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Research on intelligent classification of multi-attribute safety information and determination of operating environment

机译:多属性安全信息智能分类及操作环境的确定研究

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摘要

To analyze the system safety through the field system operation data, especially the system operation information provided by the operators, and to obtain the environment scope of the safe operation of the system, the multi-attribute safety information intelligent mining method is adopted. The new definitions and methods of attribute circle classification are proposed. The improvement is using inner attribute polygon and outer attribute polygon to construct the object attribute area. Monte Carlo method is used to calculate the overlap area of the object attribute area, and define overlap and transform with similarity, which is calculated by the overlap degree and the distance between two points in multi-dimensional space. The object classification reasoning method and system adaptive environment analysis method is established. The improved similarity analysis method is more suitable for computer implementation and intelligent analysis. Based on the previous study, this paper also analyzes the similarity of operation safety evaluation given by 30 operators of an electrical system, and obtains the pair wise similarity. The results show that the algorithm classification results have good correspondence with the original data decision level, and the range of the system safe operation environment is obtained, which can lay a foundation for further study of intelligent classification and system safety operation environment optimization.
机译:为了通过现场系统操作数据分析系统安全,尤其是由操作者提供的系统操作信息,并获得系统安全操作的环境范围,采用多属性安全信息智能采矿方法。提出了属性圆分类的新定义和方法。改进是使用内部属性多边形和外部属性多边形来构建对象属性区域。 Monte Carlo方法用于计算对象属性区域的重叠区域,并使用相似性定义重叠和变换,其通过重叠程度和多维空间中的两个点之间的距离来计算。建立了对象分类推理方法和系统自适应环境分析方法。改进的相似性分析方法更适合计算机实现和智能分析。基于先前的研究,本文还分析了电气系统的30个运营商给出的操作安全评估的相似性,并获得了一对明智的相似性。结果表明,算法分类结果与原始数据判定级别良好,获得了系统安全运行环境的范围,可以为进一步研究智能分类和系统安全运行环境优化奠定基础。

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