Research on the Diagnosis and Prediction of Equipment Faults in Hydropower Stations Based on Big Data Technology
This article proposes a research method based on big data technology for the diagnosis and prediction of equipment faults in hydropower stations.Firstly,it introduces the development of big data technology and its im-portance in the diagnosis and prediction of equipment faults in hydropower stations.Secondly,it studies the correla-tion between big data and the equipment of hydropower stations,including the general performance and possible types of faults of the equipment of hydropower stations,and the application of big data technology in the opera-tional monitoring of the equipment of hydropower stations.Thirdly,it explores the application of big data technol-ogy in the diagnosis and prediction of equipment faults in hydropower stations,including data collection and pre-processing,the analysis of fault modes and effects,and fault diagnosis strategies and technologies based on big data.Fourthly,it introduces the fault prediction model based on historical data and real-time data,fault prediction tech-nologies based on machine learning,and methods for verifying and evaluating fault prediction results.Fifthly,through the study and analysis of typical application cases,it verifies the effectiveness of big data technology in the diagnosis and prediction of equipment faults in hydropower stations.
Big data technologyHydropower station equipmentFault diagnosisFault prediction
万方数据
维普
