iRAYPLE R7250MG-00C-NGG01E Pricing & Product Details
Ranked Nr. 304 of 126 2D Vision Systems
R7250MG-00C-NGG01E Pricing
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R7250MG-00C-NGG01E Overview
What is R7250MG-00C-NGG01E?
The iRayple R7250MG-00C-NGG01E, part of the R7000 Series, stands out with its advanced features tailored for industrial applications. It boasts a high-speed CMOS sensor with a resolution of 5120 × 5104 pixels, ensuring detailed and accurate image capture. This camera incorporates a global shutter mode, minimizing motion blur and distortion, making it suitable for high-speed imaging tasks in manufacturing and automation environments.
Equipped with a built-in deep learning algorithm, the R7250MG-00C-NGG01E enhances its efficiency in image processing tasks such as object recognition and quality evaluation. With support for software trigger, hardware trigger, and free-run modes, this camera offers flexibility in operation, catering to diverse automation requirements. Its GigE connectivity, providing up to 1Gbps bandwidth, ensures fast and reliable data transfer for real-time monitoring and control applications.
The R7250MG-00C-NGG01E features a rugged industrial design with an IP67-rated casing and aluminum alloy construction, ensuring durability in harsh industrial environments. With abundant I/O interfaces including RS232 and opto-isolated inputs/outputs, it facilitates seamless integration with other industrial equipment and systems. This camera is well-suited for a wide range of applications such as quality control, robotics, and object recognition in industries including manufacturing, logistics, and electronics.
What applications is R7250MG-00C-NGG01E product best for?
- Manufacturing Quality Control: The iRayple R7250MG-00C-NGG01E is tailored for precise quality inspection tasks in manufacturing, ensuring product integrity and adherence to standards.
- Robotics & Automation: With its high-speed capture and versatile trigger modes, this camera is well-suited for integration into robotic systems, enabling efficient automation processes.
- Object Recognition & Control: The built-in deep learning algorithm enhances the camera's capability for object recognition, making it ideal for applications requiring precise identification and control of objects in real-time.