Linear laser video recognition is a high-tech device that combines laser scanning technology and video processing technology. It uses a linear laser beam to scan the target object, receives the reflected light through the sensor, converts the light signal into an electrical signal or a digital signal, and then generates video image data that can reflect the surface characteristics and geometry of the object for subsequent recognition, analysis and other operations.

Optical system: including cylindrical objective lenses, lens groups, etc., used to diffuse, focus, or adjust the laser beam to a linear laser, and collect the reflected light, optimize the transmission and imaging quality of the light, and reduce stray light and optical distortion.

Image sensors, such as CCD or CMOS sensors, are responsible for converting the received optical signals into electrical or digital signals. Their resolution, frame rate, and sensitivity determine the image's clarity, acquisition speed, and adaptability to low-light environments.

Scanning device: controls the scanning path and speed of the laser line to ensure a comprehensive and uniform scan of the surface of the object. The scanning method can be mechanical scanning, electronic scanning or a combination of both.

Control and processing unit: usually composed of a computer, microprocessor, or dedicated controller, responsible for coordinating the work of various components, controlling scanning parameters, receiving and processing image data, and running recognition algorithms and software to analyze and judge objects.

Control and processing unit: usually composed of a computer, microprocessor, or dedicated controller, responsible for coordinating the work of various components, controlling scanning parameters, receiving and processing image data, and running recognition algorithms and software to analyze and judge objects.

High frame rate imaging: can achieve a high frame rate, capable of quickly capturing the motion state and changes of objects, suitable for the detection and tracking of high-speed moving objects.

Large field of view inspection: Through progressive scanning, it can cover a wide field of view, capable of detecting larger-sized objects or scenes at one time, improving detection efficiency, reducing the number of equipment and installation costs, and is often used in the surface inspection of large objects, logistics monitoring and other fields.

Non-contact measurement: No direct contact with objects is required, avoiding damage and contamination to the surface of the object, and it is also suitable for some occasions where contact measurement is not convenient, such as object detection in high temperature, high pressure, fragile or dangerous environments.

Strong adaptability: It has strong adaptability to environmental factors such as lighting conditions, ambient temperature, humidity, etc., and can work stably in complex and changeable industrial environments without being affected by surface characteristics such as object color and material. It has high reliability and stability.

Strong adaptability: It has strong adaptability to environmental factors such as lighting conditions, ambient temperature, humidity, etc., and can work stably in complex and changeable industrial environments without being affected by surface characteristics such as object color and material. It has high reliability and stability.

Data collection: The camera or sensor captures the light reflected by these laser lines that are deformed by the shape of the object, converts it into an electrical or digital signal, and records the pixel data of each row to obtain two-dimensional or three-dimensional information on the surface of the object.

Data processing and reconstruction: The collected large amount of pixel data is transmitted to the computer or image processing unit for complex geometric calculation and image processing. Through algorithm analysis, the three-dimensional space coordinates corresponding to each pixel are determined, and then the three-dimensional shape of the object is reconstructed or the two-dimensional image information is generated.

Recognition and analysis: With the help of artificial intelligence algorithms and software, the reconstructed or generated image data is further analyzed and processed to realize the recognition, classification, measurement, and detection of objects, such as recognizing the type of object, detecting the defect of the object, and measuring the size of the object.

Improve inspection efficiency: Fast scanning and imaging speeds, as well as automated identification and analysis functions, can greatly improve the efficiency and speed of inspection, reduce the workload and errors of manual inspection, and improve production efficiency and product quality.

Enhance inspection accuracy: With high-precision measurement and imaging capabilities, it is possible to accurately detect subtle defects, dimensional deviations, and other issues in objects, which helps to improve product consistency and reliability, reduce the rate of defective products, and enhance the competitiveness of enterprises.

Realize intelligent detection: Combined with artificial intelligence algorithms, equipment can automatically learn and recognize the characteristics of objects, continuously optimize detection results, realize intelligent detection and diagnosis, and provide strong support for industrial automation and intelligent manufacturing.

Data-rich and traceable: The large number of images and 3D data collected by the equipment can not only be used for real-time detection and analysis, but also for storage and traceability, providing valuable data support for product quality traceability, process optimization, failure analysis, and so on.

Integrated structure, with appearance patent; with anti-dust, anti-mud and other harsh environments, with self-cleaning system.