Definition and composition of the hottest machine

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Definition and composition of machine vision

automation of the RIA robotic Industries Association defines machine vision as: "machine vision is a device that automatically receives and processes the image of a real object through optical devices and non-contact sensors to obtain the required information or control the motion of robots"

machine vision system refers to capturing the image through machine vision products (i.e. image pickup devices, divided into CMOS and CCD), and then transmitting the image to the processing unit. Through digital processing, the size, shape, color, etc. are judged according to pixel distribution, brightness, color and other information. Then, according to the result of discrimination, the equipment action on site is controlled

with the development of computer technology and fieldbus technology, machine vision has become mature with superior appearance quality. It has become an indispensable product in modern processing and manufacturing industry, and is widely used in food and beverage, cosmetics, pharmaceuticals, building materials and chemical industry, metal processing, electronic manufacturing, packaging, automobile manufacturing and other industries

the introduction of machine vision, instead of traditional manual detection methods, has greatly improved the product quality and production efficiency

in modern industrial automation production, various inspection, production monitoring and parts recognition applications are involved, such as dimensional inspection of batch processing of spare parts, integrity inspection of automatic assembly, automatic component positioning of electronic assembly line, character recognition on IC, etc. Generally, the human eye cannot complete these highly repetitive and intelligent tasks continuously and stably, and other physical quantity sensors are also difficult to be used. Therefore, people began to consider using the photoelectric imaging system to collect the image of the controlled target, and then digitize it by computer or special image processing module. According to the pixel distribution, brightness, color and other information of the image, we can distinguish the size, shape, color and so on. In this way, the rapidity and repeatability of computer are combined with the highly intelligent and abstract ability of human vision, which leads to the concept of machine vision

a successful machine vision system is a system that has been carefully engineered to meet a series of clear requirements. When these requirements are fully determined, the system is designed and established to meet these precise requirements

the characteristics of machine vision include the following points:

■ high accuracy

as an accurate measuring instrument, an excellent vision system can measure one of a thousand or more components in space. Because this measurement does not require contact, there is no wear and danger to fragile parts

■ continuity

the visual system can protect people from fatigue. Because there is no manual operator, there is no man-made operation change. Multiple systems can be set to operate independently

■ high cost efficiency

with the sharp decline in the price of computer processors, the cost efficiency of machine vision systems has become higher and higher. A $10000 vision system can easily replace three human detectors, each of which requires a salary of $20000 a year. In addition, the operation and maintenance cost of the visual system is very low

■ flexibility

the vision system can make various measurements. When the application changes, only the software needs to be changed or upgraded to meet the new requirements

many companies applying satisfactory process control (SPC) are considering the application of machine vision systems to deliver continuous, coordinated and accurate measurement SPC commands. In SPC, manufacturing parameters are continuously monitored. The control of the whole process is to ensure that these parameters are within a certain range. This enables the manufacturer to adjust the process parameters when the production process is out of control or there are bad parts

machine vision system has better adaptability than optical or machine sensors. They make automatic machines have diversity, flexibility and reconfigurability. When the production process needs to be changed, for machine vision, "tool replacement" is only the transformation of software, not the replacement of expensive hardware. When the production line is reorganized, the vision system can often be reused

the composition of machine vision system

machine vision technology uses computers to analyze an image and draw conclusions based on the analysis. There are two applications of machine vision nowadays. Machine vision system can detect components, where optical devices allow the processor to observe the target more accurately and make effective decisions on which components can be discarded and which need to be discarded; Machine vision can also be used to create a component, that is, using complex optical devices and software to directly guide the manufacturing process

although machine vision applications are different, they all include the following processes

■ image acquisition

the optical system collects images, which are converted into analog format and transferred to computer memory

■ image processing

the processor uses different algorithms to improve the image elements that have an important impact on the conclusion

■ feature extraction

the processor recognizes and quantifies the key features of the image, such as the location of holes on the printed circuit board or the number of pins on the connector. These data are then transmitted to the control program

■ decision and control

the control program of the processor makes a conclusion based on the received data. For example, these data include whether the hole on the printed circuit board is within the required specification or how an automatic machine must move to pick up a part

machine vision system analysis

typical vision systems generally include: light source, optical system, camera, image processing unit (or image acquisition card), image analysis and processing software, monitor, communication/input and output unit, etc

■ image acquisition

image acquisition actually converts the visual image and internal characteristics of the measured object into data that can be processed by computer, which directly affects the stability and reliability of the system. Generally, the light source, optical system, camera and image processing unit (or image capture card) are used to obtain the image of the measured object

■ light source

light source and important factors affecting the input of machine vision system, because it directly affects the quality of input data and at least 30% of the application effect. Since there is no general machine vision lighting device, the corresponding lighting device should be selected for each specific application example to achieve the best effect. Many industrial machine vision systems use visible light as the light source, mainly because visible light is easy to obtain, such as low price and easy to operate. The commonly used visible light sources are white flag lamp, fluorescent lamp, mercury lamp and sodium lamp. However, one of the biggest disadvantages of these light sources is that the light energy can not remain stable. Take fluorescent lamps as an example. In the first 100 hours of use, the light energy will decrease by 15%. With the increase of use time, the light energy will continue to decline. Therefore, how to keep the light energy stable to a certain extent is an urgent problem to be solved in the process of practical x12crmowvnbn10 ⑴ ⑴ steel with good castability, hardenability, oxidation resistance, weldability and durable toughness. On the other hand, ambient light will change the total light energy of these light sources on the object, making the output image data noisy. Generally, the method of adding a protective screen is used to reduce the impact of ambient light. Due to the above problems, in today's industrial applications, invisible light such as X-ray and ultrasonic is often used as the light source for some highly demanding testing tasks

the lighting system composed of light sources can be divided into: back lighting, forward lighting, structured light and strobe lighting according to their illumination methods. Among them, back illumination is that the tested object is placed between the light source and the camera, and its advantage is that it can obtain high contrast images; Forward illumination means that the light source and camera are located on the same side of the tested object, which is convenient for installation; Structured light illumination is to project grating or linear light source onto the measured object, and demodulate the three-dimensional information of the measured object according to their distortion; Stroboscopic illumination is to irradiate high-frequency light pulses onto objects, which requires the scanning speed of the camera to be synchronized with the stroboscopic speed of the light source

■ optical system

for machine vision system, image is the only source of information, and the quality of image is determined by the appropriate selection of optical system. Generally, errors caused by poor image quality cannot be corrected by software. Machine vision technology combines optical components and imaging electronics, and uses computer control systems to distinguish, measure, classify and detect components that are passing through automatic processing systems. Machine vision systems can usually detect processed products as fast as 100% without reducing the speed of the production line. As more and more manufacturers are demanding "6-sigma" (less than 3 parts per million of effective units) results, in order to be more competitive in today's market with strong quality awareness, this ability is very important. In addition, these systems can be combined with satisfactory process control (SPC) Very ideal cooperation

the main parameters of the optical system are related to the format of the photosensitive surface of the image sensor, generally including: aperture, field of view, focal length, F number, etc

■ camera

camera is actually a photoelectric conversion device, that is, the optical image received by the image sensor is converted into an electrical signal that can be processed by the computer. Photoelectric converter is the core component of camera. At present, the typical photoelectric converters are vacuum camera tubes, CCD, CMOS image sensors, etc

the vacuum TV camera tube consists of a camera target sealed in a glass tube cover and an electron gun. The camera target converts the illumination distribution of the input optical image into the two-dimensional spatial distribution of the corresponding pixel charge on the target surface, which mainly completes the tasks of photoelectric conversion and charge storage; The electron gun completes the process of scanning and picking up image signals. TV camera tube imaging system has the characteristics of high definition, high sensitivity, wide spectrum and high frame rate imaging. However, as the TV camera tube is a vacuum tube device, its weight, volume and power consumption are large

ccd is the most commonly used image sensor in machine vision at present. It integrates photoelectric conversion, charge storage, charge transfer and signal reading. It is a typical solid-state imaging device. The outstanding feature of CCD is that it takes charge as the signal, which is different from its device, which takes current or voltage as the signal. Such imaging devices form charge packets through photoelectric conversion from lightweight materials, industrial equipment, overall solutions, etc., and then transfer and amplify the output image signal under the action of driving pulses. A typical CCD camera consists of an optical lens, a timing and synchronization signal generator, a vertical driver, and an analog/digital signal processing circuit. The following figure is the principle block diagram of CCD camera. As a functional device, CCD has the advantages of no burn, no hysteresis, low voltage operation and low power consumption compared with vacuum tube

The development of CMOS (comprehensive metal oxide semiconductor) image sensor first appeared in the early 1970s. In the early 1990s, with the development of VLSI manufacturing technology, CMOS image sensors developed rapidly. CMOS image sensor integrates photosensitive element array, image signal amplifier, signal reading circuit, analog-to-digital conversion circuit, image signal processor and controller on one chip, and also has the programming randomization of local pixels

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