Machine vision technology involves computer science, artificial intelligence, signal processing, image processing, machine learning, optics, automation and other fields.
In recent years, with the rapid development of industrial intelligence, machine vision technology has been widely used in various fields of industrial production. As a modern detection method, it has become more and more popular. Be taken seriously.
Machine vision obtains the image information of the target object through optical equipment and sensors, then converts the image information into digital information, and then analyzes the data through a computer and displays it on an electronic screen or guides the machine to complete tasks through a control unit. Machine vision focuses on information technology engineering and automation, but it is also built on the basis of computer technology visual effects methodology. Its focus is on perceiving data information such as the position information, size, shape, color information, and existence status of the target object.
Currently, China’s machine vision industry is still in its early stages of development. From the perspective of the industry chain, it can be divided into upstream parts and software, and midstream industrial machines. There are three major links: visual equipment, and downstream system solutions and applications. The overall scale, strength and technical level of upstream parts and software companies still need to be improved. Midstream industrial machine vision equipment needs to continue to improve the comprehensive performance of products and continuously improve the intelligence level of products. The main downstream application industries are in the fields of semiconductors, consumer electronics and automobiles.
Increased policy support and continued growth in demand have created a good development environment for industrial machine vision. On the one hand, the national and local governments have issued a series of policies to support the development of industrial machine vision. For example, the "14th Five-Year Plan for Intelligent Manufacturing Development" has deployed four key tasks such as "strengthening independent supply and strengthening new advantages of the industrial system". In the "Intelligent Manufacturing Equipment Innovation and Development Action", the company focuses on the research and development of basic components and devices such as high-resolution vision sensors, which reflects its emphasis on and support for the industrial machine vision industry.
On the other hand, China's national economy continues to recover and develop. In the first quarter of 2022, the added value of national industrial enterprises above designated size increased by 6.5% year-on-year, and the profits of industrial enterprises above designated size increased by 8.5%. As a key application field of industrial machine vision, The output of new energy vehicles increased by 140.8% year-on-year, and the output of industrial robots increased by 10.2% year-on-year. The continued growth in downstream application fields has brought greater development space for the application of machine vision.
The demand for machine vision technology in industrial scenarios continues to drive the development of industrial machine vision products in the direction of standardization and modularization. The usage demands of industrial machine vision customers are diverse and highly specific. Customers all hope that suppliers can customize and optimize to a certain extent according to their own needs. Therefore, the development speed of customized industrial machine vision products directly determines the growth rate of corporate performance.
In order to solve this pain point, leading companies in the industry vigorously promote product standardization and modular development, assemble standardized modules from non-standard products as much as possible, and then output solutions to customers from standardized modules. This will improve the turnover rate of its own products and inventory, improve the company's ability to provide external solutions, and thereby improve the company's operational efficiency.
The technical level of industrial machine vision has become a key factor that directly affects the further intelligent development of various equipment. In recent years, the intelligence level of robots, drones and other equipment has been continuously improved and the application scenarios have been continuously enriched, which has put forward higher and more urgent demands for the comprehensive performance of industrial machine vision solutions.
For example, in the process of patrolling the chemical plant area, the petrochemical inspection robot needs to accurately identify problems such as "runs, leaks, leaks" of complex pipelines, and the timeliness and accuracy of identification directly determine the petrochemical inspection The practicality of robots and the market prospects of this type of robots.
For another example, in the coal gangue processing production line, the robot not only needs to identify the location and size of the coal gangue, but also needs to find the most suitable gripper for the coal gangue of different weights and shapes. position and determine the amount of clamping force exerted by the mechanical claw, so that it can truly and effectively replace manual work.
Industrial robots are the main representative technology of modern science and technology. Industrial robots are widely used in home appliances, Electronics, clothing, automobiles, food, and other industries. With the rapid development of modern science and technology, high standards and high efficiency have become the goals pursued by many enterprises. Against this development background, industrial robots emerged as the times require.
What impressed me most was the Jingdong automated robot warehouse. In the huge warehouse, thousands of robots are constantly moving back and forth between the shelves to classify, place and transport items. In the field of industrial robots, machine vision has the following functions.
(1) Positioning and control. Modern factory production requires machine vision systems to quickly and accurately find targets and confirm their locations. Then machine vision is used for positioning and guiding the robotic arm to grasp accurately.
(2)Identification. Machine vision is mainly used to obtain images, and then the images are processed, analyzed and understood to identify targets and objects in various states for tracking and collecting data. General machine identification systems are accomplished with the help of cameras.
(3)Detection. Testing the quality of products on the production line is also the link that replaces the most labor. In the industrial field, the main inspections include size inspection, bottle appearance defect inspection, bottle mouth defect inspection, defective product inspection, etc.
(4) High-precision inspection. In industrial production, some precision electronic equipment parts require high precision, such as highly integrated electronic circuit boards on computers and mobile phones. Some can reach an accuracy of 0.01mm or even μm level. The human eye cannot identify these small components, so It must be done using a machine.
(5) Sorting and transportation. In the process of modern industrial production and operation, there will inevitably be some sorting work. The traditional method of using human power to perform sorting work has great limitations. However, the application of visual robots can greatly improve the efficiency and work accuracy of industrial production. , thus liberating people’s hands.
Machine vision technology plays a core role in the application of robots. The most critical aspect of machine vision is how to enable robots to accurately identify moving targets. Vision system technology can solve this problem. Adding vision system technology can enable the robot to track and detect the movement of the target object in real time, and then accurately determine the position and direction of the target object to ensure the robot's accurate positioning.
The work of the robot vision system is mainly divided into four parts: camera positioning, image analysis and processing, target object status recognition and robot action control. First, the camera is used to position the target object to establish a motion coordinate system and obtain the object coordinates; then the obtained target object is divided into images for analysis and processing; state recognition is based on image analysis, analyzing and processing the state of the target object, and then according to the image The results of processing and analysis control the robot's action behavior.
The use of industrial robots is a great progress and development of modern industry compared to traditional industry. It solves the shortcomings of traditional industry such as high cost, low efficiency, and long time consumption, and frees people's hands to enable modern industrial production. More automated and intelligent.
Most modern industrial production tends to mechanical integration. For example, the production of potato chips, from potato cleaning to final potato chip packaging No human involvement is required for bagging and sealing. Of course, some people would say that things produced in this way are impersonal, but I would like to say that the mechanically integrated production method may be the general trend of all industrial production in the future, and its advantages will not be repeated. So, how can we control mechanized production? This requires the use of machine vision technology to control machine production.
The machine vision controller, because of its excellent processing capabilities, can complete the detection of up to 128 points at high speed within 10s. The powerful processing capabilities can directly affect the executable algorithms and the decision-making process of the visual system. speed. To reduce image processing time, some factories now use isomorphic processing to run vision algorithms.
In addition, some machine vision controllers now have dedicated Ethernet ports for network connections and ports for connecting external data storage. Through the factory connection function, staff can monitor product production in the office, view images, and play back in real time, which greatly facilitates factory production.
This direct method of industrial integrated production is slowly replacing the traditional production method. It is believed that in the future industrial development, a large number of factories will use machine vision control to achieve integrated factory production.
In the modern industrial production process, target detection is diverse and the market demand is relatively large. For example, detect whether the size of mechanical parts meets the standard, identify barcodes or packaging barcodes, test the appearance defects of goods, bottle mouth defects, printing defects, etc. These applications require large-scale testing, and they are all high-precision tests. Human eye recognition is at a disadvantage in these tests. If it is only done manually, it can be imagined that it is time-consuming.
In the production process of beer bottles, the size of the bottle and whether there are defects in appearance need to be quality tested. Some factories produce thousands of beer bottles a day, and it would be incompetent to handle them all manually.
Moreover, the general human eye has been staring at the same object detection for a long time, which will cause visual fatigue, which will lead to a high rate of defective products and low work efficiency. Not only that, some factories also spend a lot of money to hire manual inspections. This backward production method is no longer suitable for modern production.
Using machine vision technology can effectively solve this problem. Machine inspection is used to replace traditional manual labor. Large-volume inspection can be completed quickly, speeding up the factory’s product production; in addition, it reduces the factory’s production costs. , improve the production efficiency of the product.
The application of machine vision technology enables industrial production to no longer be limited by the defects identified by the human eye, improves the accuracy and efficiency of industrial inspection, and makes industrial production more automated and intelligent. .
Machine vision, as the broadest branch of artificial intelligence applications, can be used in various fields such as industry, agriculture, medicine, military, aerospace, meteorology, astronomy, transportation, security, scientific research, etc. Based on the rise of multi-scenario applications of machine vision and its irreplaceable performance advantages, a trillion-level market blue ocean has emerged, and all parties in the industry are accelerating their influx.
The above is the detailed content of What are the applications of machine vision in the industrial field?. For more information, please follow other related articles on the PHP Chinese website!
![[Web front-end] Node.js quick start](https://img.php.cn/upload/course/000/000/067/662b5d34ba7c0227.png)
