Pipeline for continuous improvement of an hvac health monitoring system combining rules and anomaly detection

Abstract

A method, apparatus, and computer program product provide for improving performance of a condition monitoring system by combining rules and anomaly detection. In the context of a method, the method receives plurality of telemetry data from a monitored system. The method processes the plurality of telemetry data to generate an anomaly score set. The method also processes the plurality of telemetry data in accordance with the predefined rule data object set to generate a rule-based result set. The method determines whether the plurality of telemetry data is associated with an undetected fault of the monitored system and generates an extracted rule data object based on the telemetry data. The method also monitors performance of the machine learning anomaly detection model and determines whether retraining is necessary.