Integrated Multivariate Health Monitoring System for Helicopters Main Rotor Drives: Development and Validation with In-Service Data

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Alberto Bellazzi Giovanni Jacazio Bruno Maino Gueorgui Mihaylov Franco Pellerey Massimo Sorli

Abstract

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

Bellazzi, A. ., Jacazio, G., Maino, B. ., Mihaylov, G. ., Pellerey, F. ., & Sorli, M. . (2014). Integrated Multivariate Health Monitoring System for Helicopters Main Rotor Drives: Development and Validation with In-Service Data. Annual Conference of the PHM Society, 6(1). https://doi.org/10.36001/phmconf.2014.v6i1.2440
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Keywords

Multivariate statistics, Anomaly detection, Gear drives, Helicopters

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Section
Technical Papers