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改进的模糊失效模式与效应分析方法在土石坝环境风险评估中的应用研究

Development of modified fuzzy FMEA method in environmental risk assessment of earth dams.

作者信息

Beiranvand Behrang

机构信息

University of Qom, Qom, Iran.

出版信息

Sci Rep. 2024 Jul 30;14(1):17585. doi: 10.1038/s41598-024-68217-w.

Abstract

The investigations have shown that the construction of the dam and its related facilities have significant physical-chemical and ecological effects on the ecosystem. Failure Mode and Effects Analysis (FMEA) is a technique for ranking risks in projects to construct dams, but it has many deficiencies and ambiguities. Therefore, to prevent the shortcomings of the classical method, the modified fuzzy inference system (MFIS-FMEA) method has been used by creating a two-stage model to more accurately assess the risk of Eyvashan Dam. First, all the considered indicators are weighted using the Shannon entropy method, and the environmental risk is prioritized using the Fuzzy OWA method. In this study, two-stage fuzzy reasoning and a Max-Min combination rule are used. When severity (SEV) and occurrence (OCC) variables are combined, the critical risk index (RCI) values are predicted in the first stage. RCI and detection index (DET) input are then used to predict the MFIS-RPN in the second stage. The results of the risk priority number (RPN) in the MFIS-RPN method are much more accurate and serious than the FIS-RPN method due to the two-stage nature and the use of new language terms. The results of the proposed MFIS-RPN technique show that the highest RPN was obtained with immediate action in the dam construction phase for soil erosion and soil pollution and in the dam operation phase for aquatic and water pollution. Therefore, due to the increase in risk score, it is necessary to take immediate and more accurate monitoring during the construction and operation phases.

摘要

调查表明,大坝及其相关设施的建设对生态系统具有重大的物理化学和生态影响。故障模式与影响分析(FMEA)是一种对大坝建设项目中的风险进行排序的技术,但它存在许多缺陷和模糊性。因此,为了避免经典方法的缺点,通过创建一个两阶段模型来使用改进的模糊推理系统(MFIS-FMEA)方法,以更准确地评估埃瓦尚大坝的风险。首先,使用香农熵方法对所有考虑的指标进行加权,并使用模糊OWA方法对环境风险进行优先级排序。在本研究中,使用了两阶段模糊推理和最大-最小组合规则。当严重程度(SEV)和发生频率(OCC)变量相结合时,在第一阶段预测关键风险指数(RCI)值。然后,将RCI和检测指数(DET)输入用于在第二阶段预测MFIS-RPN。由于两阶段性质和使用新的语言术语,MFIS-RPN方法中的风险优先数(RPN)结果比FIS-RPN方法更准确、更可靠。所提出的MFIS-RPN技术结果表明,在大坝建设阶段,土壤侵蚀和土壤污染方面以及大坝运行阶段,水生生物和水污染方面,立即采取行动时获得的RPN最高。因此,由于风险得分的增加,在建设和运行阶段有必要立即进行更准确的监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a96/11289376/6f45ec110ca7/41598_2024_68217_Fig1_HTML.jpg

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