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Since 1986, the U.S. Army has been evaluating a digital data recording system known as a Portable Engine Analyzer Test Set (PEATS) for the detection, diagnosis and prognosis of faults on turbine engines installed in helicopters. On-board use of digital data systems makes test cell quality instrumentation available for testing installed engines. Electronic data recording and transfer of accurate performance information into a personal computer allows the use of Artificial Intelligence methods to form and interpret the significance of the data. The resulting information is being successfully used to provide previously unobtainable diagnostic capabilities for maintenance decisions. Standardized engine testing and formatting of data helps low experience technicians see the relative internal condition of a gas turbine engine at a glance.

The purpose of this paper is to share how the quantity and quality of data available For propulsion system management greatly increases with the use of digital technology engine monitoring hardware. A previously unobtainable data base for maintenance decisions is available from the use of diagnostic monitoring systems. Artificial intelligence methods are being successfully used to provide improved data presentation and interpretation. The computational capability of the digital technology allows reduction of in-flight data into referred diagnostic values from deviations in engine performance. Although referred diagnostic data may not detect all potential engine problems, this available capability, with its artificial intelligence, has demonstrated the ability to identify hidden problems, which greatly enhances propulsion system management.