Human Performance Detection Using Operator Action Log of Nuclear Power Plant

Xinyu Dai, Ming Yang (), Jipu Wang, Zhihui Xu and Hanguan Wen
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Xinyu Dai: College of Nuclear Science and Technology, Harbin Engineering University, Harbin 150001, China
Ming Yang: College of Nuclear Science and Technology, Harbin Engineering University, Harbin 150001, China
Jipu Wang: Institute for Advanced Study in Nuclear Energy & Safety, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
Zhihui Xu: College of Nuclear Science and Technology, Harbin Engineering University, Harbin 150001, China
Hanguan Wen: School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China

Energies, 2023, vol. 16, issue 4, 1-13

Abstract: The introduction of digital technologies into the main control room of a nuclear power plant also introduces new human errors. The operator log records the control information of operators on systems and equipment, and provides an important data source for the retrospective investigation of operating events in a nuclear power plant. A traditional operator log review is conducted manually, which has some major problems, such as being time-consuming and inefficient. This paper proposes an automatic detection method for operator logs, which models an operating procedure at three levels, including procedure, step and action. Such a model clarifies the overall logic and basic attributes of the operating procedure, and can be used as a standardized template of a control action sequence to compare with the actual operation actions in the operator log, so as to identify possible human performance deviations. This paper explains the method, and discusses the advantages and limitations of the proposed method.

Keywords: human error; nuclear safety; operation log audit (OLA); data mining; nuclear power plant (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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