Page 48 from: March 2016

48 March 2016
S E N S O R – B A S E D S O R T I N G
new ejection principle can contribute to better
sorting performances’, Rauch stressed.
The new method developed by MaB can be
described as a ‘mechanically articulated bridge’.
The patented system is characterised by a down-
stream orientated bridge device; the bridge ele-
ments are opened when the optical sensor rec-
ognises a chosen item – for example, newspaper
rather than plastic bottles.
This allows the machine to remain closed when it
encounters what it is programmed to let pass – say,
plastic bottles – so that they fall onto the conveyor
belt directly below the screening platform. The
desired materials – that is, newspapers in the test
project – are re-routed via the now open arm of
the system and fall onto a different conveyor belt.
‘It is important that there is a seamless con-
nection between the screening area and the
wbridge arms so that no material can get stuck
in the cracks,’ Rauch noted. ‘We have achieved
a smooth path to the conveyor belt in our pilot,
so we know this is definitely possible.’
While a pneumatic ejection system has to ‘shoot’
on to a gravity centre to optimise the removal
movement and while a robot hand has to ‘know’
the item form in order to grab it effectively, nei-
ther is required for the mechanically articulated
bridge, Rauch observed.
This new solution would be a suitable alterna-
tive for sorting materials of a limited height and
weight, and also materials that are relatively
wet or have a rough surface, according to the
speaker.
The profitability and maximum efficiency of the
new system would be proven, he added, once
tests confirmed the time needed to move and
retract the bridge arms, together with the aver-
age energy consumption. The latter, however,
wouldn’t be too high as the only energy needed
is the indirect help afforded by an electrical or
hydraulic cylinder opening/closing the indi-
vidual bridge sections.
‘Bag of visual words’
‘Classification is a core task when sorting bulk
materials, leaving objects to be either accepted
or rejected based on features as programmed
by the engineer,’ said Matthias Richter of the
Fraunhofer Institute. ‘While successful in the
past, this approach is reaching its limits. More
challenging tasks and complex objects call for
automated methods to learn how to interpret
the data intelligently via precise pattern recog-
nition methods.’
Typically, the engineer has to manually input
the pre-defined feature descriptors of each kind
of material – such as colour, shape, length, etc.
With less clearly defined classes combined with
The patented system created by
Manufacture à Besançon is charac-
terised by a downstream orientated
bridge device; the bridge elements
are opened when the optical sensor
recognises a chosen item.
The more compact
the material flow, the
bigger the problem.’
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