Introduction of Machine Vision Inspection Technology

1. overview

Visual inspection is to measure and judge with machine instead of human eyes. Visual detection refers to the conversion of the captured object into image signal through machine vision products (i.e. image capturing devices, divided into CMOS and CCD), which are transmitted to a special image processing system and converted into digital signal according to the information of pixel distribution, brightness, color, etc. The image system extracts the features of the target by various operations, and then according to the results of discrimination. Control the device action on site. It is a valuable mechanism for production, assembly or packaging. It has immeasurable value in detecting defects and preventing defective products from being distributed to consumers.

The feature of machine vision inspection is to improve the flexibility and automation of production. In some dangerous working environments that are not suitable for people's work or where artificial vision is difficult to meet the requirements, machine vision is often used to replace artificial vision. At the same time, in the mass industrial production process, using artificial vision to inspect product quality is inefficient and inefficient, and using machine vision detection method can greatly improve production efficiency and automation of production. Moreover, machine vision is easy to realize information integration, which is the basic technology to realize computer integrated manufacturing.

2. Basic Composition and Principle of Machine Vision System

A typical industrial machine vision application system includes digital image processing technology, mechanical engineering technology, control technology, light source lighting technology, optical imaging technology, sensor technology, analog and digital video technology, computer hardware and software technology, man-machine interface technology, etc.

- Image component

The camera captures the electronic image of the detected object and sends it to the processor for analysis. Electronic images are converted into numbers to represent the smallest part of the image, that is, the pixels. The number of pixels displayed in an image is called resolution. The higher the resolution of the image is, the more the number of pixels it contains. The more the number of pixels in the image is, the more accurate the detection result is.

Camera

The camera of the visual inspection system has three variables that need to be adjusted to optimize the captured image. They are aperture, contrast and shutter speed.

- Lighting components

Correct lighting is critical to help create the contrast needed for effective detection. When evaluating the correct system settings for a product, the designer spends considerable time determining the best lighting for the test. The type, geometry, color and intensity of lighting solutions should provide as strong a contrast as possible.

Software tools

Visual inspection system uses software to process images. The software uses algorithmic tools to help analyze images. Visual inspection solutions use such a combination of tools to complete the required detection. Commonly used include search tools, boundary tools, feature analysis tools, process tools, visual printing tools and so on.

3. Advantages of Machine Vision Inspection

Compared with human vision, machine vision has obvious advantages in detection industry.

High accuracy: Human vision has 64 gray levels and weak resolution to small targets; Machine vision can significantly improve the gray levels, while observing micron targets;

Fast: Human beings can't see the fast moving target, and the shutter time of the machine can reach microsecond level.

High stability: Machine vision solves a very serious human problem, instability, manual visual inspection is a very boring and hard work industry, no matter what reward and punishment system you design, there will be a relatively high rate of missed detection. But machine vision detection equipment has no fatigue problem, no mood fluctuation, as long as you write in the algorithm, every time will be seriously implemented. In the quality control, it greatly improves the controllability of the effect.

Integration and retention of information: The amount of information obtained by machine vision is comprehensive and traceable, and related information can be easily integrated and retained.

4. Application of Machine Vision Inspection

Application of Visual Inspection in Printing Industry

On-line/off-line vision system is used to find quality problems in printing process, such as die cutting, ink stacking, flying ink, missing/shallow printing, imprecise overprint, color deviation, etc. At the same time, on-line equipment can feedback the detection results of color deviation and ink quantity to PLC, control the ink supply quantity of printing equipment, adjust the ink supply quantity online, and improve printing quality and efficiency.

Application of Visual Inspection in PCB Board Inspection

The vision system is used to detect the bare PCB board. The position and spacing errors of the wires and components on the board, the size errors of the wires and components, the shape errors of the components, the passages of the lines and the contamination on the board are detected.

Application of Visual Inspection in Parts Inspection

Machine vision inspection can easily deal with the quality control of metal parts production, such as coins, automotive parts, connectors and so on. By means of image processing, defects such as scratches, defects, discoloration and mucosa on the surface of metal parts are found, and the mechanical transmission system is guided to eliminate the defective products, which greatly improves the production efficiency. At the same time, the statistical analysis of defect types can guide the adjustment of production parameters and improve product quality.

Application of Visual Inspection in Automobile Safety

The working principle of this kind of digital system is to detect and measure real-time geometric features and motion features of eyelid and eyeball, eye gaze and its dynamic changes, head position and direction changes by visual sensors, to establish the relationship model between driver's eye head characteristics and fatigue state, and to study fatigue.