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ifm O2D Object Recognition

The ifm O2D object detection sensor is used for presence, completeness, position, and quality control. The sensor offers rotation- and position-independent contour detection with an intuitive, user-friendly operation. It is a stand-alone device with integrated illumination and Ethernet interface for data transmission.

0 px

Max. Operating Distance

50 - 2,000 mm

Technical Questions

€1,092.90 excl. VAT.

From 200,00 € a month with lease buy or installment.

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Innovation and quality in the automotive industry

In the automotive industry, the most modern production technologies are used. Coordinated systems consisting of machining centers, transport systems, and industrial robots enable cost-effective, large-scale production and at the same time meet the customer’s individual equipment requirements.

Optical type recognition of car bodies and components

The complex variety of parts places high demands on logistics and production. Vision sensors of the O2D series help to maintain an overview and ensure quality by detecting structural parts.

Contour Sensor

The vision sensor O2D can recognize and assign previously taught objects and their contours or structures for the purpose of checking for completeness, position, and rotational position.

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Field of view20
Min. Operating Distance50 mm
Max. Operating Distance2,000 mm
Max. FPS20
Resolution640 x 480

The ifm O2D object detection sensor with rotation position independent contour detection solves tasks like presence, position, and quality control, as well as sorting and counting tasks. It is optimally suited for applications with recurring and fixed object contours. 
The sensor captures the contour image of the part to be inspected and compares it with the contours of one or more models in a reference image. The rotational position-independent object detection compares the test object with the specifications and sends results of "good" / "bad" to the higher-level PLC, including position and rotational position. The parameterization can be done at the device level or via an easy to understand, step-by-step parameterization software tool. 

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