Strip tracking measurement and control in hot strip rolling

It is well known that poor strip tracking can lead to reducedproduct quality but also to mill delays. The resultingcosts for internal rejects, customer complaints and yieldlosses have historically been significant. Moreover, the severityof these issues increases dramatically when stripsbecome wider, thinner and harder. Ultimately the rollingprocess becomes completely unstable. Hence, to reducecost of poor quality for the current product mix as well asto enable product development it is vital that strip trackingis improved.Most strip tracking issues arise at the head or the tail ofthe strip. In the rougher mill the main issue is head camber,a shape defect of the bar where the head is curved. Aclear example of this shape is shown in Fig 1. Large headcamber of the transfer bar may result in further problemsdownstream in the finishing mill and should ideally thus beprevented.Another notorious problem closely related to strip trackingis tail pinching in the finishing mill. This is a phenomenonwhere the tail of the strip suddenly moves sideward’s andgets damaged right after it has left the previous stand. AnPoor strip tracking is one of the notorious problems threatening process stability in a hot strip mill. Theseissues often lead to tail pinching and in the worst cases even to cobbles. The main pillars of the strategy setout to tackle these issues for the Hot Strip Mills in IJmuiden are rougher mill camber control and finishing millstrip steering and tail control. For such applications, a camera based measurement system has been developedin-house that is simple, cost-effective and yet both accurate and robust. Moreover, as we show in this paper,the system has proven its merits both as a finishing mill interstand centerline deviation measurement aswell as a rougher mill camber measurement. In the latter application the measurement data can be used forautomatic levelling in the rougher mill. The results of production tests presented in this paper demonstrate thatthe camber measurement in combination with a basic rougher mill tilt set-up model is sufficient to reduce thetransfer bar camber significantly

Detection of slopping in basic oxygen steelmaking using a CMOS camera aimed at the converter mouth

In basic oxygen steelmaking foam overflow or slopping causes operational and environmental problems. In most steel plants however, slopping is neither detected nor recorded. In this paper a slop detection algorithm is presented, which is based on images taken by a CMOS camera aimed at the converter mouth. The proposed algorithm has accuracy and selectivity of 74% and 94% respectively, is relatively simple and can easily be used in on-line applications. When using this algorithm in the majority of the slopping batches, slopping is quickly detected and can be halted