Abstract
Waterleakage detection and localization in distribution networks pipelines is a challenge for utility companies. For this purpose, thermal Infrared Radiation (IR) techniques have been widely applied in the literature. However, the classical analysis of IR images has not been robust in detecting and locating leakage, due to presence of thermal anomalies such as shadows. In this study, to improve the detection and location accuracy, a digital image processing tool based on multitemporal IR is proposed. In multitemporal IR analysis, the variation of soil's temperature due to field temperature can be obtained; and hence; estimating variations due to water leakage would be more accurate. An experimental setup was built to evaluate the proposed multitemporal IR water leak detection method. In order to consider the temporal temperature variation due to water leakage and mitigate the field temperature effects, a luminance transformation of the IRimages was introduced. To determine the temporal temperature variation of the soil's surface due to the leakage, several metrics have been considered such as the difference, the ratio, the log-ratio and the coefficient variation (CV) images. Based on the experimental results, the log-ratio and the CVimages were the most robust metrics. Then, based on log-ratio or the CV image, a temporal variation image (TVI) that traduces the temporal IR luminance variation was introduced. The analysis of the TVI image showed that the CV image is less noisy than the log-ratio image, and can more accurately locate the leakage. Finally, based on TVI histogram, a threshold was de ned to classify the TVI image into leakage/non-leakage areas. Results showed that the proposed method is capable of accurately detecting and locating water leakage, which is an improvement to the false detections of spatial thermal IR analysis.
