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[ Hot attention from chemical machinery equipment network ] The application of machine vision in intelligent manufacturing, iphone is a smart phone that everyone is familiar with.
Iphone manufacturing is a highly automated and intelligent manufacturing process, which also shows us the intelligence in industrial application scenarios.
A miniature of manufacturing.
Chemical machinery and equipment network hotspots pay attention to chemical machinery and equipmentIphone manufacturing is a highly automated and intelligent manufacturing process, which also shows us the intelligence in industrial application scenarios.
A miniature of manufacturing.
In a typical industrial application scenario, one of the cores of intelligent manufacturing is the machine vision system, which is the visual perception system that people give to the machine.
Just like humans have eyes, they can flexibly use their hands to process complex work procedures.
Just like humans have eyes, they can flexibly use their hands to process complex work procedures.
Machines are inanimate, so how do we endow machines with visual perception? How does the machine play a role in actual production after it has the ability to improve vision?
With these questions, let's take a look at the application of machine vision in industrial intelligent manufacturing in this issue.
Machine vision is to let robots understand the world, focusing on robots and understanding two points, while computer vision is to let computers understand the world, focusing on computers and understanding, comparing the difference between industrial-grade machine vision and consumer-grade computer vision.
The main point is to compare the application content of the subject.
For example, machine vision belongs to the system engineering science, which is an integrated solution of hardware and software.
It is mostly used for automatic control of industrial production lines.
Industrial cameras are used, including illumination images, capture lenses, and control.
Technical details such as image processing.
For example, machine vision belongs to the system engineering science, which is an integrated solution of hardware and software.
It is mostly used for automatic control of industrial production lines.
Industrial cameras are used, including illumination images, capture lenses, and control.
Technical details such as image processing.
Computer vision is a software-led discipline of computer science, focusing on the image itself and related interdisciplinary research, mostly using consumer-grade cameras, mainly researching image processing algorithms, and comparing the difference between mv and cb.
We focus on analyzing the key points of machine vision intelligent manufacturing
*, the role of machine vision in industry is to give a pair of eyes to the production process to make it possible to make manufacturing intelligent
Second, the definition of a machine vision system is to automatically acquire one or more target object images in the actual production process, process, analyze and measure various features of the acquired images, and make qualitative analysis of the measurement results And quantitative interpretation, so as to obtain a certain understanding of the target object and make the corresponding decision-making system.
Third, the core function of machine vision is measurement, recognition and positioning, as well as qualitative and quantitative analysis and decision-making on the basis of
Fourth, the composition of the machine vision system consists of lighting, light sources, optical lenses, industrial cameras, image capture cards, and image processing algorithms.
After understanding the above knowledge, let's take a look at a scenario where machine vision can play a role, taking the Amazon Robotic Grabbing Challenge as an example.
The robot uses two 3D cameras, one is installed on the fixture and the other is installed on the column.
The two 3D cameras and the corresponding vision algorithm constitute the machine vision module, which is responsible for detecting the target object and estimating the position of the object.
The robot grabs the object.
In the process, the robot detects and locates the target object through machine vision, thereby guiding the robot to grasp.
The two 3D cameras and the corresponding vision algorithm constitute the machine vision module, which is responsible for detecting the target object and estimating the position of the object.
The robot grabs the object.
In the process, the robot detects and locates the target object through machine vision, thereby guiding the robot to grasp.
Four scenarios where machine vision may play a key role in practical applications
Measurement: In the process of industrial production, the dimensions of parts or products, such as diameter, length, width, area direction of objects, angle between objects, position of objects, distance between objects or parts, number of objects, etc.
Take measurements.
Take measurements.
Image classification integrity detection: In the packaging industry, machine vision is used to detect the integrity of packaging.
Recognition and positioning: In the automobile manufacturing process, the door and other components are recognized and positioned, and the robot is guided to perform operations such as painting and assembly.
Defect detection: In the production process of mobile phones, machine vision is used to accurately distinguish the real scratches and the excessive reduction caused by interference, so as to ensure the quality of the products.
Intelligent manufacturing is a brand-new production model that adopts various* technologies such as machine vision, robotics, artificial intelligence, Internet of Things, and big data to further realize efficient, energy-saving and flexible factories.
Original title: How machine vision is applied to industrial intelligent manufacturing