The implementation into service of accelerometric health monitoring systems of mechanical power drives on helicopters has shown that the generation of false failure alarms is a critical issue. The paper presents a combined application of several multivariate statistical techniques and shows how a monitoring method which integrates these tools can be successfully exploited in order to improve the reliability of the diagnos- tic systems. The first phase of the research activity was ad- dressed to exploring the potential advantages of using multi- variate classification/discrimination/anomaly detection methods on real world accelerometric condition monitoring data. The second phase consisted of an implementation into actual service of an innovative integrated multivariate health monitoring system.
How to Cite
Multivariate statistics, Anomaly detection, Gear drives, Helicopters
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