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With the development of robots and vision, "Industry 4.0" is approaching us step by step
The author:SIPO  Time:2018-04-02  Read: 146

From the detection of product defects, the identification of two-dimensional codes, the establishment of production history to the implementation of robotic tasks, the field of application of machine vision continues to expand and its performance on the production line is remarkable. Machine vision technology not only saves a lot of manpower, but also creates values that many human operators cannot bring.

Machine vision can be said to be the window of the soul of an industrial automation system. From object/bar code identification, product inspection, appearance measurement to robot arm/transmission equipment positioning, machine vision technology can play a role. In order to cope with an endless stream of new application requirements, the design of industrial cameras has also taken a new direction of development.

With more and more applications, in order to increase the flexibility of applications or to work with industrial computers to form more complex automation systems, the development trend of industrial cameras is gradually approaching the personal computer, and some products have even evolved into a small, five-legged family of sparrows. Full mini industrial computer.

As CPU performance, vision algorithms, and hardware costs continue to improve, the application of machine vision in factories has become more and more popular. At the same time, it also brings benefits to manufacturers such as reducing costs, improving quality, and improving production efficiency. Compared with the human eye, machine vision has the advantages of fast detection speed and the control standards that are not subjectively influenced by humans. Moreover, the resolution of machine vision is much higher than that of the human eye. When detecting fine parts or circuits, it is better able than the human eye to see clearly. . These advantages have made machine vision popular in both the technology manufacturing industry and the traditional manufacturing industry in recent years.

The application of machine vision in manufacturing is becoming more and more extensive, and industrial cameras have emerged in new directions. Because there are great differences in the performance and function configuration of machine vision between different applications, machine vision can be roughly divided into configurable systems, embedded systems, and smart camera types. Regardless of the machine vision system, apart from a few special applications, the industrial cameras used by them are increasingly closer to the personal computer. Even the smart camera is essentially a built-in CPU and memory and can perform various kinds of vision. Algorithmic industrial computer.

In addition to the need for progressive scanning (such as panel detection) or very high-speed applications still using industrial cameras equipped with Camera Link interface, most industrial cameras currently use GbE interfaces, in addition to low cost, easy to interface with industrial computers, constitute a huge Complex automation systems are also a big advantage. Industrial cameras equipped with USB 3.0 are also gaining popularity in the market for the same reason.

As for the smart camera, it is essentially a mini-industrial computer. In addition to the elements of the camera such as optics, image sensors, and digital signal processors, the camera also features a quad-core Atom processor that can perform various visual algorithms directly on the camera. This smart camera has the advantages of small size and simple deployment. It is suitable for use in small-scale automated systems, or combined with the robot arm to guide the operation of the robot arm.

It is worth noting that apart from the fact that the hardware design is getting closer to the PC, the software of future industrial cameras will become more and more open as the PC, because the main opening and release of GENiCAM Middleware is increasingly gaining industrial Camera users love it.

GENiCAM can be said to be a major turning point in the development of industrial cameras. Before this open intermediaries appeared, each industrial camera manufacturer used its own closed software platform. If users wanted to switch to other industrial camera manufacturers' products, they were already writing. The application has to be written from scratch and the conversion cost is very high. With GENiCAM, although conversion vendors still need to rewrite applications, the revision rate has been greatly reduced.


Dedicated software algorithms blessing two-dimensional code reading difficult

In addition to being more open, the evolution of the performance of machine vision software in recent years cannot be underestimated. In order to improve the degree of automation of the product manufacturing process or to collect complete production history data, the culture of manufacturing industry to introduce industrial QR codes has taken shape.

However, it is a considerable challenge to read the correct QR code on the production line in a stable and fast manner. For example, the two-dimensional code label itself has been damaged, hidden by other objects, or the status of the label is blurred, is a very common problem. The most advanced two-dimensional code recognition algorithm has been able to overcome the above problems. Even if the two-dimensional code itself is partially damaged or blocked by other objects, it can still be interpreted correctly.

For the two-dimensional codes used in the electronics industry, there is one more problem encountered by other industries: the miniaturized two-dimensional codes. For example, a mobile phone brand maker already uses lasers, etching, and other methods on the components used in his mobile phones to directly use two-dimensional codes on components. As a result, in the process of assembling and manufacturing the mobile phone, every step can leave a record, which not only helps improve the product yield, but also makes it easy to trace back to the source of production in the event of a phone malfunction.

However, since the mobile phone parts themselves are very small, the area that can be reserved for the two-dimensional codes is very limited. Therefore, the length and width of such two-dimensional codes is often only a few millimeters, and often even smaller than that of rice grains. Therefore, it is reliable for machine vision algorithms. Degrees and performance pose considerable challenges.

In order to solve various challenges encountered when reading two-dimensional codes on a production line, Cognex spent years developing a PowerGrid reading algorithm that can be easily read even when a barcode is missing or partially obstructed. This feature also allows the company's algorithm to accurately read ultra-small QR codes. For example, because the PowerGrid algorithm can successfully read even if the two-dimensional code tag does not have a mute area, a clock pattern, or a positioning pattern, manufacturers can save a very considerable amount of space when printing labels on components. .

Visual function blessing robot application more flexible

Robotic arms are a symbol of industrial automation and have been widely used in some manufacturing industries in the past, such as the automotive industry. Industry 4.0 will be an opportunity for the expansion of robotic arm applications to other manufacturing industries. However, before that, robotic operators must first try to introduce robotic arm solutions with high deployment flexibility that are suitable for various industrial applications, and they must try to drive down the introduction. threshold.

The robotic arm will not remain at the stage of replacing labor, but will develop towards performing tasks that humans cannot perform. Therefore, the robot arm must be matched with various sensing functions, and depending on the current conditions to deal with the problems encountered. Therefore, the machine arm with a variety of sensing functions such as machine vision and force sensing will be the inevitable trend.

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