Design of a machine vision-based measurement system for automotive seat slide rail end face dimensions

https://elibrary.ru/UTMKQB

Abstract

Automotive seat slides are subjected to complex loads in vehicle use, and the dimensions need to be strictly measured at the factory. In this paper, we design a machine vision-based automotive seat rail end surface size inspection system, which can automatically and non-contact measurement of the rail end surface size. The image is collected by building a hardware platform, and after gray scale conversion, filtering, sharpening and emphasize algorithm enhancement, the edge to be measured is extracted by Canny algorithm, and then the arc is obtained by least squares fitting and the radius is measured. Halcon United VS software was used to design the human-computer interaction interface to realize one-button measurement. Experiments show that the running speed of a single picture is stable at 3s, the maximum measurement error is 0.02mm and the minimum is 0.01mm, the maximum repeatability is 0.04mm and the minimum is 0.03mm, which realizes accurate and efficient non-contact measurement, meets the measurement demand, and provides a new dimension detection method for the automobile manufacturing industry.