SENSORS: COLOUR RECOGNITION
measurement system, resulting in only a low batch sample being measured.” Greyscale detection and high colour
accuracy are combined with user-friendly operation and configuration using pushbuttons and a display. A multi-teach function enables up to 320 colours in 254 colour groups to be saved, as well as the teaching of reference colours and tolerances. Illumination, averaging and signal amplification are automatically adapted to the current measurement task. “Integrated into production processes,
the sensors can continuously monitor 100 per cent of products produced. This can lead to dramatic improvements in automated inspection, quality control, production efficiencies and product quality, while also reducing operational costs and waste,” adds Jones.
Joined-up colour sensing
Jonathan Newell finds out more about Micro-Epsilon’s range of colour recognition sensors with high measuring rate, good reproducibility and modern communications interfaces designed for high precision true colour measurement in industrial applications
M
icro-Epsilon’s true colour sensor range is suitable for colour sorting tasks in food and beverage processing, colour inspection of interior parts in
the automotive industry and the recognition of colour marks in the printing industry as well as quality control in packaging, cosmetics, medicine and plastic products. The sensors project a modulated high-
power white light LED light spot via optical fibre onto the target surface to be inspected. Part of this light is back- scattered and directed onto a perceptive True Colour detector via the same optical fibre. This light is then refracted into long-, medium- and short-wavelength light components (X=long, Y=medium, Z=short) and transformed into L*a*b* colour values. High colour accuracy, good
reproducibility, high light power (>220 lm) and a fast measuring rate of up to 20kHz enable the sensor to reliably detect the finest of colour graduations, even in high- speed measurement tasks and on poor reflecting surfaces. Equipped with optical fibres and focus lenses, the sensor can also be used in confined areas, as the sensor head requires minimal space. Chris Jones, managing director at Micro-
Epsilon UK, comments: “The accuracy of most inline colour sensors in the marketplace are typically defined with a E of 1-1.5, which represents similar performance to the human eye. CFO200 sensors offer a E of 0.6 at a very competitive price level. This will enable more applications to be solved in-process, measuring 100 per cent of produced parts that previously would have to be measured offline by a high-performance
INDUSTRY 4.0 READY According to Micro-Epsilon, the company’s colorSENSOR CFO100 and CFO200 models are equipped with both RS232 and Ethernet communication interfaces for easier network integration and Industry 4.0 capability. Such connectivity fulfils the growing
requirements for devices, such as sensors, on the edge of the network to possess some processing capability and be able to communicate across the industrial network. When asked to define the sensor range’s
Industry 4.0 readiness, Jason Biddulph, internal sales and support engineer at Micro-Epsilon UK, told us: “The CFO 100/200 Industry 4.0 capabilities can be summarised in four important categories, namely inter-operability, data logging, intelligence and functionality.” Inter-operability: with several output
options, including EtherCAT, the CFO can connect and communicate with multiple machines, devices or systems. Data logging: the CFO100/200 sensor
and software is capable of taking real time data and storing/exporting it to other devices or to a back up file. Intelligence: the CFO 100/200 has the
ability to solve problems and algorithms autonomously, making decisions in most cases faster than a human, and in others completing tasks that a human cannot. Functionality: the CFO 100/200 can
be easily programmed through web interface software or the push buttons on the sensor. EE
❱❱ To read more on sensors and instrumentation online, scan the QR code or visit
https://goo.gl/eiY7pH
June 2018 /// Environmental Engineering /// 35
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