Abstract: An automated method to determine modal characteristics of a wind turbine tower at an offshore location in a continuous manner includes reading one or more sensor data signals, prefiltering the one or more sensor data signals to divide the signals into a plurality of time segments, obtaining a frequency domain representation of each of the plurality of time segments by computing a Power Spectral Density (PSD) of each of the time segments to identify one or more frequency peaks in each of the time segments, assigning a probability to each of the frequency peaks in the PSD of each of the time segments, combining all assigned probabilities and determining the likelihood of the one or more frequency peaks. Also disclosed is an offshore wind turbine tower having a turbine control system utilizing the automated method to determine modal characteristics of the wind turbine.

Abstract: An electric power system includes a generating unit, which includes a controller for controlling an operational mode of the generating unit. The electric power system also includes an event estimator communicatively coupled to the controller of the generating unit and a network estimator communicatively coupled to the event estimator. The network estimator includes a processor configured to receive status information associated with the electric power system, determine, based upon the status information, at least one characteristic of the electric power system, and transmit the at least one characteristic to the event estimator.

Abstract: An automated method to determine modal characteristics of a wind turbine tower at an offshore location in a continuous manner includes reading one or more sensor data signals, prefiltering the one or more sensor data signals to divide the signals into a plurality of time segments, obtaining a frequency domain representation of each of the plurality of time segments by computing a Power Spectral Density (PSD) of each of the time segments to identify one or more frequency peaks in each of the time segments, assigning a probability to each of the frequency peaks in the PSD of each of the time segments, combining all assigned probabilities and determining the likelihood of the one or more frequency peaks. Also disclosed is an offshore wind turbine tower having a turbine control system utilizing the automated method to determine modal characteristics of the wind turbine.

Abstract: An electric power system includes a generating unit, which includes a controller for controlling an operational mode of the generating unit. The electric power system also includes an event estimator communicatively coupled to the controller of the generating unit and a network estimator communicatively coupled to the event estimator. The network estimator includes a processor configured to receive status information associated with the electric power system, determine, based upon the status information, at least one characteristic of the electric power system, and transmit the at least one characteristic to the event estimator.

Abstract: A machine monitoring device is provided which includes a communications link to interrogate a machine with a probe signal and receive one or more measured machine operating condition outputs; and a device controller capable of selecting a machine operating condition input variable for which a corresponding machine operating condition output is unknown; applying a predictive model in which the machine operating condition input variable serves as an argument of a predicted machine operating condition output; updating a library of predicted machine operating condition outputs; and alerting a human operator if a measured or predicted machine operating condition output exceeds a predetermined limit. The predictive model is based on at least two independent primary models having at least one correspondence between a primary model machine operating condition and a corresponding machine output. The primary models share a common basis in the predictive model.

Abstract: A machine monitoring device is provided which includes (a) a communications link to interrogate a machine with a probe signal and receive one or more measured machine operating condition outputs; and (b) a device controller capable of (i) selecting a machine operating condition input variable for which a corresponding machine operating condition output is unknown; (ii) applying a predictive model in which the machine operating condition input variable serves as an argument of a predicted machine operating condition output; (iii) updating a library of predicted machine operating condition outputs; and (iv) alerting a human operator if a measured or predicted machine operating condition output exceeds a predetermined limit. The predictive model is based on at least two independent primary models having at least one correspondence between a primary model machine operating condition and a corresponding machine output. The primary models share a common basis in the predictive model.

Abstract: A method of detecting a vibration node between a non-collocated sensor-actuator pair of a rotatable component includes applying an excitation signal to an actuator of the sensor actuator pair. The method also includes obtaining frequency response data from the sensor-actuator pair. The method further includes analyzing the frequency response data to ascertain a resonant frequency of the rotatable component. The method includes identifying a resonance/anti-resonance peak pair in the frequency response data for the non-collocated sensor-actuator pair. Furthermore, the method includes determining whether the vibration node is located between a sensor and the actuator of the non-collocated sensor-actuator pair based on the resonance/anti-resonance peak pair.

Abstract: A method of detecting a vibration node between a non-collocated sensor-actuator pair of a rotatable component includes applying an excitation signal to an actuator of the sensor actuator pair. The method also includes obtaining frequency response data from the sensor-actuator pair. The method further includes analyzing the frequency response data to ascertain a resonant frequency of the rotatable component. The method includes identifying a resonance/anti-resonance peak pair in the frequency response data for the non-collocated sensor-actuator pair. Furthermore, the method includes determining whether the vibration node is located between a sensor and the actuator of the non-collocated sensor-actuator pair based on the resonance/anti-resonance peak pair.