Research on Concentricity Detection Method of Automobile Brake Piston Parts Based on Improved Canny Algorithm
Year: 2025
Type: article
Abstract: The automotive brake piston component is an important part of the automotive brake system, and the concentricity detection of the first piston component is crucial to ensure driving safety. In this paper, an improved Canny algorithm is proposed for non-contact detection of spring concentricity of the first piston component. Firstly, the traditional Canny algorithm is improved by replacing the Gaussian filter with a bilateral filter to fully retain the edge information, and accurate edge detection results are obtained by constructing a multi-scale analysis. After obtaining the edge images, a sub-pixel edge detection method with gray moments is introduced to optimize these edges; secondly, a circle is fitted to the extracted edge points by using the RANSAC algorithm to determine the center position and radius of the circle; and finally, the concentricity of the first piston part is calculated based on the fitting results. The experimental results are compared with those of the CMM and the traditional Canny algorithm, and the results show that the improved Canny algorithm reduces the coaxiality error by 4% and enables effective measurement of the concentricity of the first piston assembly spring.
Source: Applied Sciences
DOI: 10.3390/app15084397
Authors: Qinghua Li, Wanting Zhao, Siyuan Cheng, Yi Ji
Institution: Changchun University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4409484042