EVT introduces Machine Learning-based EVT Scratch Inspector | Automation.com

EVT introduces Machine Learning-based EVT Scratch Inspector

EVT introduces Machine Learning-based EVT Scratch Inspector

June 24, 2019 - With the Machine Learning-based EVT Scratch Inspector, users can automate the detection of defects on surfaces. Based on a Deep Learning method, the Scratch Inspector detects any disturbance on the surface, similar to the human eye.

As standard the Scratch Inspector is available in three different illumination variations. Depending on the requirements, the illuminations can be adapted to the different sizes of the component parts.

The smart system has everything to integrate it directly into the plant. It has 8 in- and 8 outputs in 24 V technology to directly control a plant or to communicate with the PLC and the system is also equipped with a Profinet option. Therefore it is sufficient to connect the EVT Scratch Inspector to the PLC.

The system has the appropriate LED outputs to connect the illumination directly to the Scratch Inspector. The 24V power supply guarantees, that the Inspector can be run on a processor power supply.

Thanks to the sophisticated GUI it is possible to define test procedures. The on Machine Learning based algorithm, takes almost the complete configuration of the user.

The errors are either reported directly via I/O signal or an ejector is activated. Furthermore information can be sent via Profinet interface to the system control. Therefore the smart sensor is = integrated into an Industry 4.0 environment. A data base connection and a detailed statistic allows the user to directly display the detected errors.

The system can be run as stand-alone system as well as headless sensor, which can be remotely programmed as OIP (Optical Inspection Processor) and integrated into the plant.

An alternative is the EyeMulti-Inspector. This system is a setup where everything is integrated: camera hardware, processor and illumination. It can be positioned directly over the inspection location and all adjustments for camera, lens and illumination are included in the system.

Additionally, a tracker unit can eject the defect component parts at a defined position. To achieve that, the system has an incremental encoder input and several sorting outputs. So different quality classes can be created. The EyeMulti-Inspect is equipped with the same software as the Scratch Inspector. Due to a variance in illuminations it is also usable for other applications.

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