The Application Of Bacterial Foraging Optimization Algorithm In Laminar Cooling Process

During strip laminar cooling process,the strip coiling temperature need reduce 200 ~ 350 ℃ in relatively short time. It is not possible to reduce much of the heat only by strip thermal radiation and heat transfer process. Therefore, we need to install high efficiency cooling spray equipment on the strip output roller, reducing the strips’ surface temperature rapidly by spraying cool dense water on the strip surface. At the same time, controlling the hydraulic manifolds open number to meet the different needs of coiling temperature control requirements in this process. In one word, final strip coiling temperature directly depends on the spraying water amount in laminar cooling process. No matter the spraying water amount is higher or lower, it will cause the coiling temperature too high or too low, this will directly reduce the quality of steel strip production. Due to the traditional strip laminar cooling process is difficult to establish accurate mathematical model, most of current steel mills still adopt the method of checking empirical formulas or experimental data form for temperature control, so the control accuracy is low.In order to improve the control precision of the coiling temperature in laminar cooling process, this paper includes these content :1. Analysis of the characteristics of laminar cooling. In the whole process of laminar cooling control, the final coiling temperature depends on the amount of sparying water, so spraying water amount is the key to solve the control problem. In recent years, the optimization algorithm is widely used as representative of swarm intelligence algorithm, because it is not limited by the accuracy of mathematical model and the operating conditions, this paper introduces the optimization algorithm to find the optimal cooling water.2. Improved the traditional bacteria optimization algorithm based on niche. In this paper, the traditional method is easy to fall into local optimization, so the niche optimization algorithm is introduced. The concept of niche is to get the species with same characteristic together. In the application of bacteria group, the individual bacteria is limited to a specific living space by distance, the niche algorithm has faster convergence speed and higher ability than the traditional method. In order to verify this point of view, this paper compared operation trajectory and the eventually optimization position of traditional bacteria optimization algorithm and the niche optimization algorithm, to verify the niche optimization algorithm had improved the optimization capability of the traditional optimization algorithm.3. Proposed the water spray quantity setting method based on niche optimization algorithm. In this paper, the bacterial structure is defined by the parameters of the environment, the location, the fitness function, the nutrition value, the turning angle, the moving step size, and they are combined with the laminar cooling control process. Niche bacteria swarm optimization algorithm goes after chemotaxis behavior, reproductive behavior and migration steps then run the niche algorithm punishment elimination mechanism, finally found the superior position, this position corresponding to the laminar cooling process of optimal water injection.4. Adapting semi physical experiments to verify the algorithm. We have a large quantity of measured data by a domestic steel plant, the data for the project providing strong support for field experiment simulation. At the same time, this research uses the National Key Laboratory Platform of Northeastern University, it has established the simulation environment of the whole laminar cooling process. The experimental results show that the method proposed in this paper can be used to find out the quantity of optimized laminar cooling water, which can be used to the strip coiling temperature close to the target temperature, so as to improve the qualit y of the strip.