The present disclosure provides a defect-detectable fiber fabric, including a plurality of bunches of fibers and a plurality of braided threads configured to respectively fix together fibers of each bunch of fibers. The plurality of braided threads include first braided threads each having a color different from a color of any of the plurality of bunches of fibers, and a respective distance between every two adjacent first braided threads is configured to make wrinkle defects that could be formed in fabric layers detectable. After the curing and molding, the positions of the defects and the layer(s) where the defects are formed can be determined according to the states of the first braided threads.

An abnormality determination method for a wind power generation device includes: a measurement step (step S1) of measuring sound emitted by the wind power generation device and recording acoustic data; an analysis step (step S2) of performing a spectrogram analysis on the acoustic data recorded in the measurement step, on a frequency axis and in a temporal axis space as a temporal change in a frequency characteristic by using the short-time Fourier transform or the wavelet transform; a detection step (step S3) of detecting, from the analysis result in the analysis step, a signal component emitted from an abnormal portion of the wind power generation device in a time corresponding to rotation of the wind power generation device; and a determination step (step S5) of determining that the wind power generation device is abnormal when the signal component detected in the detection step is greater than or equal to a certain threshold value.

Techniques are provided for monitoring blades of a wind turbine by actively promoting blade vibrations by imposing a pitch actuation signal. A method of operating a wind turbine is disclosed where for each blade of a wind turbine, vibrations of the blade are actively promoted by imposing a pitch actuation signal to the pitch actuator, and at least one parameter relating to the blade vibration is determined.

Systems and methods for performing external inspections and internal inspections on wind turbine blades and correlating the external and internal inspections with one another are disclosed herein. A method of inspecting a wind turbine blade includes analyzing an exterior of the blade to produce external blade data, analyzing an interior of the blade to produce internal blade data, correlating a first position of the internal blade data with a second position of the external blade, and displaying an image including the first position and the second position.

A system for a wind turbine nacelle includes a rotor head, a plurality of blade holders connected to the rotor head, and a shaft having a first end that extends into the rotor head. Linear movement of the shaft causes movement of the plurality of blade holders. The system further includes an electromechanical pitch actuator connected to a second end of the shaft and configured to translate linearly to move the shaft linearly. The system further includes a linear drive system connected to the electromechanical pitch actuator. The system further includes a fail-safe system connected to the electromechanical pitch actuator via the linear drive system. The fail safe system actuates to force the electromechanical pitch actuator rearward to move the blades into a stall blade position.

The present disclosure provides a system and method for real-time anomaly data determination for turbine blades of a wind turbine. The system receives sensor data associated with a set of turbine blades of the wind turbine. The sensor data indicates one or more structural characteristics associated with each of the set of turbine blades and/or one or more operational characteristics associated with each of the set of turbine blades. The system determines profile data associated with each of the set of turbine blades based on the sensor data. The system determines anomaly data associated with at least one of the set of turbine blades based on the profile data associated with each of the set of turbine blades. The anomaly data indicates a deviation between at least two turbine blades of the set of turbine blades. The system outputs the anomaly data.

A detection unit acquires detection data of a wind turbine generator. A controller generates abnormality information indicating an abnormality or an abnormality sign in the wind turbine generator based on the detection data. The controller transmits the abnormality information to a user terminal.

In order to provide an improved and cost-efficient method and tool for performing a defect detection procedure aiming at the detection of a defect underneath an outer protection layer covering the leading edge of a wind turbine generator blade a method is described during which a tool tip is being biased against the surface of the outer protection layer while being guided over the outer protection layer and deviations in the uniformity of the at least one feedback value are sensed to identify potential defects. A tool and a detection unit suitable for the described method is also described.