【摘要】：在冷連軋的計(jì)算機(jī)控制系統(tǒng)中,軋制規(guī)程的設(shè)定是冷連軋生產(chǎn)控制參數(shù)設(shè)定的核心內(nèi)容。合理的軋制規(guī)程可以使冷連軋制高效運(yùn)行,達(dá)到更好的控制效果,并能降低生產(chǎn)能耗及提高產(chǎn)品質(zhì)量。隨著軋制技術(shù)的不斷發(fā)展和品質(zhì)要求的不斷提高,基于單目標(biāo)制定軋制規(guī)程已無(wú)法滿足生產(chǎn)的需要,目前廣泛采用的是多目標(biāo)優(yōu)化的軋制規(guī)程。本文根據(jù)生產(chǎn)的實(shí)際需要,研究了基于改進(jìn)免疫克隆算法的軋制規(guī)程多目標(biāo)優(yōu)化方法。首先,分析了傳統(tǒng)免疫克隆多目標(biāo)進(jìn)化算法的進(jìn)化機(jī)制,并針對(duì)算法收斂速度過(guò)慢的問(wèn)題,改進(jìn)了算法的變異策略。利用差分變異及云模型方式對(duì)種群個(gè)體進(jìn)行自適應(yīng)的變異,使個(gè)體的變異更有針對(duì)性,增大了算法的搜索范圍,提高了算法的收斂性能。其次,分析研究各種保持多目標(biāo)個(gè)體分布性的保留裁剪機(jī)制,根據(jù)免疫克隆多目標(biāo)算法中進(jìn)化種群和記憶種群的特點(diǎn)及在優(yōu)化過(guò)程中的作用,設(shè)計(jì)了混合的裁剪選擇機(jī)制,分別對(duì)進(jìn)化種群與記憶種群進(jìn)行個(gè)體選擇,防止種群中的個(gè)體過(guò)于密集的情況,提高了算法中個(gè)體的分布度。最后,針對(duì)軋制規(guī)程優(yōu)化過(guò)程中多目標(biāo)函數(shù)之間存在耦合,相互制約,難以選擇目標(biāo)側(cè)重的問(wèn)題,以唐山某鋼廠五機(jī)架冷連軋生產(chǎn)線為例,構(gòu)造了由等功率裕度、板形良好和防打滑目標(biāo)函數(shù)組成的多目標(biāo)負(fù)荷函數(shù),并采用本文提出的改進(jìn)算法對(duì)其進(jìn)行多目標(biāo)優(yōu)化計(jì)算。試驗(yàn)結(jié)果表明,此算法能夠很快的收斂到Pareto前沿,并且能夠獲得分布性良好的解集;優(yōu)化后的不同偏好軋制規(guī)程組合可以滿足不同的選擇要求。并與原規(guī)程相比,各軋機(jī)的利用更加合理,提高了軋機(jī)的利用效率,改善帶鋼板形和表面質(zhì)量,并且減少了劃痕的產(chǎn)生概率,對(duì)二級(jí)設(shè)定計(jì)算起到了指導(dǎo)的作用。
[Abstract]:In the computer control system of cold continuous rolling, the setting of rolling schedule is the core of the control parameter setting of cold tandem rolling. Reasonable rolling schedule can make cold continuous rolling run efficiently, achieve better control effect, and reduce production energy consumption and improve product quality. With the continuous development of rolling technology and the continuous improvement of quality requirements, making rolling schedule based on single objective can no longer meet the needs of production. At present, multi-objective optimization rolling schedule is widely used. In this paper, the multi-objective optimization method of rolling schedule based on improved immune clone algorithm is studied according to the actual needs of production. Firstly, the evolutionary mechanism of traditional immune clone multi-objective evolutionary algorithm is analyzed, and the mutation strategy of the algorithm is improved to solve the problem of slow convergence. The difference mutation and cloud model are used for adaptive mutation of individual population, which makes individual mutation more targeted, increases the search range of the algorithm and improves the convergence performance of the algorithm. Secondly, based on the characteristics of evolutionary population and memory population in immune clone multiobjective algorithm and its role in the optimization process, a hybrid clipping selection mechanism is designed. The individual selection of evolutionary population and memory population is carried out respectively to prevent the individuals in the population from being too dense and to improve the distribution degree of the individuals in the algorithm. Finally, aiming at the problems of coupling and mutual restriction between multi-objective functions in the process of rolling schedule optimization, it is difficult to select the target focus. Taking a five-stand cold continuous rolling line in Tangshan steel plant as an example, the equal power margin is constructed. The multi-objective load function with good shape and anti-skid objective function is used to calculate the multi-objective load function by using the improved algorithm proposed in this paper. The experimental results show that the proposed algorithm can converge to the Pareto front quickly and obtain a well distributed solution set, and the different preferred rolling schedule combinations after optimization can meet different selection requirements. Compared with the original regulation, the use of each rolling mill is more reasonable, the utilization efficiency of the mill is improved, the strip shape and surface quality are improved, and the probability of the scratch is reduced, which plays a guiding role in the calculation of the two-stage setting.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TG334.9;TP18

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本文編號(hào)：2325142