The surface machining of cracks is a key issue to ensure the quality of steel rods and billets. The aim is to grind these defects out of the material. This paper presents a real-time optical servo-system, consisting of three image processing systems and an industrial robot, which fully automate this process. A high resolution color progressive scan camera, placed at a suitable position above the roller conveyor, observes the material and detects color markings indicating the presence of a crack. This camera system controls the roller conveyor transporting the material until a marked crack is detected. Diffuse light sources provide homogeneous lighting to ensure reliable detection of the markings. A demosaicing algorithm, RGB to HSL color modeling and thresholding with statistical morphology are used to identify the marked areas. On detecting a crack the material is automatically positioned within the working area of an industrial robot. A collineation is used to generate metric two-dimensional coordinates corresponding to the bounding rectangle of the detected error. At this point two plane-of-light scanners are used to acquire a cross section of the material to the left and the right of the robot's working area. From this, a three-dimensional model for the rod or billet surface is calculated and the two-dimensional coordinates of the color marking are projected onto this surface to generate a patch. The coordinates of this patch are sent to the 6R industrial robot, which then grinds out the defect. A new concept has been implemented which enables the calibration of the three image processing systems and the industrial robot so as to have one common coordinate system. Operational results have shown the full functionality of the system concept in the harsh environment of a steel production facility.
Recently developed mining machines are capable of cutting different profiles. Cutting desired profiles opens new fields of application for these machines. The precision of the profile, which is cut, depends on the kinematics of the machine and its calibration. The dimensions of the profiles up to 10 m wide and 5 m high make it difficult to calibrate and even measure. This paper presents an image processing system, which was developed to solve this problem. An ultra-bright infrared LED was mounted on the primary calibration point of the machine. The 2-R manipulator (i.e. the cutting arm) is moved so as to generate the desired outer profile. The 2-R kinematics of the machine result in the calibration point moving along the surface of a torus. The imaging system acquires a sequence of images, each of them captures the machine in one point along the profile. This delivers a 2-D central projection of the 3-D motion. The inverse projection is determined using projective geometry. The true position of the calibration points is determined by applying the inverse projection, which is then compared to the desired position. Measurements of a mining machine and a comparison with the desired profile are presented.