The Use of Probabilistic Reasoning to Improve Least Squares Based Gas Path Diagnostics

Abstract

A method is proposed to support least square type of methods for deriving health parameters from a small number of independent gas path measurements. The method derives statistical information using sets of solutions derived from a number of data records, to produce sets of candidate solutions with a lesser number of parameters. These sets can then be processed to derive an accurate component fault diagnosis. It could thus be classified as a new type of "concentrator" approach, which is shown to be more effective than previously existing schemes. The method's effectiveness is demonstrated by application to a number of typical jet engine component faults.