A Machine Vision-Based Measurement Method for the Concentricity of Automotive Brake Piston Components

Abstract The stability and reliability of the brake system are critically affected by the concentricity error of automotive brake piston components. Traditional contact-based concentricity measurement methods are inefficient. To address the issue of low detection efficiency, a non-contact concentricity measurement method based on the combination of machine vision and image processing technology is proposed in this paper. In this method, an industrial camera is utilized to capture images of the measured part's end face from the top of the spring. Edge contours are extracted through image preprocessing algorithms, the outer circle center is calculated, and the inner circle center is fitted. Finally, the concentricity error is calculated using the coordinates of the two circle centers. Experimental results show that, compared to a coordinate measuring machine(CMM), this method has a maximum error of only 0.0393mm and an average measurement time of just 3.9s. It significantly improves measurement efficiency and meets the industry's demand for automated inspection. The experiments verified the feasibility and effectiveness of this method in practical engineering applications, providing reliable technical support for the online inspection of automotive brake piston components. Additionally, this method can be applied to the concentricity measurement of other complex stepped shaft parts.