Estimating Instrumentation Data Acquired During Flight Test of a Helicopter using Predictor Models

Abstract

In this paper, we propose a hybrid system consisting of decision trees and neural networks to calculate the measurement faults of sensor readings and to predict the actual values in a flight test of a helicopter in production. We present the architecture of the models, and extensive test results.