随着我国水利工程事业的高速发展,水利工程中的安全问题越来越被重视。本文将人因可靠性分析与抽水蓄能电站结合,利用SLIM(Success likelihood index method,SLIM)方法对抽水蓄能电站充排水作业人员进行可靠性分析。由于SLIM方法更多依...随着我国水利工程事业的高速发展,水利工程中的安全问题越来越被重视。本文将人因可靠性分析与抽水蓄能电站结合,利用SLIM(Success likelihood index method,SLIM)方法对抽水蓄能电站充排水作业人员进行可靠性分析。由于SLIM方法更多依赖于专家的主观意见,为提高结果的准确性,本文采用层次分析法与SLIM相结合的方式筛选出部分不合格的专家打分结果,再以PSF为准则层计算出权重值和对失误的影响程度,得到失误发生概率。分析结果证明“组织完善性、人机界面(MMI)与运行支持的完善性、经验培训、各成员合作质量”对发生概率较高的失误影响程度较大,即人为因素对水电站实际操作有重要影响,工程上可主要通过提高人因可靠性来降低事故发生概率。展开更多
Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of ...Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of risk management, has a substantial impact on the system-safety level of organizations, industries, and operations. If the causes of all kinds of failure and the interactions between them are considered, effective risk assessment can be highly accurate. A combination of traditional risk assessment approaches and modern scientific probability methods can help in realizing better quantitative risk assessment methods. Most researchers face the problem of minimal field data with respect to the probability and frequency of each failure. Because of this limitation in the availability of epistemic knowledge, it is important to conduct epistemic estimations by applying the Bayesian theory for identifying plausible outcomes. In this paper, we propose an algorithm and demonstrate its application in a case study for a light-weight lifting operation in the Persian Gulf of Iran. First, we identify potential accident scenarios and present them in an event tree format. Next, excluding human error, we use the event tree to roughly estimate the prior probability of other hazard-promoting factors using a minimal amount of field data. We then use the Success Likelihood Index Method(SLIM) to calculate the probability of human error. On the basis of the proposed event tree, we use the Bayesian network of the provided scenarios to compensate for the lack of data. Finally, we determine the resulting probability of each event based on its evidence in the epistemic estimation format by building on two Bayesian network types: the probability of hazard promotion factors and the Bayesian theory. The study results indicate that despite the lack of available information on the operation of floating objects, a satisfactory result can be achieved using epistemic data.展开更多
文摘随着我国水利工程事业的高速发展,水利工程中的安全问题越来越被重视。本文将人因可靠性分析与抽水蓄能电站结合,利用SLIM(Success likelihood index method,SLIM)方法对抽水蓄能电站充排水作业人员进行可靠性分析。由于SLIM方法更多依赖于专家的主观意见,为提高结果的准确性,本文采用层次分析法与SLIM相结合的方式筛选出部分不合格的专家打分结果,再以PSF为准则层计算出权重值和对失误的影响程度,得到失误发生概率。分析结果证明“组织完善性、人机界面(MMI)与运行支持的完善性、经验培训、各成员合作质量”对发生概率较高的失误影响程度较大,即人为因素对水电站实际操作有重要影响,工程上可主要通过提高人因可靠性来降低事故发生概率。
文摘Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of risk management, has a substantial impact on the system-safety level of organizations, industries, and operations. If the causes of all kinds of failure and the interactions between them are considered, effective risk assessment can be highly accurate. A combination of traditional risk assessment approaches and modern scientific probability methods can help in realizing better quantitative risk assessment methods. Most researchers face the problem of minimal field data with respect to the probability and frequency of each failure. Because of this limitation in the availability of epistemic knowledge, it is important to conduct epistemic estimations by applying the Bayesian theory for identifying plausible outcomes. In this paper, we propose an algorithm and demonstrate its application in a case study for a light-weight lifting operation in the Persian Gulf of Iran. First, we identify potential accident scenarios and present them in an event tree format. Next, excluding human error, we use the event tree to roughly estimate the prior probability of other hazard-promoting factors using a minimal amount of field data. We then use the Success Likelihood Index Method(SLIM) to calculate the probability of human error. On the basis of the proposed event tree, we use the Bayesian network of the provided scenarios to compensate for the lack of data. Finally, we determine the resulting probability of each event based on its evidence in the epistemic estimation format by building on two Bayesian network types: the probability of hazard promotion factors and the Bayesian theory. The study results indicate that despite the lack of available information on the operation of floating objects, a satisfactory result can be achieved using epistemic data.
