Systems and methods for building predictive and prescriptive analytics of wind turbines generate a historical operational dataset by loading historical operational SCADA data of one or more wind turbines. Each sensor measurement is associated with an engineering tag and at least one component of a wind turbine. The system creates one or more performance indicators corresponding to one or more sensor measurements, and applies at least one data clustering algorithm onto the dataset to identify and label normal operation data clusters. The system builds a normal operation model using normal operational data clusters with Efficiency of Wind-To-Power (EWTP) and defines a statistical confidence range around the normal operation model as criterion for monitoring wind turbine performance. As real-time SCADA data is received by the system, the system can detect an anomalous event, and issue an alert notification and prescriptive early-action recommendations to a user, such as a turbine operator, technician or manager.

The present invention relates to non-thermal renewable energy turbines (20,24,34, 38,40), in particular to the monitoring of turbine performance to identify a loss of performance indicative of faults or component degradation. The method involves comparison of measured power from a target turbine (20) with a predicted value for same turbine. The predicted value is calculated using the output from a plurality of other turbines (24,34,38,40) from an array and a predictive model including weightings for the other turbines (24, 34,38,40) based on the strength of correlation of their historical with historical data from the target turbine (20).

A wind turbine generator fault detection method is described. The method includes obtaining a first signal from a generator of a wind turbine and a second signal from a vibration sensor coupled to the wind turbine, the first signal representing an output current of the generator, and the second signal being a time-sampled signal representing vibrations of a bearing in the wind turbine. Determining a shaft rotation frequency signal from the first signal, the shaft rotation frequency signal representing a time-varying rotational speed of a shaft of the wind turbine. Resampling an envelope of the second signal based on the shaft rotation frequency signal to provide a third signal, the third signal being an angular sampled signal. Detecting, by the at least one processor, a fault in the bearing of the wind turbine by identifying a characteristic signature of a bearing fault in the third signal.

A method for monitoring at least one journal bearing for a shaft in respect to at least one acoustic event is provided. The at least one journal bearing is coupled with a gearbox, wherein a time dependent solid borne sound signal is detected by at least one solid borne sound signal sensor, the output signal of the at least one solid borne sound signal sensor is transmitted to a signal pre-processing device, frequency components of the solid borne sound signal with of more than 250 kHz are amplified in the signal pre-processing device and/or with a frequency of less than 50 kHz are attenuated in the signal pre-processing device, and the output signal of the signal pre-processing device is wirelessly transmitted via an antenna device to a signal evaluation device for the detection and/or location of the at least one acoustic event.

A computing system is configured to detect irregular yawing at wind turbines. To this end, the computing system (i) for each respective turbine of an identified cluster of wind turbines: (a) obtains yaw-activity data indicative of the respective turbine's yaw activity during a window of time, and (b) based on obtained yaw-activity data, derives a yaw-activity-measure dataset having measures of the respective turbine's yaw activity during time intervals within the window of time, (ii) based on the respective yaw-activity-measure datasets for the turbines in the cluster, derives a cluster-level yaw-activity-measure dataset, (iii) evaluates the respective yaw-activity-measure dataset for one or more turbines in the cluster as compared to the cluster-level yaw-activity-measure dataset, (iv) based on the evaluation, identifies at least one turbine of the cluster that exhibited irregular yaw activity, and (v) transmits, to an output device, a notification of the irregular yaw activity at the at least one turbine.

A system of fans ventilates heated air from within an IHS (Information Handling System), such as a rack-mounted server, when operated during normal conditions at a rated fan speed. A controller detects a failure of a fan of this fan system and identifies the functioning fans of the system. One or more of the functioning fans are selected for boosting by operation of a fan failure compensation circuit that has been configured for delivery of additional power to the selected boost fans. The fan failure compensation circuit delivers an output voltage that boost the airflow output of the system to compensate for the failed fan. By increasing the output voltage by approximately twenty percent, the boosted fans operate at approximately fifteen percent above rated speeds, which has been demonstrated to compensate for a failed fan while avoiding further failures during the expected lifespan of the fan system.

In a method, impulse response information indicative of an impulse response is determined based on an impulse introduced into a lightning conductor and characterized by an electromagnetic wave. The impulse response information representing at least a waveform and a travel time determined after the introduction of the impulse based on reflection thereof. Evaluation information is specified based on the determined impulse response information. The impulse response information is analyzed at least with respect to the represented waveform and travel time of the introduced and reflected electromagnetic wave. The evaluation information is indicative of whether or not the lightning conductor is functional. The determined evaluation information is output. Also disclosed are a device for practicing this method, a rotor blade for a wind turbine that includes at least one lightning conductor and a device for practicing the method, and a system with one or more devices for practicing the method.

A method for detecting an electrical fault in the stator of an electric machine is provided, wherein the stator includes multiple groups of windings, wherein the windings of each group are assigned to a respective phase of the electric machine, including the steps of: determining a respective current firstly between a subgroup of one of the groups of windings and a distinct further subgroup of the same group of windings and/or secondly between a subgroup of one of the groups of windings and a neutral point, and/or thirdly between a neutral point and either a further neutral point or to a common neutral point connected to at least the neutral point and the further neutral point, evaluating a fault condition, wherein the fulfilment of the fault condition depends on the respective determined current, and outputting a fault signal to personal and/or a device when the fault condition is fulfilled.

A method of determining an orientation of a nacelle of a wind turbine, wherein the nacelle carries a Global Navigation Satellite System (GNSS) sensor, the method comprising: yawing the nacelle between a series of orientations; obtaining locus data based on a series of calibration positions measured by the GNSS sensor, wherein each calibration position is measured by the GNSS sensor when the nacelle is in a respective orientation of the series of orientations; storing the locus data; after storing the locus data, measuring a new position with the GNSS sensor; and determining the orientation of the nacelle on the basis of the stored locus data and the new position.

The present disclosure relates to methods and systems for measuring deflection of blades of a wind turbine. Examples include a light emitting and collection device mounted to the nacelle and configured to emit light in a direction within a substantially vertical plane. Examples include a method for operating a wind turbine including emitting light above a hub, receiving the light when reflected by a blade of the wind turbine, and, if the level of blade deflection is above a threshold, reducing blade loading of the blade before the blade reaches a vertically downward position. Examples include a method for monitoring deflection of a rotor blade of a wind turbine comprising emitting a light sheet, collecting reflections of the emitted light, and determining deflection of the rotor blade by determining a time during which the blade reflects the emitted light sheet.