Surface defect detection method and device for injection molding part, equipment and storage medium

Abstract

The invention provides a surface defect detection method and device for an injection molding part, equipment and a storage medium, and relates to the technical field of computer vision. The method comprises the following steps: acquiring a product picture of an injection molding part; carrying out first preprocessing on the product picture to obtain a to-be-detected picture; and detecting the obtained to-be-detected picture by adopting a pre-trained detection model to obtain a detection result about whether the surface of the injection molding part has defects or not. According to the technical scheme, the computer vision and the neural network are combined in advance to train the detection model, and the detection model is adopted to detect the to-be-detected picture, so that whether defects exist on the surface of the injection molding part or not is quickly and accurately detected. The problem of detection errors caused by external factors such as emotion changes of detection personnel in current manual visual inspection solved, and the problems that a traditional solution is low in compatibility and cannot quickly adapt to new requirements are solved. The enterprise training and management cost is reduced, and the problem that defective goods flow into the market to cause loss to enterprises is effectively avoided.

Description

technical field [0001] The present application relates to the technical field of computer vision, and in particular to a method, device, equipment and storage medium for detecting surface defects of injection molded parts. Background technique [0002] All kinds of injection molding products produced by injection molding machines are collectively called injection molded parts. In the production process of injection molded parts, surface defects, such as lack of material (missing edge) often occur due to reasons such as raw material selection, temperature setting, process design, and human error. small pieces), dents, scratches, flow marks (ripples on the surface), etc. [0003] At present, most enterprises use manual visual inspection to find defects on the surface of injection molded parts, but manual visual inspection often produces deviations due to the influence of employees' seriousness, mood, fatigue and other factors, resulting in missed and false detections situatio...

AI Technical Summary

Problems solved by technology

[0003] At present, most enterprises use manual visual inspection to find defects on the surface of injection molded parts, but manual visual inspection often produces deviations due to the influence of employees' seriousness, mood, fatigue and other factors, resulting in missed and false detections situation occurs

Some enterprises have begun to try to find defects on the surface of injection molded parts by using industrial cameras to take pictures and measure specific defect indicators in the image, such as the length of scratches, the area of ​​notches, and the color of the surface; however, in this method, when the When the position of the injection molded part on the production line deviates, or the external light changes, the measurement results will also change accordingly; at the same time, when a new defect finding requirement arises, the staff needs to redesign the detection plan for the new defect, and Repeated measurement experiments are time-consuming and labor-intensive

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