Automotive industry in real time using digital image segmentatiom
Versandkostenfrei!
Versandfertig in 6-10 Tagen
49,99 €
inkl. MwSt.
PAYBACK Punkte
25 °P sammeln!
The image segmentation algorithm is the most challenging step and requires more computer processing power than the boundary filtering, and the Cullen et al's method, which used the Cullen et al's method to determine the electrodes tip width automatically in the automotive industry in real time Spot welding is used extensively in the automotive industry. The quality of an individual spot weld is a major concern due to the heavy reliance on their use in the manufacture of motor vehicles. The main parameters that control the quality of a spot weld are current, voltage, welding force, welding time...
The image segmentation algorithm is the most challenging step and requires more computer processing power than the boundary filtering, and the Cullen et al's method, which used the Cullen et al's method to determine the electrodes tip width automatically in the automotive industry in real time Spot welding is used extensively in the automotive industry. The quality of an individual spot weld is a major concern due to the heavy reliance on their use in the manufacture of motor vehicles. The main parameters that control the quality of a spot weld are current, voltage, welding force, welding time, and the quality of welding electrodes In order to determine the quality of the welding electrodes, a machine vision approach is employed, where images of the electrode tips in real time are captured and are processed using various image-processing algorithms. These algorithms can be used to automatically measure the electrode tip width and hence assess the quality of the electrodes tip in real time. The quality of two types of spot welding electrode tips, namely flat-shaped and dome-shaped tips, is assessed here using image processing techniques. For each tip type, a database of 250 images
Andere Kunden interessierten sich für
