In the era of Industry 4.0, the production of parts for the market is becoming more and more precise, and the cost of personnel is increasing, the labor efficiency and stability are not high, and the ratio of false detections and missed detections is high.
In the current market, a detection method based on machine vision is introduced. The detection principle is to take a picture through a CCD camera and perform image analysis by software. This method is efficient, high-speed, and non-contact detection.
For example, screw nuts are extremely strict with quality requirements, and the use of screw nuts is generally very large, generally mass production. At this time, the appearance inspection can not be completely handled by manual, so only optical image inspection equipment can be used. To conduct quality testing.
The implementation process is as follows:
- Acquire images → image preprocessing → contour matching → position correction → thread detection → data judgment → numerical display. As shown in the figure below, using our self-developed software, we can easily detect that the number of screw turns is 5 turns.
Summary: In visual inspection, the process of processing generally includes image input, image positioning, inspection tools, and output results. In this case, the tool for image positioning is contour matching and position correction, and the detection tool is thread detection, and the result is the number of turns of the thread.
In the process of application, it is necessary to flexibly use the combination of various tools to achieve integration and practice, and practice makes perfect.
Features of screw and nut appearance testing equipment:
1. Detection efficiency can reach 300-1200 pcs / min
2. The detection accuracy is up to ± 0.02mm
3. The detection accuracy can reach 99.9%
4. Automatic loading and unloading without manual operation.
Appearance testing equipment is equipment that specifically detects the appearance of products. For example, product size, flaws, defects, scratches, burrs, stains, deformation, etc.
In today’s industrial manufacturing, due to the limitations of science and technology, manual detection methods are still mainly used to detect defects on the surface of products. This method is not only slow and inefficient in detecting products due to manual limitations and backward technology, but also It is easy to make mistakes in the process, which leads to the failure of the test results.
With the development of computer technology; surface defect detection technology based on machine vision technology has appeared. The emergence of this technology greatly improves the efficiency of production operations, avoids affecting the accuracy of the test results due to operating conditions, subjective judgments, etc., and enables better and more accurate surface defect detection and faster identification of product surface defects. .
The application of machine vision technology is more to improve production efficiency and reduce labor costs. Therefore, some artificial links in industrial production and management are gradually being replaced by robots.