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Visual Analysis Of Trend Anomaly Of Key Parameters In Nuclear Power Plant

Posted on:2018-03-30Degree:MasterType:Thesis
Country:ChinaCandidate:Y H ZhaoFull Text:PDF
GTID:2322330542985010Subject:Software engineering
Abstract/Summary:PDF Full Text Request
Digital,information management,intelligent,interactive decision-making on the construction of nuclear power plants put forward higher requirements.The operation of the key parameters in the nuclear power plant is the embodiment of the operation state of the power plant,which is of vital importance to the safe production of the whole nuclear power plant and the focus of the operation and safety analysis personnel.Parameter alarm is an important means of nuclear power safety monitoring.Taking the nuclear power plant as an example,this paper uses the historical operation data and real-time data of the power plant for many years to study the trend change visualized analysis method of the key parameter in early warning.As the operating parameters of nuclear power plants are high-dimensional data,and the number is many,the visual analysis of this work has challenges.We provide the time dimension,tree structure,correlation analysis tools to analyze,using dynamic forecasting and trend forecasting method for deterioration of the trend of early warning.Through the analysis of our experimental results,we communicated with the relevant managers about our findings,they are satisfied with our visual analysis.The significance of this study is to apply the technology of visualization and visual analysis to the nuclear power plant,to make full use of the historical data and real-time operation data of power plant,analyze and process the data to study the trend of nuclear power plant.Through this study,the relevant personnel can advance the operation of nuclear power plant anomalies,identify fault information in the potential,mining the parameters of the abnormal parameters and finish comprehensive troubleshooting.
Keywords/Search Tags:Nuclear power plant, Key parameter, Trend prediction, Association analysis, Visual analysis
PDF Full Text Request
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