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Infrared vision system detects missing lids

11 August 2010

While thermal imaging was once the preserve of high-end applications with large budgets, today’s technology is eminently affordable

However, while the technology itself has moved on, the food processing industry’s perception of thermal imaging is, to a large extent, rooted in its elitist past.

While thermal imaging was once the preserve of high end applications with large budgets, today’s technology is eminently affordable. However, whilst the technology itself has moved on, the food processing industry’s perception of thermal imaging is, to a large extent, rooted in its elitist past.

In many cases processors are still opting for traditional vision systems which do not have the flexibility nor the performance of an infrared alternative. And, in the view of systems’ integrator Thermascan, this is pity when the cost of both types of system is virtually the same.

Thermascan has earned itself a high reputation for applying successful thermographic vision systems in the food processing sector. The company uses the FLIR A-Series infrared cameras as the basis for its vision solutions and the principal reason for its choice is the product’s flexibility.

“The I-O ports on the FLIR camera enable it to trigger four separate alarms,” explains Thermascan’s Dave Blain. “It is also compatible with a broad range of third party software so, for example, we can use LabView to tailor a system to best suit the application.”

An infrared vision system certainly proved the best choice for a client of Thermascan that manufactures pre-packed food for the large supermarket chains. The products include pasta and rice salads packed in plastic, lidded bowls. Initially the company’s traditional visual camera-based system was employed for quality control on the packing line but it soon proved inadequate to the task.

The traditional system could not detect whether the lid had been successfully applied to the bowl. This inability caused considerable wastage as the next process is the application of a label to seal the product and identify its content. In the absence of a lid, the label came into direct contact with the food, instantly contaminating it.

As the vision system did not alert the operator to the error, the machine continued to run out of sync, resulting in food being scrapped and the production line needing to be reset. And for a volume food processor this is costly exercise.

Although visual systems can be used to detect lids the problem in this application was its thinness – a little over 10 microns – and also its transparency. The solution that Thermascan applied centred on the use of a FLIR A320 infrared camera, the first ever thermal camera to be GigEVision™ and GenICAM™ compatible and to feature a trigger/synchronisation capability. This fixed installation camera provides excellent live images via its 320 x 240 pixels detector.

In this application the FLIR camera effectively detects the minute difference in temperature between a salad bowl with a lid and one without. “We are looking a temperature variation of maybe just 1.5 to 2°C,” Dave Blain explains. “But this is a very effective and accurate way of determining whether the lid has been successfully applied.”

If the camera detects a missing lid through this thermal difference it activates an alarm and automatically stops the line allowing the operator to remove the defective product. In this way, only single products are scrapped - not entire batches - and any production downtime is substantially minimised.

The success of this system however was not just its detection ability. In addition to triggering the missing-lid alarm, the FLIR camera’s I-O ports allowed it to be easily linked to the established vision system. The combined arrangement therefore allows the food processor to detect automatically that the container has been accurately filled, the product profile is correct and the lid is in place in readiness for the label to be applied.

Dave Blain concludes: “The digital I-O connector on the camera can be used for various tasks in food processing. For example it allows us to link the output from the FLIR camera to a thermostat so that operating temperature can be automatically adjusted and of course the technology is also ideal for detecting if cooked food reaches optimum temperature. It’s immensely versatile.”


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