Wind turbine generator yaw risk determination method and system and computer readable storage medium

The invention provides a wind turbine generator yaw risk determination method and system and a computer readable storage medium. The method for determining the yaw risk of the wind turbine generator comprises the steps of obtaining historical operation time of the wind turbine generator and historic...

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Bibliographische Detailangaben
Hauptverfasser:	JIANG XIAOMO, TANG WEIJIAN, HUI HUAIYU, LIN LIN, MA MINGJUN, CHENG XIAOBIN, CHEN QING, ZHAO HAIXIN
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	BLASTING CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES HEATING LIGHTING MACHINES OR ENGINES FOR LIQUIDS MECHANICAL ENGINEERING OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR PHYSICS PRODUCING MECHANICAL POWER SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR WEAPONS WIND MOTORS WIND, SPRING WEIGHT AND MISCELLANEOUS MOTORS
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Beschreibung
Zusammenfassung:	The invention provides a wind turbine generator yaw risk determination method and system and a computer readable storage medium. The method for determining the yaw risk of the wind turbine generator comprises the steps of obtaining historical operation time of the wind turbine generator and historical yaw data generated when the wind turbine generator operates within the historical operation time; the wind turbine generator sets comprise healthy generator sets and fault generator sets; the historical operation time comprises the historical operation time of the healthy unit and the historical operation time of the fault unit; the historical yaw data comprises historical yaw data of the healthy unit and historical yaw data of the fault unit; establishing a proportional risk regression model according to the historical operation time and the historical yaw data; and using the proportional risk regression model to determine an accumulated failure rate of the wind turbine generator in the historical operation tim