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基于改进FMEA法的深基坑施工风险评价 被引量:10

Risk Assessment of the Deep Foundation Pit Based on the Improved FMEA Method
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摘要 深基坑施工具有较大的风险,为了有效分析和管理深基坑施工的关键风险,采用基于二元语义和灰色关联分析的改进失效模式和影响分析(FMEA)法进行其风险分析。该方法在传统FMEA方法基础上,将专家给出的语言评价信息用二元语义形式表示,并考虑了专家评价时存在的多粒度问题,对计算值采用灰色关联分析进行风险排序,得到风险优先等级。以某深基坑施工项目为例对该方法进行了运用,得到该项目深基坑施工的关键风险因素。该方法针对传统FMEA方法的局限性进行改进,相对于传统FMEA方法,减少了评价信息转化中产生的信息失真或损失情况,还考虑了风险因子的权重及决策者的决策态度,提高了风险排序的准确性,为深基坑施工风险评价提供了新的思路。 There exist great risks in the construction of deep foundation pit. In order to know the key risks affecting the construction of deep foundation pit,we put forward an improved failure mode and effect analysis(FMEA) method which combined 2-tuple linguistic and grey relational analysis(GRA). Based on the traditional FMEA method,the linguistic assessment information by decision makers is represented by means of 2-tuple linguistic variables and the multi-granularity issue is taken into account. Furthermore,the risks are ranked by using GRA. A deep foundation pit construction project is taken as an example to demonstrate and validate the proposed method. By using the improved FMEA approach,the most critical risks in deep foundation pit construction process can be identified. The proposed method overcomes the inherent weaknesses of the traditional FMEA method and provides a reliable and distinguishable risk ranking system by considering the weight of risk factors and decision behavior of decision makers. Compared with the traditional FMEA method,the proposed method can deal with the language information more precisely,reduce the information distortion and loss,and improve the precision and reliability of the risk ranking. The study provides a comprehensive risk identification and evaluation tool for the risk analysis of deep foundation pit construction.
出处 《土木工程与管理学报》 北大核心 2018年第1期54-59,72,共7页 Journal of Civil Engineering and Management
基金 教育部人文社会科学研究项目(16YJCZH009)
关键词 深基坑 风险评估 失效模式与影响分析 二元语义 灰色关联分析 deep foundation pit risk assessment failure mode and effect analysis two-tuple linguistic variable gray correlation analysis
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