Abstract: The present invention relates to a signal processing device for monitoring states of wind-power turbine blades and a method thereof, the signal processing device comprising: an optical fiber sensor unit for sensing moment of rotation of three blades so as to output the moment of rotation as blade signals; a signal transformation unit for converting three blade signals into two fore-ape signals; a rotation information input unit for sensing rotation information of the blades; a rotation speed estimation unit for estimating a rotation speed of the blades on the basis of the rotation information; a state determination unit which removes rotation components from the fore-ape signals and determines whether an operation of a blade is abnormal; and an output unit for outputting the determination result.

Abstract: The present invention provides a method of automatically calculating a power curve limit for the power curve monitoring of a wind turbine that may set an optimal power curve limit by automatically calculating a power curve limit for power curve monitoring even if wind speed-power data measured at a wind turbine includes a large amount of abnormal data in addition to normal data. To this end, the present invention includes: classifying, by an input data classifying unit, the input data on wind power generation through a variable speed bin; calculating, by a power calculating unit, a power average value and standard deviation for each bin for the classified input data; estimating, by a power curve estimating unit, a power curve for the calculated power average value for each bin; searching for, by a limit searching unit, an accurate power curve limit while moving the estimated power curve; and setting, by a data extracting unit, the data included in the accurate power curve limit as new input data.

Abstract: The present invention relates to a signal processing device for monitoring states of wind-power turbine blades and a method thereof, the signal processing device comprising: an optical fiber sensor unit for sensing moment of rotation of three blades so as to output the moment of rotation as blade signals; a signal transformation unit for converting three blade signals into two fore-ape signals; a rotation information input unit for sensing rotation information of the blades; a rotation speed estimation unit for estimating a rotation speed of the blades on the basis of the rotation information; a state determination unit which removes rotation components from the fore-ape signals and determines whether an operation of a blade is abnormal; and an output unit for outputting the determination result.

Abstract: The present invention provides a method of automatically calculating a power curve limit for the power curve monitoring of a wind turbine that may set an optimal power curve limit by automatically calculating a power curve limit for power curve monitoring even if wind speed-power data measured at a wind turbine includes a large amount of abnormal data in addition to normal data. To this end, the present invention includes: classifying, by an input data classifying unit, the input data on wind power generation through a variable speed bin; calculating, by a power calculating unit, a power average value and standard deviation for each bin for the classified input data; estimating, by a power curve estimating unit, a power curve for the calculated power average value for each bin; searching for, by a limit searching unit, an accurate power curve limit while moving the estimated power curve; and setting, by a data extracting unit, the data included in the accurate power curve limit as new input data.