摘要
电力物资供应链潜在供应风险,吞吐量低、纵向载荷值与预期最大值差距大,因此,设计一种基于大数据的电力物资供应链安全风险监测系统。系统在电力物资供应风险防控框架设计基础上,采用AD7606数据采集模块结合并口方式跳线,采集原始风险数据。以89C52单片机作为中央处理单元,处理采集的原始数据;采用供应链安全风险评估模块,评估供应链中采购以运输等环节的风险信息,结合供应链安全风险预警与处理模块,完成供应链安全风险的实时预警;通过大数据技术计算两个相邻采样点的测量数据和标准残差,通过归一化处理残差指数,利用聚类有效性指数获得最优聚类效果,识别电力物资供应链潜在风险,完成风险监测系统设计。实验结果表明:该系统监测到的纵向载荷值与预期最大值相差0.5 kN/m~3,供应链吞吐量最大值为60 bit,说明电力物资供应链稳定。
Potential supply risks of power supply chain,low throughput,large gap between longitudinal load value and expected maximum value,therefore,a security risk monitoring system of power material supply chain based on big data is designed.Based on the design of risk prevention and control framework of power material supply,the system adopts AD7606 data acquisition module combined with parallel port jumper to collect original risk data.89C52 single chip microcomputer is used as the central processing unit to process the collected original data;Using the supply chain security risk assessment module to evaluate the risk information of procurement,transportation and other links in the supply chain,and combined with the supply chain security risk early warning and processing module to complete the real-time early warning of supply chain security risk;The measured data and standard residuals of two adjacent sampling points are calculated by big data technology,and the residual index is normalized,use the clustering effectiveness index to obtain the optimal clustering effect,identify the potential risks of power material supply chain,and complete the design of risk monitoring system.The experimental results show that the difference between the longitudinal load value monitored by the system and the expected maximum value is 0.5 kN/m~3,and the maximum throughput of the supply chain is 60 bit,indicating that the power material supply chain is stable.
作者
刘晶晶
张华强
陈嘉羽
褚莉
杨涛
LIU Jingjing;ZHANG Huaqiang;CHEN Jiayu;CHU Li;YANG Tao(Materials branch of State Grid Anhui Electric Power Co.Ltd.,Hefei 230011,China)
出处
《工业加热》
CAS
2023年第4期64-68,共5页
Industrial Heating
基金
国家电网公司科技项目(52062519063T)。
关键词
大数据
电力物资
供应链
安全风险
监测
big data
electric power supplies
supply chain
security risk
monitoring
