基于隐马尔可夫的核电厂半数字化人-机界面事故诊断过程人因可靠性模型

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基金项目:

岭东核电有限公司科研项目(KR70543)

国家自然科学基金资助项目(70873040,71071051)

Human Factors Reliability Model of Half-Digital Human-Machine Interface During Diagnosing Process Based on Hide MarKov in Nuclear Power Plants

1. Human Factors Institute, University of South China, Hengyang, Hunan, 421001, China;
2. Hunan Technical College, Hengyang, Hunan, 421001, China;
3. Center for Research in Information Management, University of South China, Hengyang, Hunan, 421001, China;
4. Guangzhou Kangda Vocational Technical College, Guangzhou, 510663, China

摘要: 以核电厂为参考背景,提出考虑人因的隐马尔可夫事故诊断过程可靠性模型。该模型由3个评价部分组成,对每一部分提出特定的函数来估计诊断过程的人因失误率,通过实验对提出的方法进行测试。测试结果表明,本文模型的人因失误率精确、可靠,提出的方法比单一的威布尔函数更准确,并得到适合该过程的神经网络激励函数。
- 人因事件 /
- 隐马尔夫 /
- 可靠性模型 /
- 神经网络
Abstract: Taking the nuclear power plant as the reference background,the authors propose a particular hide Markov model for diagnosing process with human factors.The model comprises of three assessment parts.For each part,the authors come up with specific function in order to assess human factors error probability of diagnosing process.The proposed methods are tested by experiments.From results of experiments,we can easily see that human factors error probability is precise and reliable in the model,the proposed method is more accurate than a single Weibull function,and that neural network predictive functions that are more suitable are obtained in diagnosing process.The method can be applied to human factors reliability analysis in nuclear power plant emergency.
- Human factor event /
- Hide Markov /
- Reliability model /
- Neural network.