热轧机有限元与神经网络集成建模

Integrated model of a hot rolling mill based finite element analysis and neural networks

  • 摘要: 以某钢厂1580热连轧生产数据为基础,提出一种有限元与神经网络集成建模的方法.该方法首先对轧制过程的塑性变形进行有限元建模,然后结合有限元数值分析方法和智能技术的优点,实现有限元和神经网络的集成建模.集成模型中的神经网络模型为有限元模型提供参数调整的依据,并且在神经网络训练过程中使用改进的混沌粒子群优化算法对神经网络进行优化.通过与现场实际生产数据进行比较,验证了该模型的有效性.

     

    Abstract: According to production data of a 1580 rolling mill, an integrated method combining finite element analysis and neural networks was presented for hot rolling. In the method, plastic deformation during the rolling process was firstly modeled by a finite element method, and then a neural network provided parameter adjustment for the finite element model, so the integrated model had the advantages of neural network and finite element methods. At the same time, intelligent chaos particle swarm optimization (CPSO) was used to optimize weights and thresholds of the network. A comparison between simulation results and actual production data proved the validity of the integrated model.

     

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