作者机构:
[Zhang, Meihui; Li, Yu; Dai, Licao] Univ South China, Inst Human Factors, Hengyang 421001, Peoples R China.;[Li, Yu] Univ South China, Sch Comp Sci, Hengyang 421001, Peoples R China.;[Zhang, Meihui] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.
通讯机构:
[Licao Dai] I;Institute of Human Factors, University of South China, Hengyang 421001, China
关键词:
clustering;eyes’ blink rate;fatigue;mouse velocity;nuclear power plant main control room;PERCLOS;supervised learning
摘要:
Abstract: Fatigue affects operators’ safe operation in a nuclear power plant’s (NPP) main control room (MCR). An accurate and rapid detection of operators’ fatigue status is significant to safe operation. The purpose of the study is to explore a way to detect operator fatigue using trends in eyes’ blink rate, number of frames closed in a specified time (PERCLOS) and mouse velocity changes of operators. In experimental tasks of simulating operations, the clustering method of Toeplitz Inverse Covariance-Based Clustering (TICC) is used for the relevant data captured by non-invasive techniques to determine fatigue levels. Based on the determined results, the data samples are given labeled fatigue levels. Then, the data of fatigue samples with different levels are identified using supervised learning techniques. Supervised learning is used to classify different fatigue levels of operators. According to the supervised learning algorithm in different time windows (20 s–60 s), different time steps (10 s–50 s) and different feature sets (eye, mouse, eye-plus-mouse) classification performance show that K-Nearest Neighbor (KNN) perform the best in the combination of the above multiple indexes. It has an accuracy rate of 91.83%. The proposed technique can detect operators’ fatigue level in real time within 10 s. Keywords: fatigue; nuclear power plant main control room; eyes’ blink rate; PERCLOS; mouse velocity; clustering; supervised learning
期刊:
Progress in Nuclear Energy,2022年144:104086 ISSN:0149-1970
通讯作者:
Pengcheng Li
作者机构:
[Luo, Zhuhua; Li, Pengcheng; Liu, Yahua; Dai, Licao] Univ South China, Sch Resources Environm & Safety Engn, Hengyang 421001, Hunan, Peoples R China.;[Jin, Xiao; Luo, Zhuhua; Li, Pengcheng; Liu, Yahua; Liu, Zhen; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
通讯机构:
[Pengcheng Li] S;School of Resources, Environment and Safety Engineering, University of South China, Hengyang 421001, Hunan, People's Republic of China<&wdkj&>Human Factor Institute, University of South China, Hengyang 421001, Hunan, People's Republic of China
关键词:
Team situation awareness;Human reliability analysis;Dynamic Bayesian network;Digital nuclear power plants
摘要:
Team situation awareness (TSA) reliability is an important factor for team reliability. Moreover, situation awareness (SA) is a prominent problem in digital nuclear power plants (NPPs). Currently, since there is no suitable method to dynamically assess TSA reliability, we constructed a dynamical assessment method of TSA reliability based on a dynamic Bayesian network (DBN) to evaluate TSA reliability. First of all, a TSA causal concept model through qualitative analysis, expert group discussion and sample data analysis. On this basis, the quantitative assessment method of TSA reliability was constructed based on DBN and obtained probability distribution of variables. A standardized method was established to obtain the probability distribution of variables. Furthermore, we evaluated TSA dynamic reliability in a steam generator tube rupture (SGTR) accident. The results showed that the error probability of TSA decreased, and the level of TSA reliability continuously increased in SGTR. TSA reliability can be dynamically predicted by causal reasoning, the most important cause of TSA error could be identified by diagnostic reasoning, which provided theoretical support for the targeted prevention of human error. Finally, this established method was proved to be reasonable through sensitivity analysis.
期刊:
Nuclear Engineering and Design,2021年376:111112- ISSN:0029-5493
作者机构:
[Li, Peng-cheng; Luo, Zhu-hua; Wang, Yan-xin; Chen, Jian-hua; Dai, Li-cao] Univ South China, Human Factor Inst, Hengyang, Hunan, Peoples R China.
关键词:
Digital nuclear power plant;Situation awareness;Team situation awareness;Task complexity;Knowledge and experience level;Workload
摘要:
With the improvement of digital level of main control rooms (MCRs) of nuclear power plants (NPPs), the issue of situation awareness (SA) of operator becomes particularly prominent in NPP operations. More and more scholars have done some research on SA and team situation awareness (TSA). In order to explore the effects of performance shaping factors (PSFs) on SA, TSA and workload, the effects of task complexity and operators? knowledge and experience level on operators? SA, TSA and workload were studied through simulator experiments. The results show significant effects on the operators? SA and TSA levels. The higher the complexity of task, the lower the level of operators? SA and TSA; and the higher the level of knowledge and experience, the higher the level of operators? SA and TSA. Experiments also show that task complexity and the level of knowledge and experience have a significant impact on the operator?s workload. The higher the task complexity is, the higher the operator?s workload level is, and the higher the knowledge and experience level is, the lower the workload level of the operator is. The research results provide a theoretical basis for improving the level of SA and reducing workload, and provide theoretical and experimental guidance for identifying the impacts of PSF on SA, TSA and workload.
作者机构:
[Li, Pengcheng; Zhang, Li; Li, Xiaofang; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Pengcheng] Univ N Carolina, Syst Engn & Engn Management, Charlotte, NC 28223 USA.;[Li, Pengcheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.
通讯机构:
[Dai, Licao] U;Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词:
Model validation;Simulation experiment;SA reliability;Fuzzy logic-AHP;Digital nuclear power plants
摘要:
Situation awareness (SA) reliability of operators is an important component of human reliability analysis (HRA) in digital nuclear power plants (NPPs). Therefore, how to identify effectively and reliably the risk of SA errors is of great significance for SA error prevention and risk reduction. SA reliability assessment model or method based on fuzzy logic and analytic hierarchy process (AHP) is forwarded in the first paper. In order to prove its effectiveness and reliability, sensitivity analysis and simulator experiments are applied to testify our model in this paper. The results show that the proposed assessment model of SA reliability has a certain degree of sensitivity as well as an accuracy of prediction, and there are a strong correlation and consistency between the predicted value from fuzzy inference system and the real value (or observed value) from simulator experiments. Although there are some differences between the predicted value and the real value based on the perspective of HRA, the model can be used to predict SA error probability or SA reliability within the range of 10 error factors as well as provide data and theoretical support for SA reliability assessment.
作者机构:
[Li, Pengcheng; Zhang, Li; Li, Xiaofang; Dai, Licao] Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Pengcheng] Univ N Carolina, Syst Engn & Engn Management, Charlotte, NC 28223 USA.;[Li, Pengcheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Zou, Yanhua] Hunan Inst Technol, Inst Human Factor & Safety Management, Hengyang 421002, Hunan, Peoples R China.
通讯机构:
[Li, Pengcheng] U;Univ South China, Human Factor Inst, Hengyang 421001, Hunan, Peoples R China.
关键词:
Situation awareness reliability;Fuzzy logic;Analytic hierarchy process;Digital nuclear power plants
摘要:
In digital control rooms, situation awareness (SA) reliability has become an important element affecting operator's reliability. In order to establish a more reasonable assessment method of SA reliability under the condition of very lack of data, based on the established influential factor model of SA reliability considering the causality relationship of performance shaping factors (PSFs) in this paper, a fuzzy logic and analytic hierarchy process (AHP)-based method is established to more objectively assess SA reliability. The weight of PSFs is identified using AHP, and a fuzzy logic method is used to simulate the fuzzy assessment and reasoning process of operator's SA reliability, and a standardized method is built to determine the fuzzy rule base of fuzzy reasoning system for SA reliability assessment for reducing the subjectivity and uncertainty of expert judgment. Finally, an example is provided to illustrate the specific application of the proposed method. The results show that the established method takes account of the weight of PSFs and their causal influencing relationship, and the fuzzy logic method used to assess SA reliability can overcome the subjectivity and uncertainty of expert judgment, which makes the assessment results more objective and realistic. Furthermore, the method can be used to get more SA error data and have a wide range of application value.
作者:
Zou, Yanhua*;Zhang, Li;Dai, Licao;Li, Pengcheng;Qing, Tao
期刊:
Nuclear Engineering and Technology,2017年49(2):335-341 ISSN:1738-5733
通讯作者:
Zou, Yanhua
作者机构:
[Zhang, Li; Zou, Yanhua] Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang, Hunan, Peoples R China.;[Qing, Tao; Li, Pengcheng; Dai, Licao] Univ South China, Human Factors Inst, Hengyang, Hunan, Peoples R China.
通讯机构:
[Zou, Yanhua] H;Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang, Hunan, Peoples R China.
会议名称:
13th International Conference on Probabilistic Safety Assessment and Management (PSAM)
会议时间:
OCT 02-07, 2016
会议地点:
Seoul, SOUTH KOREA
会议主办单位:
[Zou, Yanhua;Zhang, Li] Hunan Inst Technol, Inst Human Factors Engn & Safety Management, Hengyang, Hunan, Peoples R China.^[Dai, Licao;Li, Pengcheng;Qing, Tao] Univ South China, Human Factors Inst, Hengyang, Hunan, Peoples R China.
关键词:
Digital Control System;Human Reliability Analysis;Nuclear Power Plant
摘要:
The main control room (MCR) in advanced nuclear power plants (NPPs) has changed from analog to digital control system (DCS). Operation and control have become more automated, centralized, and accurate due to the digitalization of NPPs, which has improved the efficiency and security of the system. New issues associated with human reliability inevitably arise due to the adoption of new accident procedures and digitalization of main control rooms in NPPs. The LingAo II NPP is the first digital NPP in China to apply the state-oriented procedure. In order to address issues related to human reliability analysis for DCS and DCS + state-oriented procedure, the Hunan Institute of Technology conducted a research project based on a cooperative agreement with the LingDong Nuclear Power Co. Ltd. This paper is a brief introduction to the project.