Blade multi-view-field point cloud registration method based on overlapping features and local distance constraint

Abstract

The invention discloses a blade multi-view-field point cloud registration method based on overlapping features and local distance constraints, and the method comprises the steps: step 100, obtaining the multi-view-field point cloud data of a blade, solving an overlapping region of the point cloud data between two adjacent view fields, and constructing a data set X and a data set Y; step 200, establishing an overlapping feature constraint matrix FMN; step 300, establishing a local distance constraint matrix DMN; step 400, on the basis of the Hadamard product of the matrix, a member probability matrix PMN between the data set X and the data set Y is constructed through an overlapping feature constraint matrix FMN and a local distance constraint matrix DMN, PMN = FMNDMN, and PMN is the Hadamard product; and step 500, calculating a rotation matrix and a translation matrix between the data set X and the data set Y based on an EM algorithm, and splicing a complete blade section contour through the calculated rotation matrix and the translation matrix. The invention provides a blade multi-view-field point cloud data registration method which does not depend on the motion precision of a detection system so as to achieve the purpose of improving the blade detection precision and reliability.

Description

technical field [0001] The invention belongs to the field of blade detection, and in particular relates to a blade multi-field point cloud registration method based on overlapping features and local distance constraints. Background technique [0002] The blade is the core component of an aero-engine, and its surface accuracy will directly affect the energy conversion efficiency and working reliability of the whole machine. Therefore, accurate detection of the blade profile has always been a key link in the blade manufacturing process. In recent years, due to its good efficiency and flexibility, the blade detection method based on optical measurement has received extensive attention. [0003] At present, the registration accuracy of multi-field point clouds mainly depends on the geometric accuracy and operational reliability of the built detection system. The Chinese invention patent with the patent number of 202011134900.7 discloses a method of calibrating the center of ro...

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Problems solved by technology

The Chinese invention patent with the patent number of 202011134900.7 discloses a method of calibrating the center of rotation based on the local leading edge curve characteristics of the blade. This method directly uses the motion parameters of the detection platform and can effectively complete the registration of multi-field point cloud data, but The registration result is easily affected by many factors such as the geometric accuracy and motion reliability of the detection system. After all, there will be certain mechanical errors in the motion parameters of the detection platform, resulting in poor reliability of the final blade detection; figure 1 In a and b, two adjacent splicing results are intercepted from the result of registering multi-field point cloud data using this method. It can be seen that the overlapping areas between the adjacent fields of view are not completely consistent, and the density is uneven ( figure 1 Point cloud data within the dotted line in a) problem

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