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陈宇博士报告

发布时间:2021年05月24日 作者: 浏览次数:

时间:2021年5月28日晚上7:00-8:00

地点:民主楼222

报告人:陈宇

报告时间:晚上7:00-8:00

报告标题:惯性导航自动导引小车系统

报告摘要:惯性导航AGV是以惯性传感器和二维码为导引方式的一种自动化物料搬运设备,能够沿预先设定的路径行驶,是现代工业自动化物流系统中的关键设备之一。在运行过程中,它可以按照上位机下达的指令,依照惯性传感器确定位置信息,并根据预设程序,沿着规定的路线自动行驶,或者在指定位置停靠,以完成一系列移载作业功能。它具有自动化程度高、应用灵活、安全可靠、无人操作、施工简单及维修方便等诸多优点。本次汇报设计了AGV的软硬件开发,并完成了样机的研发和验收。

时间:2021年5月30日下午4:00-5:00

地点:升华后楼504

报告人:陈宇

报告时间:下午4:00-5:00

报告标题:不确定条件下湿法炼锌机会约束配料优化方法

报告摘要:针对各仓库锌精矿成分的不确定性导致配料达标率低的问题,提出了一种处理不确定性的非线性计划约束规划模型。首先,根据统计学方法获得了锌精矿不确定成分的分布特征。其次,为了最小化目标函数的悲观值,将非线性随机优化模型转化为一个易于处理的非线性极小机会约束规划模型。然后,采用混合智能优化算法对该问题进行有效的求解。最后,利用某锌冶炼厂配料过程的实际生产数据验证了该方法的有效性。与确定性优化方法相比,该模型不仅给出了混合锌精矿各成分满足要求的概率,而且在相同条件下也能达到较高的合格率。

时间:2021年6月5日晚上7:30-8:30

地点:升华后楼504

报告人:陈宇

报告时间:晚上7:30-8:30

报告标题:Closed-loop blending optimization based on variational Bayesianandits application in industry

报告摘要:There are uncertainties in the process of blending optimization. Considering the characteristics of large lag and small sample size of the feedback test data and the dynamic raw material inventory, we innovatively proposed a closed-loop blending optimization framework based on variational Bayes under uncertainty. The framework consists of both data-driven system and model-based system. In the data-driven system, the feedback optimization problem was reconstructed into a linear regression problem, and the variational Bayesian was used to obtain the mean and variance of the distribution. Then, according to the incoming raw materials, the mean value of each distribution parameter was adjusted by expert rules. Last, in the model-based system, blending ratio was obtained by chance-constrained programming model. To verify the effectiveness of the closed-loop framework, a detailed derivation process of variable Bayesian, expert rule and chance-constrained programming model were established for zinc smelting process. Numerical studies and an industrial application for zinc smelting process were presented to demonstrate the advantages of the proposed model. Compared with the manual blending, the volatility index of test value is greatly reduced and the compliance rates of zinc and lead is increased by 6.7% and 3.3%, respectively.

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