Abstract: The invention relates to an assembly for monitoring and/or controlling a wind turbine. The assembly includes a first strain sensor for measuring a first blade bending moment of a rotor blade of a wind turbine in a first spatial direction; a second strain sensor for measuring a second blade bending moment of a rotor blade of a wind turbine in a second spatial direction, which differs from the first spatial direction; an arrangement for determining constant components of forces and moments of the rotor blades provided in the wind turbine; and a controller for combining the first blade bending moment, the second blade bending moment and the constant components.

Abstract: The invention relates to a method by means of which a system that is capable of oscillating can be monitored. The method comprises detection of natural oscillation modes of the system that can oscillate as a function of at least one operating parameter and/or as a function of at least one environmental parameter of the system that is capable of oscillating, creation of a frequency distribution of the detected natural oscillating modes, division of the natural oscillating modes into frequency classes and, in at least one frequency class, determination of a mode profile over the operating parameter and/or over the environmental parameter.

Abstract: Embodiments of the invention describe a method for ascertaining a value of an ice buildup quantity on at least one rotor blade (111, 112) of a wind turbine (100) and to the use thereof.

Abstract: The invention relates to a method for creating a prediction model for ice build-up on wind turbines. The method comprises: detecting ice build-up data at at least one wind turbine; using meteorological data for the location of the at least one wind turbine; feeding in the ice build-up data of the at least one wind turbine and the meteorological data in a machine learning method; and creating a prediction model based on the machine learning method. The invention also relates to a method for predicting ice build-up on wind turbines. The method comprises: detecting ice build-up data at at least one wind turbine; using meteorological data for the location of the at least one wind turbine; and predicting an ice build-up based on a machine-learned model.

Abstract: The invention relates to a method by means of which a system that is capable of oscillating can be monitored. The method comprises detection of natural oscillation modes of the system that can oscillate as a function of at least one operating parameter and/or as a function of at least one environmental parameter of the system that is capable of oscillating, creation of a frequency distribution of the detected natural oscillating modes, division of the natural oscillating modes into frequency classes and, in at least one frequency class, determination of a mode profile over the operating parameter and/or over the environmental parameter.

Abstract: Embodiments describe a method for predicting the accumulation of ice on a rotor blade (111, 112) of a wind turbine (100) and the use thereof.

Abstract: The invention relates to an assembly for monitoring and/or controlling a wind turbine. The assembly includes a first strain sensor for measuring a first blade bending moment of a rotor blade of a wind turbine in a first spatial direction; a second strain sensor for measuring a second blade bending moment of a rotor blade of a wind turbine in a second spatial direction, which differs from the first spatial direction; an arrangement for determining constant components of forces and moments of the rotor blades provided in the wind turbine; and a controller for combining the first blade bending moment, the second blade bending moment and the constant components.

Abstract: The invention relates to a method (200) for monitoring a status of at least one wind turbine. The method (200) comprises: detecting first measurement signals via one or more sensors (210), wherein the first measurement signals provide one or more parameters relating to at least one rotor blade of the at least one wind turbine in a normal status; training a trainable algorithm based on the first measurement signals of the normal status (220); detecting second measurement signals via the one or more sensors (230); and recognising an undetermined anomaly via the trainable algorithm trained in the normal status, if a current status of the wind turbine, determined based on the second measurement signals, deviates from the normal status (240).

Abstract: The invention relates to a method (100) for determining loads on a wind turbine tower. In a first step (110) of the method (100), bending moments in at least one rotor blade of the wind turbine are determined in order to provide a first variable, which identifies a first force acting on a nacelle of the wind turbine tower. In addition, in a second step (120) of the method (100), a nacelle deflection is determined in order to provide a second variable which identifies a second force acting on the nacelle of the wind turbine tower. Furthermore, a third step (130) of the method (100) comprises entering the first variable and the second variable into a calculation model, which displays the behavior of the tower. A fourth step (140) of the method (100) comprises a determination of loads on the tower of the wind turbine by means of the calculation model.

Abstract: Embodiments describe a method for predicting the accumulation of ice on a rotor blade (111, 112) of a wind turbine (100) and the use thereof.

Abstract: Embodiments of the invention describe a method for ascertaining a value of an ice buildup quantity on at least one rotor blade (111, 112) of a wind turbine (100) and to the use thereof.