پديد آورنده :
اعلايي، حسين
عنوان :
بررسي تاج حرارتي غلتك در فرآيند نورد و تاثير آن برعيب موج ورق
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
طراحي كاربردي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مكانيك
صفحه شمار :
پانزده، [110] ص: جدول، نمودار
يادداشت :
ص. ع. به: فارسي و انگليسي
استاد راهنما :
محسن اصفهانيان
استاد مشاور :
محمود سليمي
توصيفگر ها :
پروفيل حرارتي , نورد گرم , غلتك كاري , اختلاف محدود , شبكه عصبي
تاريخ نمايه سازي :
27/10/88
استاد داور :
محمدرضا احمدزاده، محمود كدخدايي
چكيده فارسي :
به فارسي و انگليسي: قابل رويت درنسخه ديجيتال
چكيده انگليسي :
Investigation on Work Roll Thermal Crown In Rolling Process and Its Effect on Strip Shape Hossein Alaei h alaei@me iut ac ir Date of Submission 07 01 2009 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 8311 IranDegree M Sc Language FarsiSupervisor M Esfahanian assist Prof mohsen esfahanian@gmail comAbstract Profile and shape control are required to assure the dimensional quality of rolled strip Occurrence ofwaves either at the edges or centre of strips is attributed to inconsistency between the entry and exit cross section profiles of the stock within a given rolling pass The exit profile of the strip can be computed byconsidering that the profile is the complement of that of the roll gap which is affected by wear thermalexpansion and distortion of the work rolls An understanding of the thermal expansion of work rolls isessential to control the flatness of a rolled strip in a modern high speed rolling mill Thermal aspects of rolling process play an important role on the product quality and performance ofrolling equipments Inappropriate thermal crown causes to shape and geometry defect such as center buckle wavy edge or ridge buckle On the other hand it can increase the rolling force and the energy consumption Sheet and roll temperature can affect on production so mainly high temperature causes the fire crack on theroll surface and wear The aim of this study is to investigate the effects of the temperature on the quality of sheets For thispurpose analytical models are combined with neural network to predict the work roll temperature forapplication in the on line control programs In addition the metal structure as a display of the thermalhistory is analyzed to follow the origins of defects in the production process because non uniform coolingcan affect on structures and mechanical properties of the sheet In this study an analytical model based on finite difference method is used under transient conditionto calculate the temperature and thermal crown profile of the work roll The model has the ability ofaccepting variable boundary conditions in circumferential and axial direction for different coolingconfigurations such as using different types and numbers of nozzles and headers in different directions The results of simulation are compared and verified with an actual rolling program result for which thetemperature of a work roll was measured at Mobarakeh Steel Complex The results of this model are used to train and back up neural network so that it can cover outputdomain After preprocessing these data set are used to train verification and test of the neural network Regarding the large number of influential parameters in the work roll temperature input correlation ofnetwork is assessed and parameters with high correlation coefficients are removed Physical approach toinput and output of neural network can help us to reduce the network size and error significantly Considering the nature of data structure dynamic and static networks are trained and their results arecompared with each other The results show that the static networks for any roll layer converge to smallererror than the others These networks can predict current temperature field by considering the temperaturefield in the 35 points of roll as the thermal roll history The network inputs are sheet dimensions initialsheet temperature gap time between two passes and reduction in stands and outputs are the work rolltemperature field Key Words Thermal profile hot rolling work roll on line neural network
استاد راهنما :
محسن اصفهانيان
استاد مشاور :
محمود سليمي
استاد داور :
محمدرضا احمدزاده، محمود كدخدايي