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A multivariate statistical approach for improved automated process control and anomaly detection in mechanical systems

This paper describes an approach for applying multivariate statistical process control techniques to improve and automate anomaly detection in mechanical systems. Implementation examples include turbocharger performance, wind turbine generator failures, transient analysis of aircraft jet engine operation, air compressor performance monitoring, and other projects where the technique has been successfully applied to detect operational anomalies in mechanical systems.