In recent years, the rapid development of robots, especially industrial robots, has drastically increased the market demand for machine vision. At the press conference of the World Robotics Congress in May 2016, Mao Weiming, Deputy Minister of Ministry of Industry and Information Technology, revealed that intelligent manufacturing is the focus of the department's future work and formulates the “13th Five-Year Plan†of the industrial robot industry in China for more policies. Supports the development, production and promotion of key robot components. Under the current era of high-end equipment manufacturing as the core of Zhisheng Industry 4.0, with the development of China's manufacturing strategy of 2025, the industrial intelligent robot industry market has shown an explosive growth momentum, and the machine vision function as the “eye-catcher†role of industrial robots has not been achieved. No.
As one of the important parts of robots, especially intelligent visual robots, machine vision is of decisive significance for the improvement of the robot's flexibility and operability. So how do we choose the right visual system based on our own needs?
1. Camera and optical components
This category usually contains one or more cameras and lenses (optical components) for shooting the object being detected. Depending on the application, the camera can be based on the following standards: black and white, composite color (Y/C), RGB color, non-standard black and white (variable scan), progressive-scan, or line scan.
2. Light
Lights are used to illuminate parts to capture better images from the camera. The lighting system can be in different shapes, sizes, and brightness. The general lighting forms are high-frequency fluorescent lamps, LEDs, incandescent lamps, and quartz-halogen fibers.
3. Component sensors
It usually appears in the form of a grating or a sensor. When this sensor senses that the part is close, it will give a trigger signal. When the part is in the correct position, this sensor tells the machine vision system to capture the image.
4. Image capture card
Also known as video capture card, this part is usually a card inserted in the PC.
The function of this capture card is to connect the camera to the PC. It takes data (analog signals or digital signals) from the camera and converts it into information that the PC can process.
It also provides signals to control camera parameters (such as trigger, exposure time, shutter speed, etc.). There are many types of image capture cards, supporting different types of cameras and different computer buses.
5.PC platform
Computers are a key component of machine vision.
Applications In terms of detection, Pentium or higher CPUs are usually used. In general, the faster a computer is, the shorter the time the vision system processes each picture.
Since there is often vibration, dust, heat radiation, and the like in the manufacturing site, an industrial-grade computer is generally required.
6. Detection software
Machine vision software is used to create and execute programs, process captured image data, and make PASS/FAIL decisions.
There are several forms of machine vision (C language library, ActiveX controls, click-through programming environment, etc.), which can be a single function (eg designed to detect only LCD or BGA, alignment tasks, etc.) or multi-function (eg, design A kit containing metering, bar code reading, robot navigation, on-site verification, etc.).
7. Digital I/O and Network Connections
Once the system has completed this part of the inspection, this part must be able to communicate with the outside world. For example, it is necessary to control the production process and send "PASS/FAIL" information to the database. Typically, a digital I/O board and/or a network card are used to communicate the machine vision system with external systems and databases.
Configuring a PC-based machine vision system Careful planning and attention to detail can help you ensure that your inspection system meets your application requirements. Here are some points that you must consider:
To determine your goals, this is probably the most important step in deciding what you need to achieve in this inspection task. Inspection tasks are usually divided into the following categories:
Measurement or measurement
Read character or code (bar code) information.
Detect the state of the object
Cognitive and recognition special pattern recognition
Compare or match objects with templates
The navigation detection process for a machine or robot may include only one operation or include multiple tasks related to the inspection task.
In order to confirm your task, first of all you should be clear in order to maximize the testing of the components you need to do the test, that is, you can take into account the defects that will occur.
In order to clarify what is the most important, it is best to make an assessment form that lists "must do" and "can do" tests. Once you are satisfied with the main test criteria, you can add more tests later to improve the testing process. It must be remembered that adding tests will also increase the testing time.
Determine the speed you need – how long does the system need to detect each part?
This is not only determined by the speed of the PC, but also by the speed of the production line.
Many machine visions include a clock/timer, so the time required to detect each step of the operation can be accurately measured. From this data, we can modify our program to meet the time requirements. Typically, a PC-based machine vision system can detect 20-25 parts per second, which is closely related to how many parts are detected and the processing program and speed of the computer.
Cleverly choose your hardware
The performance of a machine vision system is closely related to its components. In the selection process, there are many shortcuts, especially in optical imaging, which may greatly reduce the efficiency of the system. The following are some basic principles that you must keep in mind when choosing parts.
1. The choice of webcam camera is directly related to the needs of the application, usually considering three points:
a) black and white or color;
b) movement of parts/targets;
c) Image resolution.
Most of the black-and-white cameras are used in inspection applications because black and white images can provide 90% of visible data and are cheaper than color. Color cameras are primarily used in applications where color images need to be analyzed. Depending on whether the part moved during the test, it was decided whether we chose a standard interlaced camera or a progressive scan camera. In addition, the resolution of the image must be high enough to provide enough data for the inspection task. Finally, the camera must be of good quality and can avoid the effects of vibration, dust and heat on the industrial site.
2. Optical components and lighting is a crucial factor that is often overlooked. When you use a poor optical component or lighting, even if you use the best machine vision system, it may not perform as well as a low-capacity system with good optics and proper lighting. The goal of optical components is to produce images of the best and the largest available area, and provide the best image resolution. The goal of lighting is to illuminate the key features of the part that needs to be measured or detected. In general, the design of a lighting system is determined by the following factors: color, texture, size, shape, reflectivity, and the like.
3. Image Acquisition Card Although the image acquisition card is only a component of a complete machine vision system, it plays a very important role.
The image capture card directly determines the camera's interface: black and white, color, analog, digital, and more.
Using an analog input image capture card, the goal is to convert the camera's captured image to digital data as little as possible. Using the incorrect image capture card may result in incorrect data.
Industrial image capture cards are often used for inspection tasks. Multimedia capture cards do not need to be used in this area because they change image data through automatic gain control, edge enhancement, and color enhancement circuitry. The goal of using a digital input image capture card is to convert the digital image data output by the camera and send it to a PC for processing.
Consider the various changes: Human eyes and brain can identify targets under different conditions, but machine vision systems are not so versatile, it can only work according to programmed tasks. Knowing what your system can see and what you can't see can help you avoid failures (such as thinking good parts are bad) or other detection errors. Common considerations include large changes in component color, ambient light, focus, position and orientation of components, and background color.
The right choice of software: Machine vision software is the smart part of the detection system, and is also the most central part. The choice of software determines the time when you write the debugger, the performance of the test, and more.
Machine vision provides a graphical programming interface (often called "Point & Click") that is usually easier than other programming languages ​​(such as Visual C++), but has certain limitations when you need some special features or functions. Code-based software packages, although very difficult and require coding experience, have greater flexibility in writing complex application-specific detection algorithms. Some machine vision software also provides graphical and code-based programming environments that provide the best of both worlds and provide a lot of flexibility to meet different application needs.
Communication and Record Data: The overall goal of machine vision systems is to achieve quality inspection by distinguishing between good and bad parts. In order to achieve this function, this system needs to communicate with the production pipeline so that it can do something in finding bad parts. Usually these actions are through digital I/O boards that are connected to PLCs in the manufacturing line so that bad parts can be separated from good parts. With the exception of the machine vision system, which can be connected to the network, data can be transmitted to a database for recording data and for the quality controller to analyze why the reject occurred. Careful consideration at this step will help to integrate the machine vision system seamlessly with the production line. The issues to consider are:
What type of PLC is used and how is its interface?
What type of signal is needed?
What type of network do you use or must use now?
What is the format of the file transferred on the network? RS-232 port and database communication are usually used to record data.
Prepare for the future: When you choose components for the machine vision system, keep in mind the future production needs and possible changes. These will directly affect whether your machine vision software and hardware are easy to change to meet future new tasks. Preparing ahead of time will not only save you time, but also reduce the overall system price by reusing existing inspection tasks in the future. The performance of the machine vision system is determined by the worst part (just like the capacity of a bucket is determined by the shortest wooden block), and the accuracy is determined by the information it can obtain. By taking the time and effort to configure the system properly, a zero-fault and resilient visual inspection system can be built.
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