3D Visual Inspection for high-temperature objects has attracted more and more attention in the industrial and manufacture field. Until now it is still difficult to measure the shape of high-temperature objects due to the following problems: 1) the radiation and heat transfer through the air seriously affect both human and measurement equipment, so the manual measurement is not capable in this situation. 2) Because of the difficulties to handle the surfaces of the hot objects, it is hard to use artificial markers to align different pieces of data. In order to solve these problems, an automatic 3D shape measurement system for high-temperature objects is proposed by combing an industrial robot with a structured blue light 3D scanner. In this system, the route for inspection is planned with the cooled object and then executed automatically with the same object in hot state to avoid artificial operations. The route is carefully planned to reduce the exposure time of the measurement equipment under the high-temperature situation. Then different pieces of data are premapped during the planning procedure. In the executing procedure, they can be aligned accurately thanks to the good repeatability of the industrial robot. Finally, different pieces of data are merged without artificial markers and the results are better than methods with traditional hand-eye calibration. Experiments verify that the proposed system can conduct the inspection of forging parts under the temperature of 900°C and the alignment precision is 0.0013rad and 0.28mm.
KEYWORDS: Detection and tracking algorithms, Target detection, Calibration, 3D acquisition, 3D metrology, Binary data, Evolutionary algorithms, Cameras, 3D image processing, Digital filtering
Distributing coded targets on the measured object is a reliable and common method for achieving optimum target location and accurate matching of corresponding targets among multi-view images. The circular coded targets which based on a central circular target surrounded by a coded band is widely used in vision measurement. However, it is difficult to decode the coded target while the number of pixels in the coded band is small or the projection angle is large. Aiming at solve this problem, a detection algorithm using the gray gradient to get the central angles of each coded section was proposed. In this algorithm, an accurate ellipse detection which can get sub-pixel locations was adopted to extract ellipse centers, and some false ellipses whose error in the fit of best fit is large will be rejected. Then, gray gradients in the coded band are calculated to get the central angle of each coded section, and the coded target will be decoded accurately. The experiment results show that the algorithm can locate and identify coded targets accurately under complex measurement conditions.
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