10.09.2018 Views

WORLD OF INDUSTRIES 06/2018 (RU)

WORLD OF INDUSTRIES 06/2018 (RU)

WORLD OF INDUSTRIES 06/2018 (RU)

SHOW MORE
SHOW LESS
  • No tags were found...

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

Many cameras are available in housings rated to IP65/67 which<br />

effectively protects against dust, dirt, water splashes or vapours<br />

In 3D measurement systems the change in geometry of the 3D<br />

sensor will generate errors, unless the sensor’s calibration has<br />

temperature compensation included. Many other environmental<br />

conditions can be addressed by choosing the optimum components.<br />

For example vibration & shock – many modern cameras are<br />

designed with high resistance to vibration and shock. Robot or<br />

track-grade cables are available for applications where the camera<br />

moves. Lockable connectors prevent them being dislodged by<br />

vibration. Ruggedised PCs and embedded computers offer good<br />

mechanical stability. Fixed focus lenses in metal mounts with<br />

lockable screws provide shock and vibration protection. Filters can<br />

provide simple protection of the lens surface.<br />

Or what about dust, dirt and water? Many cameras are available in<br />

housings rated to IP65/67 which effectively protects against dust, dirt<br />

and water splashes. Dust, dirt, liquids or vapours can stick to the LED<br />

or the surfaces of the lens system, reducing the light reaching the<br />

sensor. This can be overcome by increasing the camera gain, by software<br />

processing of the image or by adjusting the output of the LED.<br />

These and other factors affect the quality of the images produced<br />

by the sensor which is critical since these images are used for the<br />

actual measurements.<br />

Making measurements<br />

Machine vision measurements are handled according to the system<br />

configuration. Smart cameras have image acquisition, processing<br />

and analysis capabilities embedded within them. Compact embedded<br />

vision systems designed for demanding machine vision and<br />

automation applications requiring multiple cameras provide image<br />

acquisition, processing and analysis capabilities within the processing<br />

unit. PC-based systems will have the software on the PC.<br />

The accuracy and repeatability of results depends on the particular<br />

software algorithms used and their sub-pixel accuracy.<br />

High quality software products and libraries often provide more<br />

robust software tools than cheaper or open source systems, but<br />

often differences can only be evaluated by direct comparison and<br />

with varying inspection environments. Today’s vision systems can<br />

even tolerate a limited degree of variation in product size and<br />

shape, and can recognise classes of natural product with their<br />

inevitable variations within them. Even with the most robust vision<br />

system, however, external influences can lead to poor measurement<br />

results. For example, vibrations can lead to blurry images,<br />

while variable part feeding could lead to variable image perspectives.<br />

Motion blur can arise when using too long an exposure time<br />

to image moving objects.<br />

What you see is not what you get<br />

One pitfall for the untrained machine vision user is the significant<br />

difference between the human eye and the image acquisition<br />

system. Eyes automatically adjust to deal with apparent significant<br />

dynamic range while a fixed camera is unable to see significantly<br />

bright and dark areas at the same time. Sunlight through a roof light<br />

or a shadow of a tall machine operator can change a camera’s<br />

images image where the human eye would compensate without<br />

you even knowing.<br />

Planning and specifying a machine vision system<br />

Planning, specifying and implementing a machine vision system<br />

that is fit for purpose should involve more than simply choosing the<br />

most robust machine vision components. One way is to make use of<br />

the VDI/VDE/VDMA 2632 series of standards for machine vision,<br />

published by the VDI/VDE Society Measurement and Automatic<br />

Control, developed in conjunction with VDMA Machine Vision in<br />

Germany. Following the VDI/VDE/VDMA 2632-2 process not only<br />

allows the determination of an optimised solution but ensures that<br />

if proposals are sought from several suppliers, they all follow the<br />

same terms and definitions and use a consistent terminology. This<br />

allows exact ‘like for like’ comparisons to be made.<br />

To raise awareness of how the VDI/VDE 2632-2 standard can help<br />

to smooth the successful integration of machine vision into production<br />

equipment, Stemmer Imaging holds a number of training<br />

courses, in association with the European Imaging Academy. These<br />

are ideal for end users looking to embark on a machine vision<br />

project, as attendees will learn what questions to ask suppliers, how<br />

to evaluate proposals and understand the completeness of any proposal.<br />

In this way, users can be confident that they will get a truly<br />

robust vision system.<br />

Photographs: 01 Courtesy Gefra, 02 Stemmer Imaging,<br />

ornaments fotolia<br />

www.stemmer-imaging.com<br />

Machine vision systems<br />

consist of several component<br />

parts, including illumination,<br />

lenses, camera, image acquisition and<br />

data transfer, and image processing<br />

and measurement software. All of<br />

them have to be planned and<br />

specified based on the<br />

application requirements.<br />

Mark Williamson<br />

<strong>WORLD</strong> <strong>OF</strong> <strong>INDUSTRIES</strong> <strong>2018</strong> 39

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!