Neural nets inspect welding tip probes
FEBRUARY 10, 2009--Neural-net technology has progressed to a point where it can handle decisions in which a human would use subjectivity.
FEBRUARY 10, 2009--Neural-net technology has progressed to a point where it can handle decisions in which a human would use subjectivity. Moreover, modern neural technology builds in mechanisms that make it easier to see the role specific inputs play in generating a given output. An example of such advances comes from Neural ID (San Mateo, CA, USA; www.neuralid.com).
The firm has devised what's called Cure, for Concurrent Universal Recognition Engine. The technology uses neural-network concepts to recognize patterns. In contrast to earlier methods, the Cure technique builds-in ways of deducing how specific inputs lead to specific outputs. According to Neural ID, Cure has proven to be better than ordinary machine-vision methods at recognizing "good" and "bad" cases in conditions characterized by a lot of variability.
One of the first applications of the technique is in recognizing whether or not welding electrode tips that have been through a dressing process are acceptable for use. Conventional machine-vision processes have proven unable to manage the subjective nature of the good/bad tip decision and also struggle with scene variations caused by factors such as debris in the weld cell and different lighting conditions. A Cure-based Weld Tip System, distributed by Orbitform Group (Jackson, MI, USA; www.orbitform.com), recently came on the market and is now deployed in several spot-welding applications. For more information, go to: http://machinedesign.com/ContentItem/73360/MachineVisionIndustryFocusNewWaytoLookatMachineVision.aspx
