An Intelligent Experience Retention System: Challenges and Limitations for Operation and Maintenance in Nuclear Power Plants

被引:1
|
作者
Gabbar, Hossam A. [1 ]
Al Jabar, Sk Sami [2 ]
Hassan, Hassan A. [3 ]
Ren, Jing [2 ]
机构
[1] Ontario Tech Univ, Fac Energy Syst & Nucl Sci, Oshawa, ON L1G 0C5, Canada
[2] Ontario Tech Univ, Dept Elect & Comp Engn, Oshawa, ON L1G 0C5, Canada
[3] Ontario Power Generat, Inspect & Reactor Innovat, Whitby, ON L1N 9E3, Canada
来源
IEEE SYSTEMS MAN AND CYBERNETICS MAGAZINE | 2021年 / 7卷 / 04期
基金
加拿大自然科学与工程研究理事会;
关键词
Training data; Knowledge engineering; Query processing; Semantics; Maintenance engineering; Nuclear power generation; Probabilistic logic; Industrial plants;
D O I
10.1109/MSMC.2021.3098981
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This article presents an intelligent experience retention system (IERS), which is designed to overcome challenges and limitations of capturing human experience related to operating procedures for plant operation and maintenance in nuclear power plants. It is time-consuming to find specific information from thousands of input documents. Less experienced employees cannot operate complex tasks due to having less knowledge and training about the documents and their operation. Research gaps in current knowledge structuring and retrieval methods are discussed and used to identify essential features to achieve effective methods to manage instructive text (iText) related to learning and answering queries connected to operating procedures. Knowledge structure is proposed to represent inputs from documents, data, text, and voice related to operation and maintenance instructions in nuclear power plants. Human experience is captured and integrated within the structured knowledge in an integrated scheme, called the human experience semantic network (HESN), which includes deterministic, qualitative, and probabilistic parameters and attributes that are captured and dynamically tuned throughout the execution of the system.
引用
收藏
页码:31 / 34
页数:4
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