WORLD OF INDUSTRIES 06/2018 (RU)

Making machine
vision robust
AUTOMATION
What makes a machine vision system robust?
Robustness in this context is more than just reliability.
It is a reliability that is maintained within the natural
variations of the environment in which the system is
being used.
number of factors come into play here, including influences
A from the surrounding environment, object variations and
machine vision component effects. Choosing the optimum components
for a machine vision system is therefore a challenging task
and benefits from the knowledge and experience offered by
machine vision systems integrators and specialist suppliers. There
is a very large difference between a solution that works in a demonstration
lab environment and one that deals with all the variations
that an industrial environment will expose the system to.
Machine vision requirements
Machine vision systems consist of several component parts,
including illumination, lenses, camera, image acquisition and data
transfer, and image processing and measurement software. The
capabilities offered by machine vision have grown exponentially as
technology continues to deliver improved performance in all areas.
Author: Mark Williamson, Stemmer Imaging, Puchheim, Germany
The overall complexity of the system is determined by the specific
application requirements. Choosing the optimum components for
a robust vision system should be based not only on their ability to
achieve the required measurement (appropriate resolution, frame
rate, measurement algorithms etc.) but also on external machine
and environmental influences and conditions. Especially in an
industrial environment, these can include part variations, handling,
positioning, the process interface, vibrations, ambient light, temperature,
dust, water, oil and electromagnetic radiation. For extremely
hostile environmental conditions, it may be necessary to utilise
specialist housings to protect machine vision components. A common
example would be the use of camera housings in hygienic
environments that require washdown capability. However, there are
many applications where various environmental conditions can be
accommodated using the most appropriate ‘off the shelf’ components.
The environmental challenge for components
The challenges posed by external factors can have implications both
in terms of potential damage to the machine vision components
themselves, and the effects that they might have on the actual measurements.
This is perfectly illustrated in considering a vision system
that has to cope with temperature variations. Many modern cameras
are built to work in temperatures as low as -5 ˚C or as high as 65 ˚C
without damage. However, increased temperatures can lead to more
noise in the image from the camera sensor, but this can be countered
by ensuring that sufficient illumination is used to improve S/N.
It is also important to recognise that temperature could affect the
object being measured. For example, temperature effects can cause
expansion or contraction particularly in metal components, leading
to variations in their actual linear and volumetric dimensions.
38 WORLD OF INDUSTRIES 2018