Supplementary data for the paper "Leak detection in water supply pipeline with small-size leakage using deep learning networks"

In recent years, there has been significant advancement in pipeline transportation technology. However, the progress of this technology is impeded by a critical challenge – the issue of leakage, particularly when it comes to small-scale leaks in water pipelines that manifest weaker signals of leakage. To address those challenges, we experimental investigate leak detection in pipelines with small leaks (leakage flow accounting for only 1.60% to 1.90% of the total volume flow) under low-pressure conditions (130~220 kPa). However, the paper on the data has not been published and this data can only be used after obtaining our consent. For this reason, we only present the typical data and results. If you need to use the data, please contact us, we will be happy to share with you and more detailed description of the data.