Cold rolling mill thickness control using the cascade-correlation neural network

The improvements in thickness accuracy of a steel strip produced by a tandem cold-roIling mill are of substantial interest to the steel industry. In this paper, we designed a direct model-reference adaptive control (MRAC)  scheme that exploits the natural level of excitation existing in the closed-loop with a dynamically constructed cascade-correlation neural network (CCNN) as a controller for cold roIling mill thickness control. Simulation results show that the combination of a such a direct MRAC scheme and the dynamically constructed CCNN significantly improves the thickness accuracy in the presence of disturbances and noise in comparison with to the conventional PID controllers.

Fault detection in a cold forging process through feature extraction with a neural network

This paper investigates the application of neural networks to the recognition of lubrication defects typical to an industrial cold forging process employed by fastener manufacturers. The accurate recognition of lubrication errors, such as coating not being applied properly or damaged during material handling, is very important to the quality of the final product in fastener manufacture. Lubrication errors lead to increased forging loads and premature tool failure, as well as to increased defect sorting and the re-processing of the coated rod. The lubrication coating provides a barrier between the work material and the die during the drawing operation; moreover it needs be sufficiently robust to remain on the wire during the transfer to the cold forging operation. In the cold forging operation the wire undergoes multi-stage deformation without the application of any additional lubrication. Four types of lubrication errors, typical to production of fasteners, were introduced to a set of sample rods, which were subsequently drawn under laboratory conditions. The drawing force was measured, from which a limited set of features was extracted. The neural network based model learned from these features is able to recognize all types of lubrication errors to a high accuracy. The overall accuracy of the neural network model is around 98% with almost uniform distribution of errors between all four errors and the normal condition.

Deformation behaviour of ultrafine grained steel produced by cold rolling of martensite

An ultrafine grained Nb microalloyed steel was produced by cold rolling of martensite followed by annealing heat treatments at different times to study its effect on the microstructure and mechanical behaviour of the ultrafine grained steel. High strength was achieved by this thermomechanical processing due to the formation of cell and subgrain dislocation substructure; however annealing reduced both strength and elongation.

Modeling and control of flatness in cold rolling mill using fuzzy petri nets

Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.

Changes of microstructure in alpha AgZn during post-deformation annealing after cold-rolling

The annealing processes of deformation-induced defects after cold-rolling to about 30 and 60% thickness reduction were investigated for Ag-21, 23, 28 at% Zn by means of residual electrical resistivity, microhardness, light microscopy and transmission electron microscopy (TEM) Three annealing stages have been detected and consistently interpreted as annealing-out of mainly point defects and their agglomerates (stage I), formation of dislocation cells and recrystallized strain-free grains (stage II) and grain growth (stage III). Further, it is tried to determine the evolution of defect production (point defects and dislocations) during rolling deformation from measured changes of electrical resistivity and microhardness. Copyright (C) 1996 Acta Metallurgica Inc.

Effect of cold-working process on corrosion behavior of copper

The microstructure, microhardness, texture and corrosion resistance of cold-swaged and cold-wiredrawn copper rods were evaluated. Elongated grains along the deformation direction were observed for both materials and the width of these grains decreased with the increase of reduction in area. Wiredrawn copper rods have higher microhardness than the swaged rods for the same reduction in area. The copper grains in both cold-worked rods presented a preferential orientation in the [1 1 0] crystallographic direction but this trend was more pronounced for swaged rods. The corrosion resistance of wiredrawn copper rods investigated in H(2)SO(4) solutions was lower than that of swaged rods, and for both deformed materials the corrosion resistance decreased with the deformation degree. (C) 2011 Elsevier Ltd. All rights reserved.

Texture analysis of cold rolled and annealed aluminum alloy produced by twin-roll casting

A 7.4 mm thick strip of 3003 aluminum alloy produced by the industrial twin-roll casting (TRC) process was homogenized at 500 °C for 12 hours, after which it was cold rolled in two conditions: 1) to reduce the strip's thickness by 67%, and 2) to reduce it by 91%. The alloy was annealed at 400 °C for 1 hour in both conditions. The results revealed that a rotated cube texture, the {001}<110> component, predominated in the as-cast condition and was transformed into brass, copper and S type textures during the cold rolling process. There was practically no difference between the deformation textures at the two thickness reductions.

Corrosion Characteristics And Mechanical Properties Of Aluminum Coatings Applied By The Cold Spray Process

Aluminum coatings were applied to 2024-T3 and 7075-T6 aluminum alloys via the Cold Spray process. The coatings were applied to substrateswith various surface preparation and Cold Spray carrier gas combinations. Some samples were coated with an additional sealant with and without a chromate conversion layer. An exhaustive corrosion analysis was then performed which utilized a number of long termand accelerated tests in order to characterize the corrosion protection of the coatings.