage rotor and the eventual release of a blade.

A thermodynamic model of the 331-500 is created and validated using the Gas Turbine Simulation Program. Test cell data is used to characterise the APU at its design point before historical failure data comprising on-wing APU performance is analysed to assess the condition of the turbine. GPA, in the form of adaptive modelling, is used to adjust the turbine efficiency to match the model with the performance data thereby determining the deterioration of the machine.

Analysis highlights a relationship between the gradient of turbine efficiency, the ratio of the controller- to model-calculated TIT, and the condition of the first stage NGV. A larger gradient and TIT ratio indicate significant material loss in the NGV and that the turbine is heavily deteriorated. From the analysis, a rule functioning as a threshold on both the turbine efficiency gradient and the TIT ratio is formulated and is capable of predicting the historical first stage turbine blade failures up to 600-250 cycles before failure. This rule may then be used for the monitoring of current and future 331-500s in operation with the aim of preventing failure.