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机器视觉Systems

What is Machine Vision?

机器视觉是指使用工业摄像头,镜头和照明来执行对制成品的自动视觉检查。
Machine vision provides a fast, reliable way to inspect parts inline. With machine vision, every part coming down a high-speed line can be imaged and inspected, to ensure 100% quality control.
In the factory processes, machine vision can automate various inspections such as appearance inspections that check defects and faults, presence-absence checks, product type verifications, measurements, code readings.

机器视觉FAQ

哪些行业通常utilize Machine Vision?

Any industrial facility with a repetitive process can benefit from introducing vision. Machine vision has heavy presence in the automotive, plastics, food and packaging, medical device, and electronics industries, among others.

What applications are commonly solved using Machine Vision?

Vision systems are extremely customizable, and as such, can be used in any number of creative ways. Major machine vision applications are:

Appearance Inspection
Ensure a product is free of scratches, burrs, dents, short shot, flash, pinholes, or discoloration, even on complicated or low-contrast parts.

Presence/Absence (Counting)
Confirm that all components of an assembly or package are present and of the proper type, and count features like holes or slots on a single part.

Positioning
Verify proper position, orientation, and seating of many components, guide an industrial robot arm to correctly pick and place targets, or confirm the marking position of a KEYENCE laser marker.

Measurement
Measure in the X, Y, and Z planes to accuracies as small as ±10 μm.

Code Reading
Combine KEYENCE machine vision and inkjet printers to easily print and confirm date and lot codes with the help of an OCR (optical character recognition) built-in library, then compare to the read data of a bar code by simply checking a box.

What types of cameras are available?

KEYENCE's machine vision lineup consists of area camera, line scan, and 3D imaging technologies:

Area camerasare the most commonly used, and will solve the majority of vision applications.

Line scan camerasbuild 2D images one line at a time, sort of like a scanner, and are useful when images of large products, cylinders, or continuous webs are needed. Either the camera or part must be in motion during capture.

3D camerascapture industry-defining images of small parts with variable surface conditions. Simultaneous 2D and 3D capture allows for stable measurement in three planes.

What components make up a machine vision system?

Machine vision systems are made up of cameras, lenses, lighting, and image processing units. Each component is selected according to the application:

Camera
KEYENCE CMOS image sensors convert light into digital image data, to be sent to the controller in as little as 2 ms.

Lens
Lenses are used to focus the light onto the camera's image sensor. KEYENCE's high-resolution, low-distortion lens options ensure stable inspection across the whole image.

Light
光的选择是至关重要的任何机器视觉configuration; what the camera can't see, a machine vision system cannot inspect. The shape, size, and color of lighting, as well as installation distance and angle, can all be optimized to emphasize the features being inspected, and prevent any influences by the surrounding environment.

Image Processing Unit
Image processing units, or controllers, use pre-defined algorithms to process the image data and extract the important information.

Why use a line scan camera?

Line scan cameras are used to capture images of moving parts one line at a time. Individual lines are stacked one atop the other in an image processing unit to ultimately build a 2D image. This style of image capture makes line scan particularly well-suited to inspections of continuous webs, cylinders, and large parts. Read on to find out why, or clickherefor more information:

Continuous Webs
Line scan cameras capture lines at either a specified rate, or according to an encoder's output. "Continuous" capture can be maintained without interruption, so that from one image to the next, 100% of a continuous web has been captured and inspected.

Cylinders
使用传统的区域摄像头设置,必须至少拍摄三张图像,以查看圆柱体周围的整个360°表面。此外,由于弯曲的表面,零件特征可能会变形或难以均匀。使用线条扫描摄像头,整个圆柱体都以一个“未包装”图像捕获,没有任何毁容。

Large Parts
Since images are built in pieces, high-resolution images can be captured and transferred more quickly than an area camera of similar size. For example, a KEYENCE line scan camera can capture images up to 67 MP at speeds of 6.1 μs/line. Additionally, lighting is much easier. Only one line across a large part needs to be illuminated at once, rather than the entire target.

Why use a 3D camera?

3D cameras are used to inspect features which can't be seen with a traditional camera, or require manual inspection. What differentiates them from other technologies is their use of height data to create contrast, instead of color, so that precise inspection can be completed even on low-contrast parts. KEYENCE's 3D cameras simultaneously capture 2D image data, without the need for external lighting, so that measurement can be performed in all three planes; X, Y, and Z. Go to our product pages to learn more.

Pattern Projection lighting– 2D & 3D inspection

XT Series- 2 d和3 d测量

RB Series– 3D Vison-Guided Robotics

The World's Most Complete Vision Lineup

KEYENCE is proud to offer the most complete machine vision lineup of any automation supplier, from vision sensors with integrated lighting, to modular vision systems supporting area cameras, line scan and 3D cameras, and laser profilers. Award-winning hardware and advanced software algorithms combine to make KEYENCE machine vision the most stable solution for appearance and defect inspection, counting, positioning, measurement, and code reading applications; while built-in troubleshooting and maintenance tools speed up installation and decrease down-time. Explore this page for industry and application specific examples, or to learn more about any of our current vision technologies.

Our Latest Machine Vision Technologies

Our Machine Vision Platforms

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Machine vision has now become necessary in automation to improve efficiency and throughput by detecting defects and eliminating scrap.

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