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Status evaluation of mobile welding robot driven by fuel cell hybrid power system based on cloud model

机译:基于云模型的燃料电池混合动力系统驱动机器人的现状评估

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The comprehensive evaluation of the performance parameters of the mobile welding robot driven by the fuel cell hybrid power system is beneficial to optimizing the energy efficiency and control performance of the system. However, few studies have paid attention to this aspect. Rough analytic hierarchy process and entropy weight method are used to calculate the weight of the evaluation index. Cloud model is used to synthesize all evaluation indicators to determine the status level. First, the golden section method is used to determine the evaluation criteria, and through cloud model, the evaluation criteria and measured parameters of the single evaluation index are transformed into corresponding evaluation reference clouds and evaluation clouds. Second, the weight of the evaluation index is determined by the method of the rough analytic hierarchy process, and the method of the entropy weight is used to revise the method of the rough analytic hierarchy process. The single evaluation reference cloud and evaluation cloud are aggregated to get the comprehensive evaluation reference cloud, and the comprehensive evaluation of the reference cloud is carried out. The evaluation cloud for each evaluation cycle. Finally, according to the correlation between the comprehensive evaluation cloud and the comprehensive evaluation standard cloud, the performance level of each evaluation cycle is determined. In this paper, the randomness and fuzziness of the qualitative concepts are solved by using the characteristics of the cloud model. Combined with rough analytic hierarchy process, the objectivity of the data is maintained and the advantages of the expert evaluation are enhanced. The validity of the model is verified by comparing the existing methods. These studies evaluate and classify the real-time status of the fuel cell robot, and provide a basis for the performance optimization and energy optimization of the hybrid power system controllers.
机译:由燃料电池混合动力系统驱动的移动焊接机器人的性能参数的综合评价有利于优化系统的能效和控制性能。然而,很少有研究则注意到这方面。粗略的分析层次处理和熵权法用于计算评估指标的重量。云模型用于综合所有评估指标以确定状态级别。首先,Golden截面方法用于确定评估标准,通过云模型,单个评估指标的评估标准和测量参数被转换为相应的评估参考云和评估云。其次,评估指标的权重通过粗略分析层次处理的方法确定,并且熵权的方法用于修改粗略分析层次结构的方法。单一评估参考云和评估云被聚合以获得综合评估参考云,并执行参考云的综合评估。每个评估周期的评估云。最后,根据综合评价云与综合评价标准云之间的相关性,确定每个评估周期的性能水平。在本文中,通过使用云模型的特征来解决了定性概念的随机性和模糊性。结合粗略分析层次处理,维持数据的客观性,并提高了专家评估的优势。通过比较现有方法来验证模型的有效性。这些研究评估并分类了燃料电池机器人的实时状态,并为混合动力系统控制器的性能优化和能量优化提供了基础。

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