Recently, laser scanners have been increasingly used for the evaluation of residual brick thickness of melt-ing furnaces. The choice of this optical technique is justified by the fact that it provides a complete picture of the vessel, increases the safety and reduces the time of maintenance.
In this study, a method for measurement of the lining residual thickness and volume of steelmaking furnace by using a 3D laser scanner and 3D surface reconstruction techniques was presented. To acquire the data, a SICK LMS511 laser rangefinder mounted on a developed mounting system and a rotary mechanism was used. Experi-mental models of a ladle furnace constructed from concrete blocks with deformations on the walls were scanned. Because of the hot environment in steelmaking plants, the effect of high temperature on the measurement was investigated on a lab-scale furnace, with temperature value up to $1100^\circ C$.
Since the acquired data is in the form of 3D point cloud, we developed several algorithms for point cloud processing. First, a segmentation algorithm based on the connectivity-graph of voxel clouds is proposed to extract the region of interest from the collected data. The comparison with the K-Nearest Neighborhood (KNN) search approach showed that the proposed method outperformed this later in terms of searching time. However, over segmentation occurred due to the non-isolated outlier clusters. These outliers pose a great challenge since they are difficult to be distinguished from valid scanned data points. Therefore, robust clustering and density based filters were proposed. Satisfactory results were obtained, and performance comparison with majority voting scheme was discussed.
The next stage, consisted of filtering out the noises by using an introduced bilateral filter based on density and surface variation. The developed smoothing algorithm proved its usefulness for further processing by signifi-cantly reducing the effect of noise. Next, we used a registration approach based on principle components analysis (PCA) and least squares fitting to align the scanned object with the mechanical model. Despite its simplicity, the used alignment approach has shown higher performance compared to the iterative closest point (ICP) approach. Finally, The residual thickness was calculated by a simple subtraction of the inner radius of the cylindrical shape from the outer one, and the residual volume of the worn out areas were accurately calculated based on the triple integration approach. The integration achieved an error less than 0.01% for synthetic shapes, and appropriate steps of integration, whereas, the accuracy depends on the quality of the acquired data for the scanned objects.