This allows for the stable detection of glossy aluminum vapor deposition packaging—simply install the Sensor directly above
Color Mark Photoelectric Sensor
about this Product Family
last update: July 06, 2016
This allows for the stable detection of glossy aluminum vapor deposition packaging—simply install the Sensor directly above
The included high luminance RGB three-color LED light emitting element drastically improves the light intensity. Meanwhile, Smart Noise Reduction technology in the Fiber Sensor is applied to reduce the amount of noise, resulting in a high dynamic range where the Sensor is not saturated even when detecting a mirror surface—without having to make any light intensity adjustments.
* Optical mirror and aluminum vapor deposition material measured at the distance with maximum incident level (13 mm); grayscale measured at the distance with minimum incident level (7 mm or 13 mm).
Stable detection even of similar colors with only minor differences
The high luminance white LED of the Fiber Amplifier Unit, and the high luminance RGB three-color LEDs and high efficiency optical system design of the Photoelectric Sensor deliver high power. "Smart Noise Reduction" (a light reception algorithm) and "N-Core" (a high-speed, high-precision IC) work together to dramatically reduce the effect of noise. Increasing the incident level and decreasing noise make it possible to obtain a high S/N ratio even when color differences are subtle.
Allowing support of packaging printing color variation, and helping to reduce downtime
RGB information for color marks and backgrounds for each lot is transmitted to a host and quantified. This information is then managed in a database, making it possible to set optimal thresholds and identify causes quickly if a problem occurs.
Until now, setting the threshold during commissioning required the knowledge of an expert. Now it is possible to get the optimal setting just by registering the RGB ratio of the packaging.
When the Sensor makes false detection, values can be checked to determine whether color variation from lot to lot in packaging material has occurred, making it easy to identify what has caused a problem and to then resolve it.
last update: July 06, 2016