Objective To propose a new dynamic extremum self searching method, which can be used in industrial processes extremum optimum control systems, to overcome the disadvantages of traditional method. Methods This algor...Objective To propose a new dynamic extremum self searching method, which can be used in industrial processes extremum optimum control systems, to overcome the disadvantages of traditional method. Methods This algorithm is based on correlation analysis. A pseudo random binary signal m sequence u(t) is added as probe signal in system input, construct cross correlation function between system input and output, the next step hunting direction is judged by the differential sign. Results Compared with traditional algorithm such as step forward hunting method, the iterative efficient, hunting precision and anti interference ability of the correlation analysis method is obvious over the traditional algorithm. The computer simulation experimental given illustrate these viewpoints. Conclusion The correlation analysis method can settle the optimum state point of device operating process. It has the advantage of easy condition , simple calculate process.展开更多
点阵材料具有轻质、抗冲击、高能量吸收等特性,因而在航天飞行器承载部件设计等领域有广阔应用前景.通过对点阵材料内部杆径进行合理的梯度设计,可以提高点阵材料在高速冲击载荷作用下的动态力学性能.利用仿真模拟数据,基于随机森林模...点阵材料具有轻质、抗冲击、高能量吸收等特性,因而在航天飞行器承载部件设计等领域有广阔应用前景.通过对点阵材料内部杆径进行合理的梯度设计,可以提高点阵材料在高速冲击载荷作用下的动态力学性能.利用仿真模拟数据,基于随机森林模型实现了梯度点阵材料的动态力学响应预测和结构参数优化.以面心立方(face center cubic,FCC)结构梯度点阵材料为研究对象,通过对杆径参数的调整实现点阵材料密度的梯度化设计.通过LS-DYNA软件计算了密度分布不同的梯度点阵材料受到冲击载荷作用时的动态力学响应,包括冲击端面与支撑端面接触应力随时间的变化曲线.基于随机森林模型,以各层胞元的相对密度为输入,实现对点阵材料端面峰值应力的预测,并基于Gini指数分析出对不同端面处峰值应力影响最大的胞元层.将网格搜索算法与训练好的随机森林对接,分别以两个端面上的峰值应力最高作为优化目标,获得点阵材料各层胞元相对密度的最优值.模型对梯度点阵材料端面峰值应力的预测误差在5%以内.数值模拟验证结果表明,优化后所得梯度点阵材料相应端面上的峰值应力高于仿真数据集内任何结构.展开更多
文摘Objective To propose a new dynamic extremum self searching method, which can be used in industrial processes extremum optimum control systems, to overcome the disadvantages of traditional method. Methods This algorithm is based on correlation analysis. A pseudo random binary signal m sequence u(t) is added as probe signal in system input, construct cross correlation function between system input and output, the next step hunting direction is judged by the differential sign. Results Compared with traditional algorithm such as step forward hunting method, the iterative efficient, hunting precision and anti interference ability of the correlation analysis method is obvious over the traditional algorithm. The computer simulation experimental given illustrate these viewpoints. Conclusion The correlation analysis method can settle the optimum state point of device operating process. It has the advantage of easy condition , simple calculate process.
文摘点阵材料具有轻质、抗冲击、高能量吸收等特性,因而在航天飞行器承载部件设计等领域有广阔应用前景.通过对点阵材料内部杆径进行合理的梯度设计,可以提高点阵材料在高速冲击载荷作用下的动态力学性能.利用仿真模拟数据,基于随机森林模型实现了梯度点阵材料的动态力学响应预测和结构参数优化.以面心立方(face center cubic,FCC)结构梯度点阵材料为研究对象,通过对杆径参数的调整实现点阵材料密度的梯度化设计.通过LS-DYNA软件计算了密度分布不同的梯度点阵材料受到冲击载荷作用时的动态力学响应,包括冲击端面与支撑端面接触应力随时间的变化曲线.基于随机森林模型,以各层胞元的相对密度为输入,实现对点阵材料端面峰值应力的预测,并基于Gini指数分析出对不同端面处峰值应力影响最大的胞元层.将网格搜索算法与训练好的随机森林对接,分别以两个端面上的峰值应力最高作为优化目标,获得点阵材料各层胞元相对密度的最优值.模型对梯度点阵材料端面峰值应力的预测误差在5%以内.数值模拟验证结果表明,优化后所得梯度点阵材料相应端面上的峰值应力高于仿真数据集内任何结构.
