Development Of Strip Rolling Simulation System Based On Bacteria Foraging Optimization

Intelligent manufacture technology is the mainstream of the current global industry research, and the intelligent algorithm is one of the core technologies about intelligent manufacture. Based on the illumination of natural law in practice, intelligent algorithm imitates biological behavior to solve the problem of algorithm. At present, different industries all put a wide attention and research on intelligent manufacture technology, and have achieved some initial results. However, the steel industry of high automation degree, already have had the conditions to achieve intelligent manufacturing.Firstly, this paper studied a new type of intelligent optimization algorithmbacteria foraging optimization algorithm, and analyzed the standard bacteria foraging optimization algorithm(BFO), then drew a conclusion that the standard algorithm has strong local search ability, but the global search ability. Another intelligent algorithm- particle swarm optimization algorithm(PSO) has a strong global search ability, thus on the basis of the original bacteria foraging optimization algorithm, the particle swarm optimization(PSO) algorithm can make up the defects of global search ability, forming the PSO- BFO algorithm. The PSO- BFO algorithm can improve the global search performance of the algorithm and speed up the convergence speed. In addition, during the migration operation of the new algorithm, it retained the fitness value ranking in the top 1/5 of the bacteria to protect the particles that have a good position will not die.Secondly, studied the center problem of the strip finishing part- load distribution, and respectively introduced the energy consumption curve method of the load distribution, allocation method based on the theory of the rolling and the load distribution optimization method based on intelligent algorithm. During the rolling process, the thickness distribution between the racks will have a very important influence on the flatness, thickness accuracy, etc. The basic task of the strip finishing model is that based on the requirement of equipment, confirms the entrance thickness of finishing mill group of each frame, exit thickness, roll speed and related process parameters according to the material conditions and requirement for finished products. So the research about the load distribution of strip finishing mill group has a very important practical significance. In the research of load distribution method based on the theory of the rolling, I put forward to a line processing method to solve the nonlinear equations of the rolling force, and a new initial value distribution method.On the basis of the new algorithm, with the goal of optimal shape, developed the strip rolling process simulation system by v c ++, joined the experience load distribution and the rolling pressure distribution ratio calculation module. This system can carry a thickness distribution simulation on the basis of traditional simulation, and can make use of PSO- BFO algorithm to optimize the experience distribution, and can make a clear introduction to the related parameters of rolling process. Finally, this paper use strip rolling process simulation system for a load distribution simulation optimization of the field data of a certain steel mill, then compare the results of load distribution optimization with those of the original data. The simulation results show that the load distribution results of PSO- BFO algorithm, not only ensure the rolling reduction of the previous frame large enough to give full play to the equipment capacity, but also meet the stability requirements of the relative convex degree change of the subsequent frame. The fitness of the optimized target function gets obvious improvement.