Abstract: This invention disclosed a full-space intelligent detection method and system for underground drainage networks, as well as storage media, including the following steps: image acquisition, intelligent image denoising, internal pipe defect segmentation, concealed defect detection around the pipe, 3D reconstruction with volume quantification, and pipeline life prediction. This invention introduced a bionic four-wheel-drive, all-terrain detection robot that can effectively navigate through mud and flowing water-challenges that hinder traditional detection devices. By leveraging deep learning algorithms as well as various techniques of computing vision, 3D reconstruction, and point cloud processing, the system thoroughly analyzed collected data to determine defect types and precise locations. Utilizing this analysis, precise location of different defect type and quantitative measurement of their dimensions can be realized.

Abstract: An intelligent decision-making method for maintaining urban underground sewer network includes steps of: analyzing with a sewer network functional defect three-dimensional instantaneous hydraulic model; calibrating parameters by finite element fitting analysis and full-scale test, and verifying accuracy of the sewer network functional defect three-dimensional instantaneous hydraulic model; combining node water level iteration method, Preissmann slit method, Godunov finite volume method and unstructured grid to rebuild a surface-subsurface one-two-dimensional coupled connection model; using R language, dynamic library linking technology, and long-short-term memory neural network method of multi-source data samples for engineering secondary development of the surface-subsurface one-two-dimensional coupled connection model, and obtaining urban sewer network functional defect conditions with waterlogging result labels; and establishing a multi-objective planning intelligent decision-making model for sewer network