B&R introduces lighting system for its machine vision solution
29 November 2018
B&R’s integrated vision system features innovative lighting components. The flexible light bars and backlights ensure optimum results even in difficult lighting situations.
Lighting control is synchronised with the automation system in the sub-µs range.
As integral parts of the automation system, both cameras and lighting are easy to synchronise with other sensors, motor positions and events in the machine application. Lighting control with microsecond precision is even guaranteed when synchronising multiple cameras and light sources.
Broad spectrum of possibilities
The flexible light bars are available individually or arranged as ring lights in groups of four, six or eight. The backlights are available in two sizes. Each light can feature up to four different LED colours at a time. The selection ranges from white and various visible colours to infrared and ultraviolet. This makes it possible to achieve just the right contrast, colour, illumination and intensity for any application.
B&R's light bars feature electronic angle adjustment from -40° to 90°. When producing multiple products on the same machine, the lighting angle can be optimised between batches – once it has been set, it can be saved as part of the batch recipe.
Configuration at runtime
All other lighting parameters can also be configured at runtime to optimise illumination or adapt to new products. Combining LEDs of different colours makes it possible to adjust the wavelength at runtime to optimise contrast.
The eye of the machine
B&R has seamlessly integrated machine vision into its automation system. The portfolio includes intelligent cameras, quality lenses, flexible lighting and powerful image processing algorithms. The high degree of integration can be found at every level of the B&R system, with machine vision fully incorporated into the engineering tool, real time operating system and machine application. Any automation engineer is now able to implement a large portion of machine vision applications on their own.
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