Embodiments of the present disclosure provide systems, methods, and computer-readable storage media configured to monitor wind turbines and detect damage to one or more components of the wind turbines, such as damage to the blades. The techniques disclosed herein may utilize sensors (e.g., acoustic sensors) disposed within air cavities of one or more blades of the wind turbines to detect acoustic signals or acoustic energy caused by corrosive impacts (e.g., wind, dust, rain, hail, lightning, etc.) to the wind turbine. Information associated with the acoustic signals may be provided to and received by a processor used to determine whether one or more of the blades of the wind turbines have been damaged. The techniques disclosed herein may facilitate real-time or near-real-time monitoring of wind turbines for damage, which may enable more efficient operation and maintenance of wind turbines.

Disclosed is a method of detecting abnormal conditions, e.g. of a blade or a rotor, on a wind turbine generator. Also disclosed is a system for detecting abnormal conditions, e.g. of a blade or rotor on a wind turbine generator.

An apparatus for detecting anomalies in an acoustic signal, the apparatus including: one or more microphones for receiving an acoustic signal of an environment; and a processor implementing: an acoustic signal processing module configured to: analyse the acoustic signal to identify anomalies in the acoustic signal indicative of events occurring in the environment; and classify the anomalies in the acoustic signal into one or more event classifications; and a communications module configured to output the one or more event classifications, wherein the apparatus is located in the environment and includes an environmental enclosure arranged to house the processor and to protect the processor from environmental contaminants.

A method of analyzing wind turbine noise is provided. The method comprises acquiring noise data representing noise produced by a wind turbine and acquiring data from a plurality of vibration sensors positioned at different locations about the wind turbine. The method further comprises identifying a region of interest in the noise data, the region of interest being a candidate for containing tonal noise generated by the wind turbine, and identifying a vibration sensor, the data for which correlates with the noise data in the region of interest. The method further comprises determining a threshold vibration level for the identified vibration sensor, the threshold being based on the vibration level detected by the identified vibration sensor in the region of interest, and determining when the vibration level detected by the identified vibration sensor exceeds the determined threshold.

An apparatus for detecting anomalies in an acoustic signal, the apparatus including: one or more microphones for receiving an acoustic signal of an environment; and a processor implementing: an acoustic signal processing module configured to: analyse the acoustic signal to identify anomalies in the acoustic signal indicative of events occurring in the environment; and classify the anomalies in the acoustic signal into one or more event classifications; and a communications module configured to output the one or more event classifications, wherein the apparatus is located in the environment and includes an environmental enclosure arranged to house the processor and to protect the processor from environmental contaminants.

Embodiments of the present disclosure provide systems, methods, and computer-readable storage media configured to monitor wind turbines and detect damage to one or more components of the wind turbines, such as damage to the blades. The techniques disclosed herein may utilize sensors (e.g., acoustic sensors) disposed within air cavities of one or more blades of the wind turbines to detect acoustic signals or acoustic energy caused by corrosive impacts (e.g., wind, dust, rain, hail, lightning, etc.) to the wind turbine. Information associated with the acoustic signals may be provided to and received by a processor used to determine whether one or more of the blades of the wind turbines have been damaged. The techniques disclosed herein may facilitate real-time or near-real-time monitoring of wind turbines for damage, which may enable more efficient operation and maintenance of wind turbines.

A method for of controlling audible levels of tonal noise produced by a wind power plant comprising a plurality of wind turbines is provided. The method comprises identifying a wind turbine as contributing to a level of tonal noise that is audible at a noise reception point; and adjusting one or more operating parameters of a wind turbine other than the identified wind turbine in order to reduce a level of tonal noise produced by the identified wind turbine that is audible at the noise reception point, and thereby reduce the level of tonal noise that is audible at the noise reception point. A controller configured to perform the method, a wind turbine and wind power plant comprising the controller, and a computer program which when executed by a computing device cause the computing device to perform the method, are also provided.

A method of analyzing wind turbine noise is provided. The method comprises acquiring noise data representing noise produced by a wind turbine and acquiring data from a plurality of vibration sensors positioned at different locations about the wind turbine. The method further comprises identifying a region of interest in the noise data, the region of interest being a candidate for containing tonal noise generated by the wind turbine, and identifying a vibration sensor, the data for which correlates with the noise data in the region of interest. The method further comprises determining a threshold vibration level for the identified vibration sensor, the threshold being based on the vibration level detected by the identified vibration sensor in the region of interest, and determining when the vibration level detected by the identified vibration sensor exceeds the determined threshold.

A method and apparatus for inspecting a wind turbine blade. The method includes: acquiring a sound signal generated by an impingement of wind on the wind turbine blade using a sound acquisition device; generating a frequency spectrogram corresponding to the sound signal; and obtaining a damage recognition result of the wind turbine blade from the frequency spectrogram by performing image recognition on the frequency spectrogram based on a damage recognition model. With the method, a damage type of the wind turbine blade is accurately recognized based on the frequency spectrogram without manual inspection. Therefore, human resources are saved. In addition, the health state of the wind turbine blade can be monitored in real time.

An acoustic monitoring system and method for the health status of an offshore wind turbine and an ocean wave are provided. The acoustic monitoring system includes a first laser transmitter, a second laser transmitter, a telephoto camera provided at a hub, a vibration detection sensor provided on a tower of a wind turbine, and four acoustic detection sensors arranged at an interval of 90? along the circumference of the tower. The first and second laser transmitters are arranged at the bottom of a nacelle of the wind turbine and emit laser lights vertically downward. The first laser transmitter, the second laser transmitter, the telephoto camera, the vibration detection sensor, and the acoustic detection sensors are connected to a data acquisition and conversion module through a transmission module. The acoustic monitoring system combines laser light detection with acoustic signal feature detection to improve stability and safety of the offshore wind turbine.