Measurement Method of Fuel Nozzle Cone Angle Based on Point Cloud Slicing

To address the issues of low efficiency and large errors in traditional dimensional measurement strategies for fuel nozzles, this paper proposes an improved region-constrained Random Sample Consensus (RANSAC) circle fitting method for high-precision measurement of the inner hole cone angle. Three-dimensional point clouds are extracted using a shape-from-focus method. The point cloud slices are then projected onto a two-dimensional plane, and the slice edges are extracted. Based on the edge shape distribution, the candidate point selection strategy of RANSAC is optimized: the initial circle is divided into eight sector regions, and three points are randomly selected from three distinct regions to fit candidate circles. After multiple iterations, the optimal fitting circle is obtained. A comparative analysis is conducted among the least squares method, standard RANSAC, and the proposed algorithm, with three quantitative metrics-residual standard deviation (σ), root mean square error (RMSE), and inlier ratio (ε)-introduced to evaluate the fitting quality. Experimental results show that the proposed region-constrained RC-RANSAC method achieves the best performance among the three, yielding σ = 2.826 px, RMSE = 2.826 px, and ε = 95.2%, and attains a cone angle deviation of only 1.0°, which closely agrees with Keyence ultra-depth measurements (error 0.8°). This method provides a new approach for accurate and robust cone angle measurement of fuel nozzle inner holes.