探讨物理、人文和技术因素对斗轮挖掘机效率的影响:一种模糊认知图方法

Q3 Engineering
M. Menegaki, T. Michalakopoulos, C. Roumpos
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引用次数: 3

摘要

挖掘物料特性、褐煤层数和厚度、斗轮容量、人员经验等参数都会影响斗轮挖掘机的工作效率。本文在广泛查阅科学文献和专家干预的基础上,采用模糊认知图(FCM)方法探讨了影响BWEs效率的因素及其相互联系和相互依赖关系。主要目标是为复杂的采矿系统提供一个透明和灵活的模型,并提出一种不同的模拟方法,可以将影响系统行为的因素相互联系起来。该模型的实施表明,在有利条件和不利条件下,BWEs的效率存在显著差异。这是模拟的第一步,旨在帮助采矿业从业者,弥合“纯”定性和定量方法之间的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the effect of physical, human and technical factors on bucket wheel excavators' efficiency: a fuzzy cognitive map approach
Several parameters, e.g., characteristics of the excavated material, number and thickness of lignite layers, bucket wheel capacity, experience of personnel, etc., affect the efficiency of bucket wheel excavators (BWEs). In this paper, the fuzzy cognitive map (FCM) approach is used to explore the factors affecting the efficiency of BWEs as well as their interlinkages and interdependencies, based on an extensive review of scientific literature and expert intervention. The main goal is to provide a transparent and flexible model and propose a different simulation approach for complex mining systems that can interconnect the factors influencing system's behaviour. The implementation of the proposed model revealed significant differences in BWEs' efficiency under favourable and hostile conditions. This is a first step towards simulations intended to help mining practitioners, bridging the gap between 'pure' qualitative and quantitative approaches.
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来源期刊
International Journal of Mining and Mineral Engineering
International Journal of Mining and Mineral Engineering Engineering-Industrial and Manufacturing Engineering
CiteScore
1.90
自引率
0.00%
发文量
1
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