Automatic fault diagnosis algorithm for hot water pipes based on infrared thermal images

In recent years, scholars have completed many studies on the fault diagnosis of air-conditioning systems based on Building Energy Management System (BEMS) data, but these studies seldom cover the leakage of water pipes and the damage of insulation layer, that are common but undetected by BEMS. To fill in the gaps, an automatic diagnosis algorithm based on infrared thermal images is proposed here to detect fault occurs on insulated heating pipes. This method can automatically diagnosis of pipeline leakage and insulation damage, so as to prevent pipeline corrosion and heat loss. The algorithm includes two sections: an image segmentation processor and a fault diagnosis module. The fault diagnosis module can detect three categories of faults: insulation damaged, insulation fall-off, and pipeline leakage. Experimental study demonstrates that the overall accuracy of the algorithm is 97.59%, while filed studies in commercial buildings exhibits an accuracy of 92.74%. These data prove the algorithm's feasibility in practice and the method can be applied with an infrared camera installed on an inspection robot or at a fixed location in a machine room. Although images of hot water pipes are used as inputs of the research, this method is also applicable to cold water pipes by modifying relevant parameters.

Automated summary

In recent years, scholars have conducted studies on fault diagnosis of air-conditioning systems based on BEMS data, but seldom focused on issues like water pipe leakage and insulation damage. To address this gap, a new automatic diagnosis algorithm based on infrared thermal images is proposed, enabling effective detection and prevention of faults.