Development of a Far-Field Noise Estimation Model for an Aircraft Auxiliary Power Unit

Aircraft Auxiliary Power Unit (APU) is one of the major aircraft systems and is reported to be a key driver of unscheduled maintenance. So far, the research has been focused on the implementation of the APU thermodynamic state data to isolate and diagnose faults. To advance the available diagnostic techniques, research work has been initiated to explore the potential of employing far-field microphone data for the identification and isolation of APU faults. This paper aims to address the first step required in the overall effort and proposes a novel methodology for the development of a noise model that can be used for evaluating noise as a source of fault diagnostics. The methodology integrates experimentally acquired full-scale aircraft state and noise data, a physics-based APU thermodynamic model, and semi-empirical noise models to estimate the noise produced by an aircraft APU based on a limited parameter-set. The methodology leads to a model which works by estimating the unknown thermodynamic parameters from the limited dataset and then passes on the relevant parameters to noise estimation models (combustion/jet noise models). An inherent part of the model is the effect of multipath propagation and ground reflections for which a relationship has been analytically derived that considers all the necessary parameters. The developed model has been validated against experimental noise and thermodynamic data acquired from a Boeing 737–400 aircraft APU under several different operating conditions. The acquired noise estimates suggest that the proposed approach provides an accurate estimation of the far-field noise under a wide range of APU operating conditions, both at the sub-system and APU level. The model would act as an enabler to simulate APU noise data under degraded functional states and subsequently developing fault diagnostic schemes based on the far-field noise data.