Application of machine vision in automatic flaw detection of large workpieces

Abstract: The application information of machine vision in automatic flaw detection of large workpieces is provided by excellent flowmeter and flowmeter manufacturers. 1 Introduction Machine vision is to use machines instead of human eyes to do measurement and judgment. Machine vision system refers to the software and hardware equipment that converts the ingested target into image signals through machine vision products, and then transmits it to a special information processing device for further processing. Depend on. For more flowmeter manufacturers to select models and price quotations, you are welcome to inquire. The following is the application article details of machine vision in automatic flaw detection of large workpieces. 1 Introduction Machine vision is to use machines instead of human eyes to measure and judge. Machine vision system refers to the software and hardware equipment that converts the ingested target into image signals through machine vision products, and then transmits it to a special information processing device for further processing. Because machine vision systems can quickly acquire a large amount of information, and are easy to process automatically and integrate with process control information, machine vision systems are widely used in working condition monitoring, finished product inspection and quality control in modern automated production processes. and other fields. The characteristics of machine vision system are automatic, objective, non-contact and high precision, which can easily improve the flexibility and automation of production. In some dangerous working environments that are not suitable for manual work or where artificial vision is difficult to meet the requirements, machine vision is often used to replace artificial vision; in the process of large-scale industrial production, using artificial vision to check product quality is inefficient and accurate. Using machine vision inspection methods can greatly improve production efficiency and production automation. Because machine vision is easy to realize information integration, it is one of the basic technologies to realize computer integrated manufacturing. In conclusion, with the maturity and development of machine vision technology itself, it can be expected that it will be more and more widely used in modern and future manufacturing enterprises. As we all know, industrial CT technology, as an advanced non-destructive testing technology, can not only be used for non-destructive testing, quality assessment, qualitative analysis and judgment of the internal structure and defects of workpieces, but also can realize the internal structure of workpieces by measuring industrial CT images. The size and defect size are measured and quantitatively analyzed, with high measurement accuracy and good repeatability. In recent years, the development from qualitative detection to quantitative measurement is an important research direction of industrial CT technology, and great progress has been made. However, at present, most of the measurement of industrial CT images at home and abroad still relies on manual methods, not only the repeatability of measurement is poor, but also the measurement accuracy is not high, and it is more and more difficult to meet the needs of large-scale image processing work. Therefore, combined with engineering practice, this paper discusses some problems existing in manual measurement, and discusses the automatic measurement method of industrial CT images. According to the characteristics of industrial CT images, an automatic measurement method based on edge extraction is proposed. 2Canny's edge detection principle Introduction The tomographic images of large metal workpieces are obtained through industrial CT machines, and then transmitted to the central management system. The system uses image processing technology to analyze the acquired images, extract the size information related to workpiece defects, and store them in the database. The image analysis system can accurately and objectively analyze the matrix structure, impurity content, tissue composition, defect size, etc. of metals or other materials, and provide a reliable basis for product quality. From the point of view of signal acquisition, the photons transmitted through the workpiece to be tested are converted into analog signals by the detector, and then converted into digital signals through A/D. The point diffusion principle in the product backprojection reconstruction algorithm [2] shows that the real boundary is 3 pixels in the edge range of the digital image. Canny transforms the edge detection problem into the problem of detecting the maximum value of the unit function [3]. In Gaussian noise, a typical edge represents a step change in intensity. (1) A good edge detection operator should have three indicators: low error probability, not only the real edge is lost, but also the non-edge is less judged as an edge; high positioning accuracy, the detected edge should be in the real edge position; has a * response for each edge, resulting in edges that are one pixel wide.

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