In the era of Industry 4.0 , the production of market-oriented parts is becoming increasingly precise, while labor costs are constantly rising, and the efficiency and stability of manual labor are not high, resulting in a high rate of false detections and missed detections.
In the current market, a machine vision-based inspection method has been introduced. The inspection principle is to take pictures with a CCD camera and then perform image analysis with software. This method is efficient, fast, and non-contact.
For example, screws and nuts have extremely strict quality requirements, and the usage of screws and nuts is generally very large, usually produced in large quantities. In this case, manual inspection is completely insufficient, so optical imaging inspection equipment can only be used for quality inspection.
The implementation process is as follows:
1. Image acquisition, image preprocessing, contour matching, position correction, thread detection data judgment, and numerical display. As shown in the image below, our self-developed software can easily detect that the screw has 5 turns.
In summary, visual inspection generally involves image input, image localization, inspection tools, and output results. In this case, the image localization tool was contour matching and position correction, the inspection tool was thread detection, and the result displayed the number of thread turns.
In the process of application, it is necessary to make flexible use of the combination of various tools in order to achieve a thorough understanding and become proficient through practice.
Features of screw and nut appearance inspection equipment:
1. Detection efficiency can reach 300-1200 samples / minute.
2. The detection accuracy can reach up to ± 0.02mm.
3. Detection accuracy can reach 99.9%.
4. Automatic feeding and unloading, no manual operation required.
Appearance inspection equipment is specifically designed to inspect the appearance of products. This includes checking for defects such as dimensional flaws, scratches, burrs, stains, and deformations.
In today's industrial manufacturing, due to limitations in science and technology, manual inspection is still the primary method for detecting defects on the surface of products. This method, due to limitations in manpower and outdated technology, is not only slow and inefficient in terms of inspection speed, but is also prone to errors during the inspection process, resulting in unqualified inspection results.
With the development of computer technology, surface defect detection technology based on machine vision has emerged. This technology greatly improves production efficiency, avoids the impact of working conditions and subjective judgment on the accuracy of detection results, and enables better and more precise surface defect detection, allowing for faster identification of product surface flaws.
The application of machine vision technology is primarily aimed at improving production efficiency and reducing labor costs. Therefore, certain manual processes in industrial production and management are gradually being replaced by robots.
