A wind turbine is disclosed which comprises a control system configured to execute at least one ice removal routine which comprises a heating stage of at least one of the blades (3), and a mechanical removal ice stage. A wind turbine removing ice method is also disclosed which comprises a stage wherein the presence of ice is detected on at least one of the blades and, once said presence of ice is detected, comprises a stage wherein at least one ice removal routine is activated which comprises, in turn, a heating stage of at least one of the blades and a mechanical removing ice stage on at least said blade.

A method for detecting anomalies during operation of an asset to improve performance of the asset includes collecting, via a server, data relating to operation of the asset or a group of assets containing the asset. The data includes normal and abnormal asset behavior of the asset or the group of assets containing the asset. Further, the method includes automatically removing, via an iterative algorithm programmed in the server that utilizes one or more inputs or outputs of an anomaly detection analytic, portions of the data containing the abnormal asset behavior to form a dataset containing only the normal asset behavior. The method also includes training, via a computer-based model programmed in the server, the anomaly detection analytic using, at least, the dataset containing only the normal asset behavior. Moreover, the method includes applying, via the server, the anomaly detection analytic to the asset so as to monitor for anomalies during operation thereof.

A method and associated system are provided for determining a yaw heading (θ.sub.heading) of a wind turbine, the wind turbine having a tower and a nacelle that includes a machine head and rotor at a top thereof. The method includes configuring a single rover receiver of a global navigation satellite system (GNSS) at a fixed position relative to the nacelle. A GNSS geographic location of a tower top pivot point (TPP) of the wind turbine is determined, as well as an angular offset of the rover receiver (β.sub.rover) relative to a centerline axis of the nacelle. Based on the GNSS geo-location of the TPP and a GNSS geo-location of the rover receiver, an angular vector () relative to North of a line between the TPP and the rover receiver is determined. The yaw heading (θ.sub.heading) is computed from a difference between the angle () and the angular offset (β.sub.rover) of the rover receiver.

Embodiments according to the invention describe a method for monitoring the state of the powertrain or tower of a wind turbine (10), said method having the steps of: detecting data of a state monitoring system which is provided for a structure of the wind turbine (10), said structure being mechanically coupled to the powertrain or tower; processing the detected data of the state monitoring system which is provided for the structure of the wind turbine (10), said structure being mechanically coupled to the powertrain or tower; and determining the state of the powertrain or tower from the processed data of the state monitoring system which is provided for the structure of the wind turbine (10), said structure being mechanically coupled to the powertrain or tower.

A self-inspection method for a hydraulic control turning system of a generator rotor includes: establishing a length dimension relationship table among a plurality of hydraulic cylinders of the hydraulic control turning system; selecting a reference hydraulic cylinder, and acquiring a reference length dimension when the reference hydraulic cylinder is located at a target working position, the target working position is a position at which a turning pin corresponding to the reference hydraulic cylinder is inserted into an adapted hole; and performing a function inspection of a motion execution module in sequence by the plurality of the hydraulic cylinders, based on the reference length dimension and the length dimension relationship table.

Disclosed is a method of condition monitoring a WTG (Wind Turbine Generator) comprising acts of collecting and storage of at least the following data sets together with their time stamps. Collection of generator power production measurements. Collection of mechanical status measurements. Collection of generator torque measurements. Collection of nacelle direction measurements. Collection of meteorological conditions measurements. The method compromises a further act of synchronizing the data sets. The invention also relates to a system for condition monitoring a WTG. The invention further relates to a system for visually inspecting a WTG.

Disclosed is a method of condition monitoring a WTG (Wind Turbine Generator) comprising acts of collecting and storage of at least the following data sets together with their time stamps. Collection of generator power production measurements. Collection of mechanical status measurements. Collection of generator torque measurements. Collection of nacelle direction measurements. Collection of meteorological conditions measurements. The method compromises a further act of synchronizing the data sets. The invention also relates to a system for condition monitoring a WTG. The invention further relates to a system for visually inspecting a WTG.

A wind turbine comprising a tower, a pod, at least one smoke detector in the region of the tower and/or in the region of the pod, at least one fan arranged in the tower and/or in the pod, and a control unit which detects a fire situation or smoke development in the wind turbine by means of the smoke detectors and activates the fans disposed in the tower and/or in the pod in order to suck away the smoke produced.

The invention relates to a system for monitoring wind turbine components including an independent data processing environment adapted to: receive a first category of data input related to operation of the wind turbine, process the received data input by one or more component specific monitoring algorithms adapted to establish an estimated component value related to a component to be monitored based on received first category data input having at least indirectly impact on the component, wherein the component specific monitoring algorithm is adapted to establish a component residual as the difference between the estimated component value and received first category of data input of the component to be monitored, and wherein the component specific monitoring algorithm furthermore is adapted to establish a component specific health value of the component to be monitored based on the established residual and put the health value at disposal for data processors outside the environment.

A compressor maintenance monitoring and alert system for use with a compressor comprises a sensor unit including a housing, at least one vibration sensor and/or electrical impulse sensor, and a computer processor. The housing is constructed and arranged for being mounted or electrically coupled to the compressor. A processor of a mobile communication device receives compressor data transmitted by the sensor unit over a period of time, processes the received compressor data, determines if the received compressor data meets or exceeds scheduled maintenance tasks included in the look up tables, and displays required maintenance tasks on a display of the mobile communication device.