A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data an...A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.展开更多
为满足人机系统概率风险评估的需要,提出一种人为差错概率量化方法。分析技能、规则和知识为基础(skill,rule and knowledge-based,SRK)框架和行为模式的确定方法Hanaman决策树法,指出在确定行为模式的过程中考虑行为模式影响因素的不...为满足人机系统概率风险评估的需要,提出一种人为差错概率量化方法。分析技能、规则和知识为基础(skill,rule and knowledge-based,SRK)框架和行为模式的确定方法Hanaman决策树法,指出在确定行为模式的过程中考虑行为模式影响因素的不确定性是必要的;使用模糊逻辑方法处理行为模式各个影响因素的不确定性,根据Hanaman决策树构建模糊推理规则,利用系统人为行为可靠性程序(systematic human action reliability procedure,SHARP)方法所提供的人为差错概率区间确定人为差错概率的隶属度函数。结果表明:该方法考虑了任务场景的不确定性,可以得到人为差错概率的精确值,满足人机系统概率风险评估的需要。展开更多
The accurate quantification of human error probability(HEP) has long been a main pursuit for most human reliability analysis(HRA) methods. This paper proposes a strategy to analyzeand predict human error on the basis ...The accurate quantification of human error probability(HEP) has long been a main pursuit for most human reliability analysis(HRA) methods. This paper proposes a strategy to analyzeand predict human error on the basis of a further modification of theexisting cognitive reliability and error analysis method (CREAM)in HRA. Through providing a broader definition for the key parametersused in the quantification method, this paper produces arelatively flexible strategy to determine the nominal HEP (HEP0).Basing on this strategy, the actual quantification of HEP in CREAMis able to be applied to more verified conditions. To prove the validityof the method proposed, a case study of spacecraft launch isalso introduced, in which the prediction derived from the method isproved consistent with real field data.展开更多
To characterize the uncertainty and fuzziness in offshore structural inspection, probability of detection (POD) must be determined. This paper presents the expressions for the POD of four different damage forms mainly...To characterize the uncertainty and fuzziness in offshore structural inspection, probability of detection (POD) must be determined. This paper presents the expressions for the POD of four different damage forms mainly existing in offshore structures. The fuzzy-set theory is applied to estimate human errors through the definition of inspection quality. Expressions of inspection quality are achieved. To verify the validity and correctness of the expressions, the data from an offshore platform field inspection of evaluation results of human errors affecting inspection quality are used to estimate the parameters of the POD. The results show that the present models can provide basis for further study of ofTshore structural inspection reliability.展开更多
Human Reliability Analysis(HRA)is an important part in safety assessment of a large complex system.Human Cognitive Reliability(HCR)model is a method of evaluating the probability that operators fail to complete during...Human Reliability Analysis(HRA)is an important part in safety assessment of a large complex system.Human Cognitive Reliability(HCR)model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time,which is widely used in HRA.In the application of this method,cognitive patterns of humans are required to be considered and classified,and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain.How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy and applicability of HCR.In this paper,a new model was proposed to deal with the uncertain information which exists in the processes of cognitive pattern classification in HCR.First,an evaluation panel was constructed based on expert opinions and processing including setting corresponding anchor points and qualitative indicators of different cognitive patterns,and mapping them to fuzzy numbers and unit intervals.Second,based on the evaluation panel,different analysts judge the cognitive pattern types of actual specific events and provide the level of confidence he or she has in the judgments.Finally,the evaluation opinions of multiple analysts were expressed and fused based on the Dempster-Shafer Evidence Theory(DSET),and the fused results were applied to the HCR model to obtain the Human Error Probability(HEP).A case study was used to demonstrate the procedure and effectiveness of the proposed method.展开更多
A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and e...A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.展开更多
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education(20114307120032)the National Natural Science Foundation of China(71201167)
文摘A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.
文摘为满足人机系统概率风险评估的需要,提出一种人为差错概率量化方法。分析技能、规则和知识为基础(skill,rule and knowledge-based,SRK)框架和行为模式的确定方法Hanaman决策树法,指出在确定行为模式的过程中考虑行为模式影响因素的不确定性是必要的;使用模糊逻辑方法处理行为模式各个影响因素的不确定性,根据Hanaman决策树构建模糊推理规则,利用系统人为行为可靠性程序(systematic human action reliability procedure,SHARP)方法所提供的人为差错概率区间确定人为差错概率的隶属度函数。结果表明:该方法考虑了任务场景的不确定性,可以得到人为差错概率的精确值,满足人机系统概率风险评估的需要。
基金supported by the National Natural Science Foundation of China(7117100871571004)
文摘The accurate quantification of human error probability(HEP) has long been a main pursuit for most human reliability analysis(HRA) methods. This paper proposes a strategy to analyzeand predict human error on the basis of a further modification of theexisting cognitive reliability and error analysis method (CREAM)in HRA. Through providing a broader definition for the key parametersused in the quantification method, this paper produces arelatively flexible strategy to determine the nominal HEP (HEP0).Basing on this strategy, the actual quantification of HEP in CREAMis able to be applied to more verified conditions. To prove the validityof the method proposed, a case study of spacecraft launch isalso introduced, in which the prediction derived from the method isproved consistent with real field data.
文摘To characterize the uncertainty and fuzziness in offshore structural inspection, probability of detection (POD) must be determined. This paper presents the expressions for the POD of four different damage forms mainly existing in offshore structures. The fuzzy-set theory is applied to estimate human errors through the definition of inspection quality. Expressions of inspection quality are achieved. To verify the validity and correctness of the expressions, the data from an offshore platform field inspection of evaluation results of human errors affecting inspection quality are used to estimate the parameters of the POD. The results show that the present models can provide basis for further study of ofTshore structural inspection reliability.
基金supported by Shanghai Natural Science Foundation(Grant No.19ZR1420700)sponsored by Shanghai Rising-Star Program(Grant No.21QA1403400)Shanghai Key Laboratory of Power Station Automation Technology(Grant No.13DZ2273800).
文摘Human Reliability Analysis(HRA)is an important part in safety assessment of a large complex system.Human Cognitive Reliability(HCR)model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time,which is widely used in HRA.In the application of this method,cognitive patterns of humans are required to be considered and classified,and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain.How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy and applicability of HCR.In this paper,a new model was proposed to deal with the uncertain information which exists in the processes of cognitive pattern classification in HCR.First,an evaluation panel was constructed based on expert opinions and processing including setting corresponding anchor points and qualitative indicators of different cognitive patterns,and mapping them to fuzzy numbers and unit intervals.Second,based on the evaluation panel,different analysts judge the cognitive pattern types of actual specific events and provide the level of confidence he or she has in the judgments.Finally,the evaluation opinions of multiple analysts were expressed and fused based on the Dempster-Shafer Evidence Theory(DSET),and the fused results were applied to the HCR model to obtain the Human Error Probability(HEP).A case study was used to demonstrate the procedure and effectiveness of the proposed method.
基金Supported by the National Basic Research Program of China("973"Program,No.2014CB046804)National Natural Science Foundation of China(No.51239008)+1 种基金Foundation of State Key Laboratory of Marine Engineering of Shanghai Jiaotong UniversityFoundation for Innovative Research Groups of National Natural Science Foundation of China(No.51021004)
文摘A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.
