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Engine module performance trending and engine system anomaly detection and identification are core capabilities for any engine Condition Based Maintenance system. The genesis of on-condition monitoring can be traced back nearly 4 decades, and a methodology known as Gas Path Analysis (GPA) has played a pivotal role in its evolution. GPA is a general method that assesses and quantifies changes in the underlying performance of the major modules of the engine (compressors and turbines) which directly affect performance changes of interest such as fuel consumption, power availability, compressor surge margins, and the like. This approach has the added benefit in that it enables anomaly detection and identification of many engine system accessory faults (e.g., variable stator vanes, handling and customer bleeds, sensor biases and drift). Legacy GPA has been confined to off-board analysis of snapshot data averaged over a stable flight conditions when the engine is in steady state operation.

The basic concepts and mathematics of a methodology that allows successful relative assessment of simultaneously occurring multiple faults in gas turbine engine modules and sensors, are presented in detail. Included are a detailed exposition of a thermodynamic/differential equation based model of a representative type of gas turbine engine; discussion of correction methods to minimize data scatter; the mathematical design aspects of a demonstratedly successful approach to data filtering to deal with residual scatter caused by large or small sensor errors, data correction errors, or engine system modelling errors.