KEYWORDS: Pipes, Calibration, Data modeling, 3D modeling, Data processing, Geographic information systems, Network security, Analytical research, Mathematical modeling, Roads
To solve the problem that manual calibration is time-consuming and laborious when some nodes of pipeline data are not marked, this paper proposes an intelligent calibration method of pipeline segment and pipeline point data based on the "node-edge" relationship of the network. Combining with ArcGIS, Python and other tools, it employs the broken line at the cross point and the break point to intelligently generate important unmarked nodes in the original network, which can avoid manual inspection of pipeline segment by segment, diagnose and correct the error data in the original data during marking the starting and ending points of the pipeline. A project case study is employed to verify the efficiency and feasibility of the method, in which the processed pipeline data provides basic data support for the two-dimensional (2D) and three-dimensional(3D) modeling and system construction of the pipeline, improves the accuracy of data processing and the efficiency of the pipeline data calibration.
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