基于模糊优选模型的桥式起重机节能评价

中国机械工程 ›› 2014, Vol. 25 ›› Issue (12): 1630-1633,1638.

基于模糊优选模型的桥式起重机节能评价

叶伟1;童一飞1;李向东2

1.南京理工大学,南京,210094
2.江苏省特种设备安全监督检验研究院,南京,210003

出版日期:2014-06-26 发布日期:2014-06-27
基金资助:
国家质量监督检验检疫总局科技计划资助项目（2012QK178）；江苏省质量技术监督局科技项目（KJ122717）；江苏省博士后科研资助计划项目（0901041C)；南京理工大学“卓越计划紫金之星”资助项目

Bridge Crane Energy-saving Evaluation Based on Fuzzy Optimization Model

Ye Wei1;Tong Yifei1;Li Xiangdong2

1.Nanjing University of Science and Technology,Nanjing,210094
2.Special Equipment Safety Supervision Inspection Institute of Jiangsu Province,Nanjing,210003

Online:2014-06-26 Published:2014-06-27

摘要/Abstract

摘要：

根据桥式起重机在“全生命周期”中的能耗状况，提出了桥式起重机节能评价指标体系,运用粗集理论知识对桥式起重机节能评价指标体系进行指标约简，约简后得到优化的桥式起重机节能指标体系并求得各指标权重。运用模糊优选理论建立桥式起重机节能评价模型,利用该模型对桥式起重机的能耗进行评价。选取5个不同设计、不同材料的桥式起重机,对其能耗优劣进行计算和分析,得到桥式起重机节能最优的设计，同时为桥式起重机设计制造提供参考意见。

关键词: 起重机, 指标体系, 模糊优选模型, 节能评价

Abstract:

Based on energy consumption of a bridge crane in “full life cycle”,this paper put forward bridge cranes energy saving evaluation index system. Rough set theory knowledge was adopted to reduce the index of the bridge crane energy saving evaluation index system. The optimized bridge crane energy saving index system could be obtained after reduction and all index weights were acquired as well. Finally the fuzzy optimization theory was applied to build energy-efficient evaluation model of the bridge crane and this model was used to evaluate the energy consumption of the overhead crane. This paper selected five bridge cranes of different designs and materials and analyzed their advantages as well as disadvantages of power consumption. Via calculation and analyses, the optimal design of energy saving of bridge can be obtained and it may provide a reference for the bridge crane design and manufacturing.

Key words: crane, index system, fuzzy optimization model, energy-saving evaluation

中图分类号:

TH132

叶伟, 童一飞, 李向东. 基于模糊优选模型的桥式起重机节能评价[J]. 中国机械工程, 2014, 25(12): 1630-1633,1638.

Ye Wei, Tong Yifei, Li Xiangdong. Bridge Crane Energy-saving Evaluation Based on Fuzzy Optimization Model[J]. China Mechanical Engineering, 2014, 25(12): 1630-1633,1638.

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