Comprehensive Failure Diagnosis Model with Degradation Indicators of Multiple Sensors

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Published Sep 4, 2023
Jun Tominaga Shoya Kamiaka Kohei Kuroda

Abstract

Although monitoring system can detect abnormality of sensor reading in air-conditioning equipment, the root cause of the abnormality may not be sensor failure but other failures such as gas shortage. We propose new method that estimates the cause by the following steps. Firstly, regression model predicts the normal readings of multiple sensors (e.g., thermistor) for a given operational condition. Secondly, the gap between measured and predicted values is calculated for each parameter as a degradation indicator. Finally, our failure diagnosis model estimates the cause by considering degradation indicators of multiple sensors. Our evaluation verifies the effectiveness of our method.  

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Keywords

Diagnostics, Prognostic, Machine learning, Degradation model, Air-conditioning equipment

References
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Section
Regular Session Papers