A modern heavy plate rolling mill can process more than 20 slabs and plates simultaneously. To avoid material
confusions during a compact occupancy and the permanent discharging and re-entering of parts, one must know
the identity and position of each part at every moment. One possibility to determine the identity and position of
each slab and plate is the application of a comprehensive visual-based tracking system. Compared to a tracking
system that calculates the position of a plate based on the diameter and the turns of the transport rolls, a visual
system is not corrupted by a position- and material dependent transmission slip.
In this paper we therefore present a vision-based material tracking system for the 2-dimensional tracking of
glowing material in harsh environment. It covers the production area from the plant's descaler to the pre-stand
of the rolling mill and consists of four independent, synchronized overlapping cameras. The paper first presents
the conceptual design of the tracking system - and continues then with the camera calibration, the determination
of pixel contours, the data segmentation and the fitting & modelling of the objects bodies. In a next step, the
work will then show the testing setup. It will be described how the material tracking system was implemented
into the control system of the rolling mill and how the delivered tracking data was checked on its correctness.
Finally, the paper presents some results. It will be shown that the position of some moving plates was estimated
with a precision of approx. 0.5m. The results will be analyzed and it will be explained where the inaccuracies
come from and how they eventually can be removed. The paper ends with a conclusion and an outlook on future work.
The environmental conditions at hot strip mills are characterized by hot objects (up to 1100 °C), dust and dense steam. Conventional methods for characterizing product parameters fail in these unfavorable measurement conditions. An alternative is optical measurement technique. It is non-contact and can be positioned in a safe location in the plant. One parameter of interest at hot strip mills that is to be observed is the geometry of the transfer bar. During the reduction of thickness of the stock in several reversing passes a deviation of the straightness, a so-called camber, can occur. This distortion can cause disturbances at the following steps of production, e.g. at the finishing mill. The value and direction of the camber is determined by means of a CCD-matrix camera and a segmented capture of the shape. The unique character of the measuring system discussed in this paper lies in the use of a single camera system to meet the requirements in contrast to other systems using two or more cameras. In the rolling process of the roughing mill with varying speed additional phenomena like lateral shift and rarely twist can occur, which make the measurement more difficult. Lateral movements of the strip are taken into consideration by checking single edges twice, the twist can be neglected. Finally the results of the camber values are statistically evaluated. One significant result shows the influence of the arrangement of stocks in the pusher-type furnaces on the camber. The results of the measurement are helpful for understanding the rolling process in more detail and even to take measures to avoid cambers and improve quality and process stability.
Precision rolled strips are often intermediate products in the manufacturing of blades. In such cases the shape and size of these strips are essential to the functionality and quality of the blade and cutting workpiece. Although precision strips are normally produced in heavily automated rolling mills, their size and shape are still inspected manually with profile gauges and microscopes. In this paper we present a measurement setup with multiple light-sectioning systems, which is suitable for the inspection of all sides of a profiled strip. It consists of three measurement heads, which are used to inspect the upper side, the lower side and the back of the blade. The heads are calibrated individually; the focus of the work here is to determine the relative position and orientation of the heads with respect to each other. The first approach has been developed to reference two or more measurement heads. The calculation of the required transformations is based on the rotation of a suitable target. Due to the small depth of field, the location of the rotation axis must be pre-adjusted very precisely. To improve the accuracy and to simplify the process, a second referencing method was developed. The required target was manufactured by means of a 5-axis high speed milling machine and features a thickness tolerance of less than 1 micron. Both the referencing method and target are presented. Additionally, we demonstrate the all-side inspection of a blade. It will be shown that the approaches allow a robust and flexible referencing of multiple measurement heads to each other.
The design of edges is very important for many components. In
this paper we therefore present a light-sectioning based
measurement head, which is suitable for the edge inspection of
different workpieces. Beyond the design we also present a new
calibration technique for its camera. The calibration is mainly
based on several perspective projections, which are successively
executed. In each step, the linear system of homogeneous
equations is solved by using singular value decomposition. Each
mapping is therefore obtained in the least squares sense. Because
of the novel design of the calibration device, a high number of
reference points can be used for the description of these
mappings. The inspection of a workpiece detail implicates a large amount of data, some of which is useless. To extract the data essential for the fitting routines, a special correlation/regression based template matching is proposed. After the description of the
segmentation process we propose a measurement progression, which
enables us to obtain a fast and easy perspective correction of the
three-dimensional light sectioning data. Finally, a fitting method
is presented. Based on singular value decomposition, the data is
fitted to the corresponding form of the fillet or chamfer. As the
fit is done in the least squares sense, one can obtain statistical
information out of the decomposition process.