Systems and methods for diagnosing the cause of trend shifts in performance data

An automated method for diagnosing the cause of a trend shift in performance data associated with an aircraft engine system, the method comprising:

• selecting a fuzzy model describing how the mean associated with a parameter shifts when a predetermined problem occurs;
• achieving a diagnosis using the fuzzy model;
• providing a plurality of validation cases associated with the aircraft engine system;
• validating the fuzzy model using the plurality of validation cases;
• providing an evaluation function;
• and
• using the evaluation function to determine how well the fuzzy model differentiates the diagnosis from a plurality of incorrect diagnoses for the plurality of validation cases.

An automated system for diagnosing the cause of a trend shift in performance data associated with a system, the diagnostic system comprising:

• a fuzzy model describing how the mean associated with a parameter shifts when a predetermined problem occurs;
• means for receiving performance data associated with the system;
• a first algorithm operable for applying a preferred set of piecewise regressions;
• a second algorithm operable for selecting a start date;
• a third algorithm operable for selecting data sets near the start date and an end date that have a predetermined size without violating normal scatter;
• a fourth algorithm operable for measuring the mean shift between a plurality of samples using one or more statistical tests;
• and
• means for combining the results with the fuzzy model to achieve a diagnosis.

An automated system for diagnosing the cause of a trend shift in performance data associated with an aircraft engine system, the diagnostic system comprising:

• a fuzzy model describing how the mean associated with a parameter shifts when a predetermined problem occurs;
• means for achieving a diagnosis using the fuzzy model;
• means for receiving a plurality of validation cases associated with the aircraft engine system;
• means for validating the fuzzy model using the plurality of validation cases;
• and
• an evaluation function, wherein the evaluation function is used to determine how well the fuzzy model differentiates the diagnosis from a plurality of incorrect diagnoses for the plurality of validation cases.