摘要
由于离散制造系统的能耗具有复杂性和不确定性等特点,急需一种数据驱动的通用能耗预测方法.对此,首先依据知识建模方法搭建面向能耗的知识模型,以指导能耗数据与工艺信息、排产信息的有机结合;然后,将数值型和字符型输入变量进行综合考虑:先采用功率波动程度计算属性的重要性,再通过层次实例检索方法来保证字符型输入变量的一致性或相关性;最后,通过检索相似工步来实现能耗预测.仿真实验表明所提出的方法可行且有效.
Considering the complexity and uncertainty of energy consumption in a discrete manufacturing system, a general data-driven energy prediction method is urgently required. Therefore, a knowledge model oriented to energy consumption is built using a knowledge modeling method to guide the combination of the energy consumption data,the process plan and the production schedule. Then, character input variables and numeric input variables are both considered in the process of energy consumption prediction. The attribute importance is calculated by the degree of power fluctuation, and the consistency or correlation of character input variables are guaranteed by using the hierarchical case retrieval method. Finally, energy consumption is predicted by retrieving similar working-steps. The experimental simulation shows the feasibility and effectiveness of the proposed method.
作者
徐彬梓
王艳
纪志成
XU Bin-zi;WANG Yan;JI Zhi-cheng(College of Internet of Things and Engineering,Jiangnan University,Wuxi 214122,China)
出处
《控制与决策》
EI
CSCD
北大核心
2019年第1期9-17,共9页
Control and Decision
基金
国家自然科学基金项目(61572238)
江苏省杰出青年基金项目(BK20160001)
关键词
能耗
知识
离散制造
实例推理
数据驱动
energy consumption
knowledge
discrete manufacture
case-based reasoning
data-driven
