Application of Acoustic Sensors for Helicopter Health Monitoring

The impending failure of a machine can be predicted by condition monitoring to detect precursors to failure. When a failure precursor is detected, actions to prevent or delay that failure can be taken. Acoustic Emission Sensors (AESs) have been successfully used in condition-monitoring applications. They are attractive because they can detect events that are significantly above the spectral range of accelerometers, and provide a unique capability for monitoring transient events such as crack propagation. During Phase I we plan to demonstrate automatic detection and classification of turbojet engine faults using a set of helicopter turbojet engine data gathered in 1993. This data is particularly attractive because it is from co-located AESs and accelerometers and spans a large number of engines in a variety of operating conditions. This fault detection and classification system will be developed on ORINCON's RIPPEN application, which provides a means of rapidly processing data through a variety of alternative processing chains. Using RIPPEN, we will develop and demonstrate a rapid prototype of the processing architecture for the onboard monitoring system. A system design that includes sensors, signal processors, a processing architecture, and displays for onboard monitoring of critical mechanical components will be produced.