Abstract: A method for preventing a pitch bearing failure of a pitch system of a wind turbine includes monitoring, via at least one sensor, one or more electrical signals of a pitch motor of a pitch drive mechanism of the pitch system that drives a pitch bearing of the pitch system. The method also includes analyzing, via the controller, the one or more electrical signals of the pitch motor so as to remove noise and amplify outliers. Moreover, the method includes estimating bearing friction of the pitch bearing using the analyzed one or more electrical signals of the pitch motor. As such, the method includes implementing, via the controller, a control action when the estimated bearing friction of the pitch bearing indicates an anomaly in the pitch bearing.

Abstract: A method for detecting a fault in a direct current (DC) battery of a pitch system includes receiving, via a server, a plurality of voltage signals of the battery over at least one time period. The method also includes storing, via a database of the server, the plurality of voltage signals of the battery for the predetermined time period. Further, the method includes determining, via the server, a state of the battery as a function of the plurality of voltage signals. When the state of the battery is indicative of a battery fault, the method includes implementing a corrective action for the battery.

Abstract: A method for detecting damage in a bearing coupled to a rotating shaft of a rotary machine includes receiving one or more measurement signals from one or more first sensors for monitoring movement of the rotating shaft in one or more directions over a time period. The method also includes removing an effect of one or more environmental and/or operating conditions of the rotary machine from the one or more measurement signals over the time period. After removing, the method includes analyzing changes in the one or more measurement signals from the one or more first sensors, wherein changes in the one or more measurement signals above a predetermined threshold or of a certain magnitude are indicative of a damaged bearing. Moreover, the method includes implementing a corrective action when the changes in the one or more measurement signals are above the predetermined threshold.

Abstract: A system and method are provided for operating and maintaining a wind turbine. Accordingly, a plurality of data inputs are received. The plurality of data inputs represent a plurality of monitored attributes of a component of the wind turbine. A consolidated risk index for the component is determined using the plurality of monitored attributes, and a range of potential risk indices is forecasted. A remaining-useful-life distribution is determined based on the damage potential and an end-of-life damage threshold. The wind turbine is shut down or idled if the remaining-useful-life distribution is below a shutdown threshold.

Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.

Abstract: 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.

Abstract: A system and method are provided for operating and maintaining a wind turbine. Accordingly, a plurality of data inputs are received. The plurality of data inputs represent a plurality of monitored attributes of a component of the wind turbine. A consolidated risk index for the component is determined using the plurality of monitored attributes, and a range of potential risk indices is forecasted. A remaining-useful-life distribution is determined based on the damage potential and an end-of-life damage threshold. The wind turbine is shut down or idled if the remaining-useful-life distribution is below a shutdown threshold.

Abstract: A method for detecting a fault in a direct current (DC) battery of a pitch system includes receiving, via a server, a plurality of voltage signals of the battery over at least one time period. The method also includes storing, via a database of the server, the plurality of voltage signals of the battery for the predetermined time period. Further, the method includes determining, via the server, a state of the battery as a function of the plurality of voltage signals. When the state of the battery is indicative of a battery fault, the method includes implementing a corrective action for the battery.

Abstract: A method for detecting damage in a bearing coupled to a rotating shaft of a rotary machine includes receiving one or more measurement signals from one or more first sensors for monitoring movement of the rotating shaft in one or more directions over a time period. The method also includes removing an effect of one or more environmental and/or operating conditions of the rotary machine from the one or more measurement signals over the time period. After removing, the method includes analyzing changes in the one or more measurement signals from the one or more first sensors, wherein changes in the one or more measurement signals above a predetermined threshold or of a certain magnitude are indicative of a damaged bearing. Moreover, the method includes implementing a corrective action when the changes in the one or more measurement signals are above the predetermined threshold.

Abstract: A method for mitigating damage in a rotor blade of a plurality of rotor blades of a wind turbine includes receiving a plurality of acceleration signals from the plurality of the rotor blades in at least one direction. The method also includes generating a spectral density for each of the plurality of acceleration signals. Further, the method includes determining blade energies for each of the plurality of rotor blades based on the spectral densities for each of the plurality of acceleration signals for at least one predetermined frequency range. Moreover, the method includes comparing the blade energies to at least one of each other or a predetermined damage threshold. In addition, the method includes implementing a control action when one or more of the blade energies vary from each other by a predetermined amount or one or more of the blade energies exceed the predetermined damage threshold.

Abstract: A method for mitigating damage in a rotor blade of a plurality of rotor blades of a wind turbine includes receiving a plurality of acceleration signals from the plurality of the rotor blades in at least one direction. The method also includes generating a spectral density for each of the plurality of acceleration signals. Further, the method includes determining blade energies for each of the plurality of rotor blades based on the spectral densities for each of the plurality of acceleration signals for at least one predetermined frequency range. Moreover, the method includes comparing the blade energies to at least one of each other or a predetermined damage threshold. In addition, the method includes implementing a control action when one or more of the blade energies vary from each other by a predetermined amount or one or more of the blade energies exceed the predetermined damage threshold.