The visual appearance inspection of equipment can realize the efficient detection and monitoring of the appearance quality of the motor, improve product quality and production efficiency, and reduce human error and resource waste.

The appearance inspection of the motor is very important in the manufacturing process, and the machine vision technology can improve the inspection efficiency and accuracy.

Capture images of the motor appearance using high-resolution industrial cameras or sensors to ensure clear image quality. The acquired images are preprocessed, including denoising, gray adjustment, edge enhancement, etc., to reduce interference and highlight features.

Extract the key features in the motor appearance image, such as color, shape, texture, etc., defect detection and classification. Machine learning algorithms (such as deep learning models) are used to detect defects in motor appearance images and identify problems such as surface defects, blemishes or foreign bodies.

The detected defect area is classified and judged to determine whether it meets the quality standard, and further treatment or alarm. Integrate machine vision system with production line to realize automated production and inspection; At the same time, according to the test results, adjust the production parameters or alarm processing.

Monitor the motor appearance inspection process in real time, record the test results, defect type and location, etc., for subsequent analysis and improvement. Design a user-friendly interface that allows operators to view test results in real time and intervene to deal with anomalies in a timely manner.