基于FDTD建模的采矿大数据应用研究  

Research on application of mining big data based on FDTD modeling

作　　者：杨勇[1] Yang Yong(Hebei College of Industry and Technology Xuangang Branch,Zhangjiakou 075100,China)

机构地区：[1]河北工业职业技术学院宣钢分院,河北张家口075100

出　　处：《能源与环保》2021年第6期248-251,257,共5页CHINA ENERGY AND ENVIRONMENTAL PROTECTION

基　　金：张家口市2019年度社会科学研究课题(2019146)。

摘　　要：大数据技术的发展为工业生产提供丰富的信息数据,可帮助煤矿企业生产、运营提供决策支持数据。提出一种基于基于有限差分时域方法,采用时间相关的波动方程,对采矿过程中电力使用进行动态模拟,核心在于对电力消耗和电力费用监测,基于大数据计算平台中通过初始随机波函数对TDSE进行数值求解,收敛于基态波函数。给出了不同约束电位参数的的能量和波函数的数值结果,并与其他数值方法的结果进行比较,结果表明,基于FDTD的方法可提供精确的能量和波函数,可在采矿工艺电力使用预测提供精确的数据支持。The development of big data technology provides rich information data for industrial production,and can help coal mining enterprises to provide decision support data for production and operation.A new method based on finite difference time domain is proposed,which uses time-related wave equation to simulate the power use in mining process.The core is to monitor the power consumption and power cost.Based on the large data computing platform,tdse is numerically solved by the initial random wave function,which converges to the ground state wave function.The numerical results of energy and wave functions of different binding potential parameters are given.The results are compared with other numerical methods.The results show that FDTD method can provide accurate energy and wave functions,and can provide accurate data support for mining process power use prediction.

关 键 词：决策支持 采矿工艺 有限差分时域 大数据平台 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]