A method for setting a fully or partially built wind power installation having a rotor having a plurality of rotor blades whose blade angle can be adjusted, wherein the wind power installation can take on variable operating situations, and each operating situation is characterized by a combination of settable installation settings of the wind power installation and environmental conditions that can be captured, with the result that an operating situation can be set for given environmental conditions by setting the installation settings, and operating situations that should be avoided and/or suitable operating situations are stored in a memory by storing a combination of environmental conditions and installation settings as a combination to be avoided for an operating situation that should be avoided in each case, and/or storing a combination of environmental conditions and installation settings as a suitable combination for a suitable operating situation in each case, and, to avoid operating situations that should be avoided, environmental conditions are captured and, depending on the captured environmental conditions and the stored combinations to be avoided and/or suitable combinations, installation settings of the wind power installation are selected and set such that installation settings of stored combinations to be avoided are avoided, and/or installation settings are selected from stored suitable combinations.

The present application discloses a blade fault diagnosis method, apparatus and system, and a storage medium. the method includes: acquiring a blade rotation audio collected by an audio collection device during operation of a wind turbine generator system; preprocessing the blade rotation audio based on a wind noise filtering algorithm to obtain a blade rotation audio filtered out of wind noise; dividing the blade rotation audio filtered out of wind noise to obtain audio segments corresponding to blades of the wind turbine generator system respectively; diagnosing, based on the audio segments, whether the blades each corresponding to one of the audio segments are faulty. The present application can diagnose whether a corresponding blade is faulty respectively according to the audio segments of different blades, which improves the accuracy of the diagnosis results.

The present disclosure is related to methods (400; 500; 600) configured for detecting the state of a wind turbine blade (22). The methods (400; 500; 600) comprising receiving (401; 501) load signals from a wind turbine blade (22), determining (402; 503) an energy of the load signal in a first and second frequency and comparing (403; 504) said energy to generate a flag signal if the energy in the first frequency is smaller than the energy in the second frequency. A control system (600) suitable to detect the state of a wind turbine blade (22) is also provided, as well as wind turbines (10) including such a control system (600).

A wind turbine has an object position and/or speed detection device including: at least one leaky feeder, at least one electromagnetic transmitter connected to the least one leaky feeder for transmitting a first electromagnetic signal along the at least one leaky feeder towards a target object, whose position is to be detected, at least one electromagnetic receiver connected to the least one leaky feeder for receiving from the at least one leaky feeder a second electromagnetic signal, the second electromagnetic signal reflected from the target object when the first electromagnetic signal hits the target object, a processing unit connected to the electromagnetic transmitter and the electromagnetic receiver and configured to analyze the first electromagnetic signal and the second electromagnetic signal for determining the position and/or speed and/or direction and/or the size of the target object.

A wind turbine rotor blade imaging arrangement is provided, including a multi-axis gimbal mounted to the exterior of the wind turbine and configured to adjust its orientation in response to one or more received settings; a camera mounted on the multi-axis gimbal and arranged to capture images of a rotor blade; an image analysis unit configured to analyze the captured images; and a camera orientation controller configured to compute updated gimbal settings on the basis of the image analysis output.

Provided is a method for monitoring one or more wind turbines in a wind farm, each wind turbine having a rotor with rotor blades which are rotatable around a rotor axis, wherein one or several times during the operation of the wind farm a process is performed that includes i) obtaining a digital image of the respective rotor blade, the image being a current image taken by a camera looking at the respective rotor blade; ii) determining one or more operation characteristics of the respective rotor blade by processing the image by a trained data driven model, where the image is fed as a digital input to the trained data driven model and the trained data driven model provides the one or more operation characteristics of the respective rotor blade as a digital output.

A device may receive historical operational data for a mechanical system, such as a rotor blade of a wind turbine. The device may determine one or more quality grades for each of one or more materials of the system, e.g., the rotor blade. The one or more quality grades may be determined by using a data model to process the historical operational data. The data model may be trained using machine learning based on one or both of historical operational data for similar systems, e.g., other rotor blades, and end-of-life (EOL) testing data for the same. The device may determine a recycling recommendation based on the one or more quality grades. The recycling recommendation may include instructions relating to recycling the one or more materials. The device may deliver the recycling recommendation to another device or recipient.

A lightning protection system is provided, in particular for a rotor blade, the system including: i) a lightning conductor for conducting electrical energy of a lightning; and ii) a measurement device electrically coupled to the lightning conductor and configured to measure an impedance with respect to the lightning conductor. Further, a rotor blade and a wind turbine are provided.

The present disclosure relates to controlling an operation of a wind turbine. A first plurality of extreme load measures indicative of extreme loads experienced by at least part of the wind turbine during the first period of time are determined and a load probability characteristic is then determined based on a statistical analysis of the distribution of the first plurality of extreme load measures. A control strategy for controlling the operation of the wind turbine is then modified based at least in part on a comparison of the load probability characteristic and a design load limit and the wind turbine is then subsequently controlled in accordance with the modified control strategy for a second period of time.

A method, an apparatus, an electronic device, and a computer-readable storage medium for detecting a wind turbine blade based on drone aerial photography are provided. The method includes: determining first initial three-dimensional position coordinates and a posture of a wind turbine; determining second initial three-dimensional coordinates of a first expected position with respect to a front shooting position of the wind turbine, based on the first initial three-dimensional position coordinates, the posture, and a preset distance; inputting the second initial three-dimensional coordinates of the first expected position into a flight control system of the drone, and controlling the drone to fly to the second initial three-dimensional coordinates based on a GPS system; and controlling the drone to track at least one first key point of blades of the wind turbine, and determining a three-dimensional movement trajectory of the first key point in a camera coordinate system.