Roundness error evaluation in image domain based on an improved bee colony algorithm

The roundness error is the main geometric characteristic parameter of shaft and hole parts. Evaluation accuracy is an important indicator of the quality inspection technology. Existing roundness error evaluation methods are insufficient in terms of the calculation amount, convergence speed, and calculation accuracy. This study proposes a novel roundness error evaluation method based on improved bee colony algorithm to evaluate the roundness error of shaft and hole parts. Population initialization and search mechanism were considered for the optimal design to improve the convergence precision of the algorithm. The population was initialized in the local search domain defined by the contour data. The roughness error was obtained by the convergence solution of the circle center calculated iteratively by the step-decreasing method. The roundness error was also evaluated by taking the same set of image domain data as an example to verify the feasibility of the proposed method. The algorithm exhibited higher accuracy than that traditional methods and thus can be widely used to evaluate the roundness error of shaft and hole parts.