Cold extrusion is a process used in the manufacture of many
automotive parts. Before the parts can be assembled, however, they must undergo
rigorous inspection to determine whether any surface defects or geometric
deviations exist. While conventional approaches may use machine-vision systems
programmed to analyze specific defects, these systems are inefficient when
small batches of very different parts must be examined.
To address the task of geometric deviations, the Fraunhofer
IPA (Stuttgart, Germany; www.ipa.fraunhofer.de) has developed a system that
uses known good models of parts and compares them with image data from parts
under test. In this way, the system can rapidly learn the surface profile of
new parts. A defect-surface map of the part under test can then be displayed.
“To deploy this system in a production environment,” says
Markus Hüttel of Fraunhofer IPA, “parts are first fed from a linear conveyor
and placed onto a rotary table by eight grippers that hold each part in place.
By indexing the rotary table in 45º increments, each part is successively
positioned under an imaging station. To obtain a surface map of the part under
test, the part is illuminated with a Lasiris line laser from StockerYale
(Salem, NH, USA; www.stockeryale.com). Using a motorized stage at the base of
the imaging station, the part is rotated, and several hundred images of the
reflected laser light are captured by a Ranger C camera from Sick IVP
(Linköping, Sweden; www.sickivp.se). From the gray-scale images the camera
extracts the laser line of highest intensity and transfers this 2-D information
to a host PC using a Camera Link frame grabber.
“Because the displacement and angle between the laser and
camera system are known,” says Hüttel, “it is possible to use the profiles
captured by the camera to determine the distance at which the laser light meets
the surface of the part.” This calculation is performed by the host PC using a
Camera Link frame grabber. The 3-D data are represented in the PC memory as a
linescan intensity data stream, except that the pixel value corresponds to
height instead of gray scale.
Once captured, the linescan intensity data are compared with
information from a known good part using Fraunhofer’s host-resident
machine-vision software-EMSIS. The resulting pseudocolored image is displayed
on the monitor of the host PC.
“In many applications,” says Hüttel, “it is also necessary
to capture a visible image of the part so that specific defects such as cracks
can be analyzed.” To accomplish this, the Fraunhofer system also incorporates a
linescan camera from Schäfter + Kirchhoff (Hamburg, Germany; www.sukhamburg.de)
that captures brightfield images of the part as it rotates. Gray-scale image
data from the camera are digitized by another PC-based frame grabber (also from
Schäfter + Kirchhoff), and the image data are reconstructed in the PC as a
visible surface map of the part under test. The software, also developed by the
Fraunhofer IPA (DefDetect), is based on texture analysis and detects defects on
structured surfaces.
“By using two cameras,” says Hüttel, “it is possible to
compare a very-high-resolution surface map of the part and its corresponding
visible image on the same display. To let OEMs take advantage of the DefDefect
surface-reconstruction software in the system, Fraunhofer offers a DLL that can
be used with
the Institute’s own EMSIS machine-vision software package.
This DLL will also be offered in other commercially available machine-vision
packages, including Neurocheck from NeuroCheck (Remseck, Germany;
www.neurocheck.com) and Coake from Sirius Advanced Cybernetics (Karlsruhe,
Germany; www.sac-vision.net).
At the Fraunhofer IPA, a variation of the system also has
been developed that replaces the linear conveyor and rotary table with a RV/3AL
robot from Mitsubishi (Ratingen; Germany; www.mitsubishi-automation.com/robots.html).
Designed primarily for demonstration purposes, the robot’s motor controllers
are manipulated from the system’s host PC over an Ethernet interface using
Mitsubishi’s MELSOFT programming interface.
“By using a robot instead of a fixed rotary table,” says
Hüttel, “the system can be adapted for applications where parts oriented at
random may need to be positioned in fixed inspection stations for defect
analysis.”
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