This study proposes a domain adaption method for pipe burst location based on deep learning. Multi-scale feature extractors are designed to extract pipe burst features, then three classifiers are trained by pipe burst features with different scales, and adversarial training is introduced during the edge domain fusion. Finally, the probability ranking of each pipeline is obtained according to the classification results of the three classifiers. In this study, a Net3 pipe network hydraulic model was used as an example to carry out related research. The pressure monitoring data of three sensors w...
