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| The Slope Fitting Method of Sonar Point Cloud on the Inner Wall of Sewer Based on Density Algorithm and Tangent Slope Fitting of the Circle |
| WU Jun-hao,LI Chen,WANG Rong,LIU Wen-li,ZHOU Xing-yu |
| School of Civil Engineering & Mechanics, Huazhong University of Science & Technology, Wuhan, Hubei 430074, China |
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Abstract To solve the problem that the scan results of the ring scan sonar are affected by the sound of mixed water in the drainage pipe, a method for denoising the point cloud data of the sonar scan is proposed. On the basis of the three-dimensional point cloud data obtained by the ring scan sonar, the density clustering optimization algorithm (DBSCAN) is used to remove the noise in the point cloud data. Then, the method of fitting the slope of the outer tangent of the circle is used to identify the boundary of the inner wall of the pipeline and the silt deposition line, and finally obtain a model including the boundary of the inner wall of the drainage pipe and the characteristics of the silt line. To verify the effectiveness, a drainage pipeline in Wuhan is taken as an example for analysis, and performs data denoising and feature extraction based on 980000 point cloud coordinates collected on site. The results show that after the initial screening of the point cloud data using the density clustering optimization algorithm, the SFA-COT can effectively identify the inner wall boundary and the siltation line of the drainage pipe. The mean square error of the fitting radius is 0.0071m, which has higher fitting accuracy and better denoising effect than the single density clustering algorithm.
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Received: 18 November 2021
Published: 21 February 2023
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2023, Vol. 44 
