基于熵算法改进的故障树-云模型风险分析方法Visual risk assessment method based on the fault tree analysis coupled cloud models using modified entropy algorithm
龙丹冰;解丽萍;杨成;
摘要(Abstract):
为了改善建筑运维期失效风险的诊断和预测能力,提升其信息化程度,以一幢有显著劣化特征及病害且损伤分布特征复杂的古旧木结构建筑为例,基于改进的熵算法,提出了故障树-云模型(IEFTC)风险评估方法;考虑不同评价结果的标准差,给出了新的熵和超熵算法,既保留了专家对事件风险的判断,又量化了评价意见的离散度。该方法先利用故障树算法描述事件间的相关性并形成对应的风险地图,再结合云模型的数学分析功能,通过故障树的逻辑门进行模糊信息传递,可以在充分保留风险信息的基础上得到更为合理的分析结果。最后,实现了基于BIM的风险等级判断,并利用显示色度差异展示不同构件的风险程度。研究充分利用了云模型在模糊性和随机性方面进行数学分析的优势,提升了传统故障树方法处理和传递模糊信息的效果,并借助BIM进行可视化,有望在复杂病害结构的分析鉴定中提升评估及维护决策的准确度和效率。
关键词(KeyWords): 安全工程;风险诊断;故障树;云模型;BIM;风险可视化
基金项目(Foundation): 国家自然科学基金项目(51808455,51778537);; 国家重点研发计划项目(2016YFC0802205)
作者(Authors): 龙丹冰;解丽萍;杨成;
DOI: 10.13637/j.issn.1009-6094.2020.1581
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