Abstract:
The present invention relates to a method and to a wind turbine for determining the tip angle of a blade of a wind turbine rotor during rotation of the rotor. The method comprising: (a) transmitting a light signal from a first blade of the wind turbine rotor towards a second blade of the rotor; (b) receiving the light signal at the second blade of the rotor; and (c) calculating the tip angle of the first or second blade based upon characteristics of the received light signal.
Abstract:
The rotor blades of a wind turbine each have a plurality of fiber-optic pressure variation sensors which can detect the onset of a stall condition. The output of the stall condition sensors is input to a stall count circuit which increases a stall count signal each time a stall indication is received. The stall count signal is decayed exponentially over time and the current signal is summed with the decayed signal from a previous sampling period to form a value from which a stall margin is determined. An λ:θ curve of tip speed to wind speed ratio λ against pitch angle reference θ is then determined from the stall margin.
Abstract:
The invention provides a method and system of monitoring bending strain on a wind turbine blade. The method in one aspect comprises:. locating at least three strain sensors on the turbine blade, in use each strain sensor providing a strain measurement, the strain sensors located such that edgewise and flapwise bending can be determined from the strain measurements; calculating a plurality of resultant bending strains using the strain measurements; calculating an average resultant bending strain from the plurality of resultant bending strains; and calculating a confidence value for a first sensor based on a comparison of resultant bending strains derived from the strain measurement from the first sensor with the average resultant bending strain.
Abstract:
To identify abnormal behavior in a turbine blade, a failure detection system generates a “fingerprint” for each blade on a turbine. The fingerprint may be a grouping a dynamic, physical characteristics of the blade such as its mass, strain ratio, damping ratio, and the like. While the turbine is operating, the failure detection system receives updated sensor information that is used to determine the current characteristics of the blade. If the current characteristics deviate from the characteristics in the blade's fingerprint, the failure detection system may compare the characteristics of the blade that deviates from the fingerprint to characteristics of another blade on the turbine. If the current characteristics of the blade are different from the characteristics of the other blade, the failure detection system may change the operational mode of the turbine such as disconnecting the turbine from the utility grid or stopping the rotor.
Abstract:
To identify abnormal behavior in a turbine blade, a failure detection system generates a “fingerprint” for each blade on a turbine. The fingerprint may be a grouping a dynamic, physical characteristics of the blade such as its mass, strain ratio, damping ratio, and the like. While the turbine is operating, the failure detection system receives updated sensor information that is used to determine the current characteristics of the blade. If the current characteristics deviate from the characteristics in the blade's fingerprint, the failure detection system may compare the characteristics of the blade that deviates from the fingerprint to characteristics of another blade on the turbine. If the current characteristics of the blade are different from the characteristics of the other blade, the failure detection system may change the operational mode of the turbine such as disconnecting the turbine from the utility grid or stopping the rotor.