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A framework for analysing system intelligence of the building control system: a study of the integrated building management system

机译:楼宇控制系统的系统智能分析框架:综合楼宇管理系统的研究

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摘要

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.
机译:在表征系统智能和结构化分析决策模型方面缺乏令人满意的共识,这限制了开发人员和从业人员以完全知情的方式理解和配置最佳的智能建筑系统。到目前为止,在这方面几乎没有进行研究。本研究旨在识别关键的智能指标,并开发分析模型来计算智能建筑中智能建筑系统的系统智能分数。集成建筑管理系统(IBMS)被用作说明框架的说明性示例。本研究中提出的模型应用了系统智能理论和概念分析框架。首先从一般调查中确定了总共16个关键智能指标。然后,采用了两种多标准决策方法(MCDM),即层次分析法(AHP)和网络分析法(ANP),来开发系统智能分析模型。 IBMS的顶级情报指标包括:对操作偏差的自我诊断;自适应极限控制算法;以及全年时间表的效果。然后,将开发的概念框架转换为实用模型。通过专家验证评估了实际模型的有效性。这项研究的主要贡献是促进对智能指标的理解,并为系统框架奠定基础,该系统框架为开发人员和建筑利益相关者提供了一个综合的包容性工具,用于对所建议的组件设计配置进行系统智能评估。

著录项

  • 作者

    Wong Johnny; Li Heng;

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  • 年度 2009
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