系统仿真学报 ›› 2016, Vol. 28 ›› Issue (12): 3087-3094.doi: 10.16182/j.issn1004731x.joss.201612030

• 仿真应用工程 • 上一篇    

基于改进主成分分析法的离散制造能耗分析

陈彦, 王艳   

  1. 江南大学物联网技术应用教育部工程研究中心,江苏 无锡214122
  • 收稿日期:2016-06-13 修回日期:2016-07-14 出版日期:2016-12-08 发布日期:2020-08-13
  • 作者简介:陈彦(1991-),男,江苏徐州,硕士生,研究方向为离散制造能效优化;王艳(1978-),女,江苏无锡,教授,博导,研究方向为网络控制优化。
  • 基金资助:
    国家自然科学基金(61572238),国家高技术研究发展计划(2014AA041505), 江苏省杰出青年基金(BK20160001)

Energy Consumption Analysis of Discrete Manufacturing Based on Improved Principal Component Analysis Method

Chen Yan, Wang Yan   

  1. Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China
  • Received:2016-06-13 Revised:2016-07-14 Online:2016-12-08 Published:2020-08-13

摘要: 针对离散制造能耗构成的复杂性,能耗指标之间相互影响,能耗分析结果难以获取的问题,从产品能耗、设备能效、任务流程能效三个层面,建立离散系统能效评价指标体系,进而提出一种基于改进主成分分析法的离散制造能耗分析方法,该方法引入指标重要性权重,优化了传统主成分分析只强调信息权重的缺陷,实现了指标客观性和主观性的有机结合,并在数据无量纲化处理时采用改进的数据标准化方法,避免了原始数据的信息丢失,全面考虑离散能耗分析的各个因素。实例分析和仿真结果表明改进方法更具合理性和稳定性。

关键词: 离散制造, 能耗, 评价指标体系, 改进主成分分析

Abstract: Due to the complexity of energy consumption of the discrete manufacturing system and the interaction between energy consumption indexes, the result of energy consumption analysis is hard to obtain, establishing energy efficiency evaluation index of discrete system, based on the three levels of energy consumption of products, equipment energy efficiency, the energy efficiency of task process. Furthermore, a method was proposed to analyze the discrete manufacturing process energy consumption based on improved principal component analysis method. The method introduced importance weights, overcame the shortcoming of traditional component analysis, which only emphasized the information weights, combined the subjective and objective of indexes which integrate, adopted the improved normalization during the data nondimensionalization to avoid the loss of original data information and considered every factors of energy consumption analysis of discrete manufacturing. Case analysis and simulation show that the improved method is more reasonable and stable.

Key words: discrete manufacturing, energy consumption, evaluation index system, improved principal component analysis

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