How does machine vision respond to the challenges of integrating applications with industrial automation systems?

As one of the important components of industrial automation system, machine vision has become increasingly mature with the development of automation industry. It is embodied in the continuous enhancement of image processing capabilities and speed, the improvement of the performance of optoelectronic devices, the gradual unification of various standards, and the relative reduction of prices.

As one of the important components of industrial automation system, machine vision has become increasingly mature with the development of automation industry. It is embodied in the continuous enhancement of image processing capabilities and speed, the improvement of the performance of optoelectronic devices, the gradual unification of various standards, and the relative reduction of prices.

According to the AIA (Automatic Imaging Association) market research report, the global machine vision market in 2006 has exceeded 7 billion U.S. dollars, and it is predicted that it will maintain a sustained growth momentum in the next five years. However, as suppliers and integrators continue to push machine vision applications to various fields, how to seamlessly integrate machine vision, a relatively independent function, into various automation equipment in various industries has encountered unprecedented challenges.

1. Application and challenges of machine vision

Machine vision applications can be divided into two main categories:

One type is used in large-scale or high-test production lines, such as packaging, printing, sorting, etc., or in the field, nuclear power and other environments that are not suitable for human work, using machine vision to replace traditional manual measurement or inspection. At the same time, it achieves reliability, accuracy and automation that cannot be achieved under manual conditions.

Another type of application is professional equipment manufacturing that must use high-performance, precision machine vision components. The typical representative is the semiconductor manufacturing equipment that first drove the rise of the entire machine vision industry. From the sorting and cutting of upstream wafer processing and manufacturing to the printing and placement of end circuit boards, this type of equipment relies on high-precision visual measurement to guide and locate moving parts. For example, if there is a positioning deviation in the solder paste printing process, and the problem is not discovered until the online test after the chip is placed, the cost of the repair will be more than 100 times the original cost.

However, in the above applications, the machine vision function is rarely used as an isolated system, but as one of the organic components of the entire automation system or equipment. It is also often used in conjunction with logic control, motion control, data acquisition, communication networks and enterprises. Only when other functions, such as database management, can really give full play to its advantages. To build a machine vision system, in addition to completing a series of processes from light source deployment to image processing software development, it also faces the challenges brought about by the integration of the above-mentioned complex automation system functions. A single vision development software and hardware solution often makes the overall development cycle, cost, and uncertainty risk of the automation system be borne by the manufacturer or integrator. The difficulty of integrating machine vision with automation systems has largely hindered its application in the relatively conservative industrial automation field.

2. Solutions based on NI LabVIEW and machine vision system

In the face of the above-mentioned challenges, the NI LabVIEW software platform and its machine vision system provide a good solution.

Let us first look at the development and integration process of machine vision from the perspective of software: First, with the help of the efficient and convenient configuration software VBAI (machine vision generator for automatic inspection) and a comprehensive vision module (covering all formats and standard cameras) Support, provide hundreds of image processing functions such as pattern matching, OCR, particle analysis, two-dimensional barcode recognition, etc.), users can verify different camera and light source settings, acquisition methods and image processing algorithms in an interactive development environment, and then Then the confirmed steps will automatically generate an executable program corresponding to LabVIEW. The LabVIEW software platform has intuitive graphical development features, allowing engineers to focus more on functional development rather than code writing.

In the process of overall system development and integration, engineers can directly use the corresponding LabVIEW toolkits and modules to complete functions such as motion control, data acquisition, industrial communication, and man-machine interface in the same way under a unified platform, and achieve integration with various functions. Connection and communication of PAC (programmable automation controller), PLC, industrial equipment, OPC client and enterprise database. Regarding this development model, both experienced integrators and junior developers are able to overcome the difficulties of dedicated or even private development methods and platforms, drivers and protocols, and physical communication and synchronization between devices corresponding to different devices. This liberation greatly reduces the difficulty and cost of system integration.

From the perspective of hardware architecture, PC-based machine vision systems provide powerful processing capabilities and are easier to integrate with other functions due to their openness and flexibility. However, the PC architecture is due to reliability and size. The reason is that it cannot fully meet the needs of industrial applications.

The other method is the embedded architecture, which is simple to use and highly reliable, but has relatively single functions and poor integration. In order to solve these contradictions, NI has integrated LabVIEW real-time and FPGA technology in its compact machine vision system (CVS), which has unprecedentedly realized flexible customization and movement of I/O and communication protocols under the same embedded hardware platform. , Can collect and process 3 channels of image signals at the same time, and ensure the robustness and reliability of the system to meet the application requirements under the harsh environment of the industrial field (Figure 1).

How does machine vision respond to the challenges of integrating applications with industrial automation systems?

Fig. 1 FIG. 1 NI compact machine vision system

Below we use two example analyses to specifically discuss how to use an open and flexible software and hardware platform to integrate machine vision and multi-domain functional applications to reduce the complexity of system integration and shorten the development cycle.

3. Automated semiconductor wafer classification system based on LabVIEW and synchronized machine vision, motion control, and data acquisition

In the semiconductor manufacturing industry, wafers must be carefully classified according to their thickness (THK), total thickness error (TTV), bending (BOW), warpage (WARP) and other electrical and physical parameters before cutting to achieve strict tolerances. Poor request. In order to ensure the measurement accuracy, the traditional single-point measurement method is used, which consumes a lot of test time.

For this reason, Gigamat Technologies of the United States has developed a new generation of full-scan automatic classification equipment (Figure 2) to increase throughput and require accuracy and repeatability requirements under single-point testing. This is a considerable technical challenge. .

How does machine vision respond to the challenges of integrating applications with industrial automation systems?

Fig. 2 Automated semiconductor wafer sorting system

The new fully automatic wafer sorting system makes full use of the LabVIEW platform and its supporting toolkit. The system is divided into two steps: wafer alignment and measurement. The alignment process uses line scan image acquisition and 3-axis motion control. By synchronizing the image acquisition and the chassis rotation rate, the entire wafer 6 million pixel image acquisition is completed in 1 second, and the LabVIEW vision algorithm is used to determine the center position of the wafer. Flatness and other characteristics, adjust the wafer position accordingly to achieve a perfect match with the parameter measurement platform.

The measurement step requires that the resolution of the upper and lower surface measurement is less than 0.0001mm. The solution is to use the NI motion control tool under the LabVIEW platform to generate a smooth arc and spiral trajectory combination, accurately control the position of the rotating wafer, and use NI data acquisition The card completes the high-speed and high-density measurement of the probe with multiple channels simultaneously, records the corresponding position in real time, performs related calculations and processes based on this, obtains various parameter information, and finally obtains the classification result.

How does machine vision respond to the challenges of integrating applications with industrial automation systems?

In addition to the above core steps, the system also includes: touch screen human-machine interface; wafer elevator control based on RS-485 communication; digital I/O control for light source, machine power and vacuum equipment; and database access with Microsoft Access Connect to realize the digital processing of the processing process. These functions are all developed in a unified manner under the LabVIEW platform. The manager of Gigmat commented that “if there is no synchronization of LabVIEW and NI machine vision, motion control and data acquisition products, this project will not be economically feasible.”

Fourth, NI compact machine vision system helps automobile spark plug inspection to reach the repeatability standard of 6Sigma

The eccentricity and electrode spacing of automobile spark plugs are the key indicators that determine its performance. In the past, a leading automobile spark plug manufacturer has always used manual methods to measure them. Because of the low measurement accuracy, too strict product tolerance band restrictions must be adopted, which leads to unnecessary production requirements increase and output reduction. In order to ensure reliable quality control, faster inspection speed and increased output, the manufacturer decided to establish a full-scan size quantitative system based on machine vision.

The system consists of IEEE 1394 camera, ring light source, robust NI CVS embedded machine vision system and LabVIEW software development platform. The collected spark plug image is transmitted to CVS through FireWire, and special algorithms such as real-time circular edge detection are run on it, and the balance point between accuracy and processing time is found through the control of under-sampling. The measurement accuracy reaches 0.01mm, which fully meets the 6Sigma standard. .

Subsequently, CVS communicates with PLCs and relays on the production line through its digital port to complete automatic rejection of unqualified products, eliminating manual intervention. The whole system is connected to the factory Ethernet, which can carry out remote parameter configuration, calibration and product information recording. Due to the improvement of test accuracy, the tolerance range has been relaxed, and the output and efficiency have been greatly improved.

in conclusion

Machine vision applications are developing from simple image acquisition, processing and analysis, and result judgment output at the beginning to become one of the important components of automation systems. However, machine vision also has its particularity compared with the manual detection method, which is reflected in its flexibility and adaptability to a certain extent. If it is not handled properly, even if a seemingly small new function is introduced, it may lead to a redesign of the system.

When faced with machine vision integration and flexibility and problems, the ideal industrial software development environment LabVIEW has become a very good choice for user development platforms. Using the rich analysis and processing algorithms contained in the machine vision module, users can customize and develop or simply upgrade the corresponding vision functions according to their specific needs. They can also realize motion control and programmable automation controllers in this unified image-based development method. The development of equipment and functions such as data acquisition, as well as the seamless connection with the three-party PLC, industrial equipment and database software, so as to complete the development and integration of automation systems covering machine vision functions.

Thanks to this system architecture, manufacturers can more easily introduce machine vision functions into their production lines, reducing the technical difficulty of their equipment manufacturing, which is in line with the trend of machine vision towards the integration of automation systems.

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