Disclosed are a method and apparatus for detecting a fault, and a method and apparatus for training a model. The method includes: acquiring characteristic data and actual temperature of a first wind turbine among n wind turbines, wherein the characteristic data of the first wind turbine is intended to characterize a working state of the first wind turbine, and n is an integer greater than 1; acquiring a prediction temperature set by inputting the characteristic data of the first wind turbine into a temperature prediction model corresponding to each of the n wind turbines; and detecting, based on the predicted temperature set and the actual temperature of the first wind turbine, whether the first wind turbine encounters a fault. Compared with the related art which depends on the working experience of the staff, the technical solution according to the embodiments of the present disclosure can more accurately detect whether a wind turbine encounters a fault, and provide early warning in time, so as to reduce the failure rate of the wind turbine.

Disclosed are a method and apparatus for detecting a fault, and a method and apparatus for training a model. The method includes: acquiring characteristic data and actual temperature of a first wind turbine among n wind turbines, wherein the characteristic data of the first wind turbine is intended to characterize a working state of the first wind turbine, and n is an integer greater than 1; acquiring a prediction temperature set by inputting the characteristic data of the first wind turbine into a temperature prediction model corresponding to each of the n wind turbines; and detecting, based on the predicted temperature set and the actual temperature of the first wind turbine, whether the first wind turbine encounters a fault. Compared with the related art which depends on the working experience of the staff, the technical solution according to the embodiments of the present disclosure can more accurately detect whether a wind turbine encounters a fault, and provide early warning in time, so as to reduce the failure rate of the wind turbine.

The present disclosure relates to methods for determining reliability of an azimuth measurement system in a wind turbine. The methods comprise measuring loads with load sensors during operation and determining in-plane moments with rotor rotational speed frequency of one or more blades based on the measured loads. The methods further comprise measuring an azimuthal position of a wind turbine rotor. The method also comprises determining that the azimuth measurement system has reduced reliability if an angular phase of the in-plane moments deviates from the measured azimuthal position by more than a first threshold value. The present disclosure also relates to wind turbine systems incorporating azimuth measurements and methods for on-line determination of correct functioning of azimuth sensors.

The present disclosure relates to methods for determining reliability of an azimuth measurement system in a wind turbine. The methods comprise measuring loads with load sensors during operation and determining in-plane moments with rotor rotational speed frequency of one or more blades based on the measured loads. The methods further comprise measuring an azimuthal position of a wind turbine rotor. The method also comprises determining that the azimuth measurement system has reduced reliability if an angular phase of the in-plane moments deviates from the measured azimuthal position by more than a first threshold value. The present disclosure also relates to wind turbine systems incorporating azimuth measurements and methods for on-line determination of correct functioning of azimuth sensors.

A method for monitoring of a wind turbine including: a) acquiring respective values of one or more operation variables of the wind turbine at the corresponding operation time point; b) determining the value of a tower clearance resulting from the acquired values of the operation variables with the aid of a trained data driven model, where the value of an output variable which is the tower clearance or a variable correlated with the tower clearance is predicted by feeding the acquired value of each operation variable as a digital input to the trained data driven model which outputs the predicted value of the output variable as a digital output, the tower clearance being shortest the distance between the tower and the tip of a specific rotor blade from the rotor blades when the specific rotor blade is in its lowermost position in which it points downward in the vertical direction.

An information generating device includes a control unit for causing a motor to rotate a pinion gear meshing with a ring gear while a predetermined braking force is applied to brake rotation of a turnable part of a wind turbine, thereby causing a fastening part to deform, where the fastening part is provided to fixedly attach the motor to a target part, a deformation amount obtaining unit for obtaining an amount of deformation experienced by the fastening part, and an information generating unit for generating correlation information indicating a correspondence between a driving torque of the motor and the amount of deformation experienced when the driving torque is used to rotate the motor.

Disclosed is a sensor roller for monitoring a lubrication condition of a roller bearing, the sensor roller providing a measuring unit for measuring at least a temperature, a speed change and a load of the roller, and a processing unit for generating a temperature profile, a speed change profile and a load profile of the roller based on the measured temperature and speed change.

According to an example aspect of the present invention, there is provided a sensor comprising at least one strut configured to be coupled to a surface of an object at a first end of the strut, a structure connected to a second end of the at least one strut, wherein the structure is V-shaped, U-shaped, curved or arched and configured to be coupled to the surface at both ends, a plurality of cavities positioned along the structure on both sides of the at least one strut, and a plurality of fibre-optic pressure transducers, wherein a single fibre-optic pressure transducer is arranged within each of the cavities, and wherein the sensor is configured such that at least some of the fibre-optic pressure transducers are arranged at different distances from the surface of the object.

A method for determining a yaw position offset of a wind turbine (1) is provided. A neighbouring wind turbine (2) of the wind farm is identified, the neighbouring wind turbine (2) being arranged in the vicinity of the wind turbine (1). Produced power data and/or wind speed data from the wind turbine (1) and from the neighbouring wind turbine (2), is obtained during a period of time, and a yaw position offset of the wind turbine (1) is derived, based on the obtained produced power data and/or wind speed data, and based on the geographical positions of the wind turbine (1) and the neighbouring wind turbine (2). A local maximum and a local minimum being separated by an angular difference in yaw position being substantially equal to 180°.

A method for determining a yaw position offset of a wind turbine (1) is provided. A neighbouring wind turbine (2) of the wind farm is identified, the neighbouring wind turbine (2) being arranged in the vicinity of the wind turbine (1). Produced power data and/or wind speed data from the wind turbine (1) and from the neighbouring wind turbine (2), is obtained during a period of time, and a yaw position offset of the wind turbine (1) is derived, based on the obtained produced power data and/or wind speed data, and based on the geographical positions of the wind turbine (1) and the neighbouring wind turbine (2). A local maximum and a local minimum being separated by an angular difference in yaw position being substantially equal to 180°.