Application of image processing technology based on field programmable gate array in mechanical part inspection - Lv, Yi (Frontiers in Mechanical Engineering, 2024)
In the field of industrial manufacturing, the accurate detection of mechanical gears and bearings is essential. The traditional testing methods of mechanical parts are often interfered by human factors, which leads to the instability, low efficiency and large error of the test results. In order to overcome these problems, this research focuses on the development of a novel edge detection model for mechanical parts using image processing technology of field programmable gate arrays. This model uses adaptive threshold multi-direction edge detection technology to detect the edge features of mechanical gears and bearings with high precision. After performance verification, the running time of this technology is 11 seconds, and the detection error is controlled within 9%, which is better than the comparison experimental group. Further analysis shows that the detection accuracy of this model is as high as 0.9004, and its internal resource occupancy rate and detection accuracy rate are 88% and 91%, respectively, which are higher than the comparison model. In summary, the proposed testing model not only improves the efficiency and accuracy of testing, but also meets the strict requirements of industrial real-time, which is expected to bring significant contributions to the field of automatic testing of mechanical parts.