Abstract: A wind farm supervision monitoring method includes: displaying, by a user interface (UI) unit, a location of the site server on a map along with a dashboard menu, a navigation menu, and an alarm & event menu; collecting, by a data collection unit, data about status monitoring of each wind turbine from the site server; detecting, by an abnormality status detection unit, an abnormality status of each wind turbine based on the data about the status monitoring of each wind turbine and issuing an alarm based on the detecting the abnormality status; providing, by a supervision unit, a turbine operation status of each wind turbine using the dashboard menu, managing operation and maintenance; and establishing, by the supervision unit, an operation and maintenance plan for the detected abnormality status of the wind turbine.

Abstract: The present disclosure relates to a method and a system for repairing a wind generator based on weather information. According to an exemplary embodiment of the present disclosure, it is possible to effectively calculate a repairing time of the wind generator based on weather information.

Abstract: A wind farm supervision monitoring system includes: a data collection unit configured to collect data about a status monitoring of each wind turbine from at least one site server; an abnormality status detection unit configured to detect an abnormality status of each wind turbine based on the collected data about the status monitoring and issue an alarm; a wind data management unit configured to early detect a fault of each wind turbine and or monitor performance of each wind turbine based on the data about the status monitoring or the data about the abnormality status; and a supervision unit configured to manage a turbine operation status and operation and maintenance of each wind turbine and provide information for establishing an operation and maintenance plan for the detected abnormality status of the wind turbine.

Abstract: Provided is a wind power generation management apparatus including: a collection unit configured to collect first data generated in a wind power plant; a fault occurrence prediction unit configured to compare the collected first data with a predefined normal state model, to create a second data indicating a state of the wind power plant based on a result of the comparison, and to predict occurrence of a fault in the wind power plant according to the second data; and a maintenance plan establishment unit configured to estimate an operating time corresponding to a time from a start of the wind power plant until the fault occurs, and to generate a maintenance plan which can be performed for the fault during the estimated operating time.

Abstract: Disclosed herein is a vibration monitoring and diagnosing system for monitoring conditions of a wind power generator and diagnosing a defective portion thereof using vibration characteristics obtained from acceleration sensors mounted to the wind power generator. A vibration-based defect detecting method may include: collecting vibration data of the wind power generator using the plurality of sensors; extracting a first characteristic value of a time domain based on the vibration data; extracting characteristic values in one or more frequency bands for a location of each sensor in a frequency domain or an envelope frequency domain if the first characteristic value is greater than a preset alarm setting value; and determining that a defect is present when at least one characteristic value of the characteristic values is greater than a preset normal value.

Abstract: An apparatus for diagnosing abnormal operation of a rotor. The apparatus includes a first sensor provided around a shaft in order to detect vibration occurring while the shaft provided in a rotor axially rotates, a second sensor to generate a periodic pulse signal over time whenever the shaft rotates once, and a controller to determine an operation state of the rotor by receiving signals detected by the first and second sensors. When an aperiodic pulse signal is detected in the rotor, the controller determines a position of the rotor at which the aperiodic pulse signal is generated, and a display indicates the position of the rotor in which the aperiodic pulse signal is generated, according to information calculated by the controller.

Abstract: Disclosed herein is a vibration monitoring and diagnosing system for monitoring conditions of a wind power generator and diagnosing a defective portion thereof using vibration characteristics obtained from acceleration sensors mounted to the wind power generator. A vibration-based defect detecting method may include: collecting vibration data of the wind power generator using the plurality of sensors; extracting a first characteristic value of a time domain based on the vibration data; extracting characteristic values in one or more frequency bands for a location of each sensor in a frequency domain or an envelope frequency domain if the first characteristic value is greater than a preset alarm setting value; and determining that a defect is present when at least one characteristic value of the characteristic values is greater than a preset normal value.

Abstract: A wind farm supervision monitoring system includes: a data collection unit configured to collect data about a status monitoring of each wind turbine from at least one site server; an abnormality status detection unit configured to detect an abnormality status of each wind turbine based on the collected data about the status monitoring and issue an alarm; a wind data management unit configured to early detect a fault of each wind turbine and or monitor performance of each wind turbine based on the data about the status monitoring or the data about the abnormality status; and a supervision unit configured to manage a turbine operation status and operation and maintenance of each wind turbine and provide information for establishing an operation and maintenance plan for the detected abnormality status of the wind turbine.

Abstract: A wind farm supervision monitoring method includes: displaying, by a user interface (UI) unit, a location of the site server on a map along with a dashboard menu, a navigation menu, and an alarm & event menu; collecting, by a data collection unit, data about status monitoring of each wind turbine from the site server; detecting, by an abnormality status detection unit, an abnormality status of each wind turbine based on the data about the status monitoring of each wind turbine and issuing an alarm based on the detecting the abnormality status; providing, by a supervision unit, a turbine operation status of each wind turbine using the dashboard menu, managing operation and maintenance; and establishing, by the supervision unit, an operation and maintenance plan for the detected abnormality status of the wind turbine.

Abstract: The present disclosure relates to a method and a system for repairing a wind generator based on weather information. According to an exemplary embodiment of the present disclosure, it is possible to effectively calculate a repairing time of the wind generator based on weather information.

Abstract: An apparatus for diagnosing abnormal operation of a rotor. The apparatus includes a first sensor provided around a shaft in order to detect vibration occurring while the shaft provided in a rotor axially rotates, a second sensor to generate a periodic pulse signal over time whenever the shaft rotates once, and a controller to determine an operation state of the rotor by receiving signals detected by the first and second sensors. When an aperiodic pulse signal is detected in the rotor, the controller determines a position of the rotor at which the aperiodic pulse signal is generated, and a display indicates the position of the rotor in which the aperiodic pulse signal is generated, according to information calculated by the controller.

Abstract: Provided is a wind power generation management apparatus including: a collection unit configured to collect first data generated in a wind power plant; a fault occurrence prediction unit configured to compare the collected first data with a predefined normal state model, to create a second data indicating a state of the wind power plant based on a result of the comparison, and to predict occurrence of a fault in the wind power plant according to the second data; and a maintenance plan establishment unit configured to estimate an operating time corresponding to a time from a start of the wind power plant until the fault occurs, and to generate a maintenance plan which can be performed for the fault during the estimated operating time.