CONCEPTUAL AND STATISTICAL PROBLEMS AND APPROACHES IN GAS TURBINE ENGINE HEALTH MONITORING

摘要

Current approaches to gas turbine engine (GTE) health monitoring involve either (a) simpledetermination of whether individual GTE variables of interest (e.g., pressures temperatures, rotationalspeeds, vane angles) are exceeding or approaching predetermined limits, or (b) complex physics-basedcomputer simulation modeling of GTE aero / thermo / mechanical performance. Purely statisticalapproaches to GTE modeling and health monitoring tend to be viewed with skepticism by GTEengineers, but nevertheless are conceptually attractive based on the epistemological philosophy thatstatistical models let GTE data “speak for themselves” rather than superimposing approximations of“truth” on the data (in the sense that, e.g., the ideal gas law is an approximation to truth). However, theadoption of a purely statistical approach to GTE health monitoring has its own set of conceptual andmathematical problems. This paper discusses three of these problems in the context of GTE healthmonitoring: defining prognosis, dynamic hypothesis testing, and determining an overall probability ofabnormality for dynamic hypothesis test results for a given GTE.