Abstract
An automated predictive algorithm has been designed to predict PC fan issues and failures before they occur. The solution leverages fan & thermal telemetry data along with detected fan errors to develop several predictive models for multiple thermal failure modes. Examples of machine learning techniques used include regression and anomaly detection. The final predictive algorithm is used to notify users of fan failures in advance, so that maintenance can occur before issues arise. The solution consists of three main steps, 1) correlate thermal PC telemetry data with fan error data, 2) design fan error predictive models for each error type, 3) develop final predictive algorithm for notifying users.
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Recommended Citation
INC, HP, "Fan Failure Prediction Using PC Telemetry Data", Technical Disclosure Commons, (July 23, 2024)
https://www.tdcommons.org/dpubs_series/7224