## 6 Conclusions  
Aimed at the problem of detecting the dimensional deviation of high-speed railway track slabs, this paper proposes a method for detecting the supporting block plane based on a 3D scanner. It is \begin{table}
\begin{tabular}{c c} \hline \hline
**Method** & **Value of Slope** \\ \hline Contact measurement & 1.321\({}^{\circ}\) (1:43.365) \\ The method in this paper & 1.342\({}^{\circ}\) (1:42.680) \\ Difference value & 0.021\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of the two methods. Figure 19: Flatness of repeated measurements. the first time that the three-dimensional scanner and robots have been applied to the detection of the high-speed railway track slab supporting block plane. Compared with traditional measurement method which takes 40 min to complete the detection of a track slab, this method not only guarantees the detection accuracy, but also improves the detection efficiency of track slab, and improves a plane extraction algorithm. We used the robot to carry a 3D scanner to detect the outer dimensions of the track slab and did a lot of experiments. We obtained the real point cloud data of the supporting block planes of track slab and processed the obtained point cloud data. Firstly, the point cloud data was denoised, and the data was spliced according to the physical space location, and then registered with the established model. Finally, the improved RANSAC algorithm was used to extract the point cloud data and analyze the final results. This method provides support for the subsequent automatic extraction of the index of the angle between the supporting block plane and the jaw surface, the slope of the supporting block plane, the features of the height of the convexity, etc. The summary is as follows:  
1. Compared with the traditional detection method, the detection method can obtain high-quality supporting block detection data, and there is no need to touch the finished slab during the detection process, so as to avoid collision between the detection equipment and its transmission equipment. The detection method is fast and reliable, it takes only 7 min to complete the detection of a track slab, which greatly improves the detection efficiency of the track slab. The requirement for the detection environment is reduced, and the investment of manpower is reduced;
2. The point cloud data obtained by the detection method used in this paper can truly reflect the actual situation of the surface of the detected supporting block. The proposed RANSAC algorithm which is robust can efficiently extract the point cloud data of the supporting block planes, and the extraction results are higher. Compared with the design value of the model, the dimensional deviation of the appearance of the track slab is obtained. The establishment of the standard model enhances the visual expression of the detect parameters of the track slab and realizes the control of the dimensional quality;
3. The manufacturing process of the CTRSIII track slab and its geometric dimensional accuracy determine that the inspection of the outer dimensions of the track slab belongs to the category of industrial measurement. The minimum allowable deviation of the detect indexes of the track slab dimensions is 0.500 mm. Several detection indicators related to the supporting block plane are detected respectively by the detection method proposed in this paper and the contact measurement. By comparing the measurement results of the two methods, it is concluded that the average error of the method proposed in this paper is less than 0.100 mm and the maximum error is less than 0.200 mm, which meets the accuracy requirements of CRTSIII track slab detection. The detection method has wide application prospects in the field of railway component detection. In future work, we will improve the detection method, add other sensors, and propose a multi-sensor integrated detection method. Conceptualization, X.C., F.Q. and X.Z. ; Methodology, X.C., C.X. and J.B.; Software, X.C. and J.B.; Validation, Y.H. and C.X.