Patent Description:
Modern wind turbines are commonly used to supply electricity into the electrical grid. Wind turbines of this kind generally comprise a tower and a rotor arranged on the tower. The rotor, which typically comprises a hub and a plurality of blades, is set into rotation under the influence of the wind on the blades. Said rotation generates a torque that is normally transmitted through a rotor shaft to a generator, either directly ("directly driven" or "gearless") or through the use of a gearbox. This way, the generator produces electricity which can be supplied to the electrical grid.

Modern wind turbines have increasingly larger rotor diameters to capture more energy throughout their lifetime and reduce the cost of energy. As the rotor size increases, the stiffness of the blades is not proportionally increased, leading to more flexible blades that are more sensitive to dynamic perturbations. Said dynamic perturbations may lead to edgewise and spanwise oscillations.

Wind turbines that are installed in cold climates require additional consideration in terms of design and safety. Icing has been recognized as an obstacle in the optimal harvesting of wind resources in cold regions. At lower temperatures, ice accretion may occur on wind turbine components. In fact, ice accretion on wind turbine blades affects the aerodynamic efficiency of the blades and thus the power output and leads to higher loads and may be a hazard for the whole wind turbine. Ice formation affects the structural behavior and fatigue life of the blade(s) as well. Further, blade imbalance may occur as a result of ice growing on the blade: even if the root end of wind turbine blade may be free from ice, ice may accumulate at the tip end of the wind turbine blade. This occurs due to the higher relative velocity between the wind turbine blade tip and atmospheric water droplets, and also due to the larger atmospheric swept area of wind turbine blade tip portions, among others. Thus, uneven ice accretion on wind turbine blades may also cause blade imbalance during rotation, posing severe risks for the operation of the wind turbine.

The accumulation of ice in wind turbine blades may also result in chunks of ice detaching from the wind turbine blades during operation (or during parked conditions). Falling chunks of ice may impact against other parts of the wind turbine structure and can pose a risk for operators working in the vicinity of the wind turbine.

It is known to utilize ice detection systems, e.g. based on cameras to try to detect the presence of ice on the blades. It is also known to interrupt operation and carry out certain tests (like imbalance tests) to try to detect ice on one or more of the blades. <CIT> describes an example of ice detection system in a wind turbine.

The present disclosure provides methods and systems to detect a variation in the dynamic response of a wind turbine blade, in particular due to ice accumulation, to at least partially overcome some of the aforementioned drawbacks.

In an aspect of the present disclosure, a method for detecting a state of a wind turbine blade is provided. The method comprises receiving one or more load signals from one or more sensors configured to measure loads on the wind turbine blade. Further, the method comprises determining an energy of the load signals at a first frequency, and determining an energy of the load signals at a second frequency, wherein the first frequency is a frequency substantially corresponding to a natural frequency of the blade in a default state. The method also comprises comparing the energy of the load signals at the first frequency to the energy of the load signals at the second frequency. Additionally, the method comprises generating a flag signal if the energy of the load signals at the first frequency is smaller than the energy of the load signals at the second frequency.

According to this aspect, the state of a wind turbine blade can be detected based on a shift or modulation of the energy of a load signal, i.e. from one frequency (band) to another frequency (band). This results in a method that allows determining the state of a wind turbine blade during wind turbine operation and without installing additional devices, i.e. cameras or others. Thus, this method allows monitoring the state of a wind turbine blade without affecting the overall power output of the wind turbine.

Throughout this disclosure, the term "load signal" should be understood as a signal that is at least partially representative of an acting load. Thus, a load signal may be, for example, a signal indicating a movement or deformation, a signal comprising acceleration values, a signal comprising force or stress readings or any other magnitude that may be used to estimate a load acting on said component or on another component mechanically connected to the former.

The "default state" may herein be regarded as a reference state of a wind turbine blade, i.e. situation or state to which a comparison is to be made. The default state may be an "ideal" state of the wind turbine blade, i.e. a clean, as delivered, blade without any deterioration of the blade or any accumulation or accretion of ice or other matter. The default state may however be chosen differently.

When reference is made throughout the present disclosure to determining an "energy" or "energy content" of a signal, this is herein to be regarded as the determination (calculation or estimation) of any indicator known in the art to indicate energy, in particular including using the square of the signal magnitude, Root Mean Square (RMS) of a signal, the envelope of squared signal magnitude or the integral of squared signal magnitude. The energy or energy content of a signal can be calculated or estimated for a finite period of time. It is noted that signal energy is not necessarily actually a measure of "energy" as understood in physics.

Additional objects, advantages and features of embodiments of the present disclosure will become apparent to those skilled in the art upon examination of the description, or may be learned by practice.

Reference now will be made in detail to embodiments of the disclosure, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation, not as a limitation. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present disclosure without departing from the scope or spirit of the teaching. Thus, it is intended that the present disclosure covers such modifications and variations as come within the scope of the appended claims and their equivalents.

In examples, the rotor blades <NUM> may have a length ranging from about <NUM> meters (m) to about <NUM> or more. Rotor blades <NUM> may have any suitable length that enables the wind turbine <NUM> to function as described herein. For example, non-limiting examples of blade lengths include <NUM> or less, <NUM>, <NUM>, <NUM>, <NUM> or a length that is greater than <NUM>. As wind strikes the rotor blades <NUM> from a wind direction <NUM>, the rotor <NUM> is rotated about a rotor axis <NUM>. As the rotor blades <NUM> are rotated and subjected to centrifugal forces, the rotor blades <NUM> are also subjected to various forces and moments. As such, the rotor blades <NUM> may deflect and/or rotate from a neutral, or non-deflected, position to a deflected position.

In the example, the wind turbine controller <NUM> is shown as being centralized within the nacelle <NUM>, however, the wind turbine controller <NUM> may be a distributed system throughout the wind turbine <NUM>, on the support system <NUM>, within a wind farm, and/or at a remote-control center. The wind turbine controller <NUM> includes a processor <NUM> configured to perform the methods and/or steps described herein. Further, many of the other components described herein include a processor.

As used herein, the term "processor" is not limited to integrated circuits referred to in the art as a computer, but broadly refers to a controller, a microcontroller, a microcomputer, a programmable logic controller (PLC), an application specific, integrated circuit, and other programmable circuits, and these terms are used interchangeably herein. It should be understood that a processor and/or a control system can also include memory, input channels, and/or output channels.

<FIG> is an enlarged sectional view of a portion of the wind turbine <NUM>. In the example, the wind turbine <NUM> includes the nacelle <NUM> and the rotor <NUM> that is rotatably coupled to the nacelle <NUM>. More specifically, the hub <NUM> of the rotor <NUM> is rotatably coupled to an electric generator <NUM> positioned within the nacelle <NUM> by the main shaft <NUM>, a gearbox <NUM>, a high-speed shaft <NUM>, and a coupling <NUM>. In the example, the main shaft <NUM> is disposed at least partially coaxial to a longitudinal axis (not shown) of the nacelle <NUM>. A rotation of the main shaft <NUM> drives the gearbox <NUM> that subsequently drives the high-speed shaft <NUM> by translating the relatively slow rotational movement of the rotor <NUM> and of the main shaft <NUM> into a relatively fast rotational movement of the high-speed shaft <NUM>. The latter is connected to the generator <NUM> for generating electrical energy with the help of a coupling <NUM>. Furthermore, a transformer <NUM> and/or suitable electronics, switches, and/or inverters may be arranged in the nacelle <NUM> in order to transform electrical energy generated by the generator <NUM> having a voltage between 400V to <NUM> V into electrical energy having medium voltage (<NUM> - <NUM> KV). Said electrical energy is conducted via power cables from the nacelle <NUM> into the tower <NUM>.

The gearbox <NUM>, generator <NUM> and transformer <NUM> may be supported by a main support structure frame of the nacelle <NUM>, optionally embodied as a main frame <NUM>. The gearbox <NUM> may include a gearbox housing that is connected to the main frame <NUM> by one or more torque arms <NUM>. In the example, the nacelle <NUM> also includes a main forward support bearing <NUM> and a main aft support bearing <NUM>. Furthermore, the generator <NUM> can be mounted to the main frame <NUM> by decoupling support means <NUM>, in particular in order to prevent vibrations of the generator <NUM> to be introduced into the main frame <NUM> and thereby causing a noise emission source.

In some examples, the wind turbine may be a direct drive wind turbine without gearbox <NUM>. Generator <NUM> operate at the same rotational speed as the rotor <NUM> in direct drive wind turbines. They therefore generally have a much larger diameter than generators used in wind turbines having a gearbox <NUM> for providing a similar amount of power than a wind turbine with a gearbox.

The nacelle <NUM> may also include a yaw drive mechanism <NUM> that may be used to rotate the nacelle <NUM> and thereby also the rotor <NUM> about the yaw axis <NUM> to control the perspective of the rotor blades <NUM> with respect to the wind direction <NUM>.

For positioning the nacelle <NUM> appropriately with respect to the wind direction <NUM>, the nacelle <NUM> may also include at least one meteorological measurement system <NUM> which may include a wind vane and anemometer. The meteorological measurement system <NUM> can provide information to the wind turbine controller <NUM> that may include wind direction <NUM> and/or wind speed. In the example, the pitch system <NUM> is at least partially arranged as a pitch assembly <NUM> in the hub <NUM>. The pitch assembly <NUM> includes one or more pitch drive systems <NUM> and at least one sensor <NUM>. Each pitch drive system <NUM> is coupled to a respective rotor blade <NUM> (shown in <FIG>) for modulating the pitch angle of a rotor blade <NUM> along the pitch axis <NUM>. Only one of three pitch drive systems <NUM> is shown in <FIG>.

In the example, the pitch assembly <NUM> includes at least one pitch bearing <NUM> coupled to hub <NUM> and to a respective rotor blade <NUM> (shown in <FIG>) for rotating the respective rotor blade <NUM> about the pitch axis <NUM>. The pitch drive system <NUM> includes a pitch drive motor <NUM>, a pitch drive gearbox <NUM>, and a pitch drive pinion <NUM>. The pitch drive motor <NUM> is coupled to the pitch drive gearbox <NUM> such that the pitch drive motor <NUM> imparts mechanical force to the pitch drive gearbox <NUM>. The pitch drive gearbox <NUM> is coupled to the pitch drive pinion <NUM> such that the pitch drive pinion <NUM> is rotated by the pitch drive gearbox <NUM>. The pitch bearing <NUM> is coupled to pitch drive pinion <NUM> such that the rotation of the pitch drive pinion <NUM> causes a rotation of the pitch bearing <NUM>.

Pitch drive system <NUM> is coupled to the wind turbine controller <NUM> for adjusting the pitch angle of a rotor blade <NUM> upon receipt of one or more signals from the wind turbine controller <NUM>. In the example, the pitch drive motor <NUM> is any suitable motor driven by electrical power and/or a hydraulic system that enables pitch assembly <NUM> to function as described herein. Alternatively, the pitch assembly <NUM> may include any suitable structure, configuration, arrangement, and/or components such as, but not limited to, hydraulic cylinders, springs, and/or servomechanisms. In certain embodiments, the pitch drive motor <NUM> is driven by energy extracted from a rotational inertia of hub <NUM> and/or a stored energy source (not shown) that supplies energy to components of the wind turbine <NUM>.

The pitch assembly <NUM> may also include one or more pitch control systems <NUM> for controlling the pitch drive system <NUM> according to control signals from the wind turbine controller <NUM>, in case of specific prioritized situations and/or during rotor <NUM> overspeed. In the example, the pitch assembly <NUM> includes at least one pitch control system <NUM> communicatively coupled to a respective pitch drive system <NUM> for controlling pitch drive system <NUM> independently from the wind turbine controller <NUM>. In the example, the pitch control system <NUM> is coupled to the pitch drive system <NUM> and to a sensor <NUM>. During normal operation of the wind turbine <NUM>, the wind turbine controller <NUM> may control the pitch drive system <NUM> to adjust a pitch angle of rotor blades <NUM>.

According to an embodiment, a power generator <NUM>, for example comprising a battery and electric capacitors, is arranged at or within the hub <NUM> and is coupled to the sensor <NUM>, the pitch control system <NUM>, and to the pitch drive system <NUM> to provide a source of power to these components. In the example, the power generator <NUM> provides a continuing source of power to the pitch assembly <NUM> during operation of the wind turbine <NUM>. In an alternative embodiment, power generator <NUM> provides power to the pitch assembly <NUM> only during an electrical power loss event of the wind turbine <NUM>. The electrical power loss event may include power grid loss or dip, malfunctioning of an electrical system of the wind turbine <NUM>, and/or failure of the wind turbine controller <NUM>. During the electrical power loss event, the power generator <NUM> operates to provide electrical power to the pitch assembly <NUM> such that pitch assembly <NUM> can operate during the electrical power loss event.

In the example, the pitch drive system <NUM>, the sensor <NUM>, the pitch control system <NUM>, cables, and the power generator <NUM> are each positioned in a cavity <NUM> defined by an inner surface <NUM> of hub <NUM>. In an alternative embodiment, said components are positioned with respect to an outer roof surface of hub <NUM> and may be coupled, directly or indirectly, to the outer roof surface.

<FIG> shows a flowchart of an example of a method <NUM> for detecting a state of a wind turbine blade according to a first aspect of the present disclosure. The method <NUM> in <FIG> comprises, at block <NUM>, receiving one or more load signals from one or more sensors configured to measure loads on the wind turbine blade. The method <NUM> also comprises, at block <NUM>, determining an energy of the load signals at a first frequency, and determining an energy of the load signals at a second frequency, wherein the first frequency is a frequency substantially corresponding to a natural frequency of the blade in a default state. The method <NUM>, at block <NUM>, comprises comparing the energy of the load signals at the first frequency to the energy of the load signals at the second frequency. Further, the method <NUM>, at block <NUM>, comprises generating a flag signal if the energy of the load signals at the first frequency is smaller than the energy of the load signals at the second frequency.

As previously discussed, method <NUM> can detect the state of a wind turbine blade based on a shift or modulation of the energy of a load signal, i.e. from one frequency (band) to another frequency (band). Thus, method <NUM> can estimate in a precise and robust manner the state of a wind turbine blade from the load signals received. Further, method <NUM> allows determining the state of a wind turbine blade during wind turbine operation and without affecting the overall power output of the wind turbine. Additionally, method <NUM> can be performed by devices generally already included in a wind turbine, and therefore, does not require the installation of additional devices in the wind turbine. Further details regarding method <NUM> and further examples will be discussed in relation to <FIG> and <FIG>.

The first and second frequencies may be chosen in accordance with the phenomenon to be detected. The default state of the blade may correspond to an ideal state of the blade, in which the blade is clean and has no external mass accumulation. And the first frequency may be selected to correspond to a natural frequency of the blade in this default state, i.e. with any mass accumulation (through ice, dirt or otherwise). The second frequency, in examples, may be chosen to substantially correspond to a natural frequency of the wind turbine blade with ice accumulation. The second frequency may be chosen to correspond to a natural frequency of the wind turbine blade with an accumulation of ice above a specified threshold.

<FIG> shows a flowchart of another example of method <NUM> for detecting a state of a wind turbine blade <NUM>.

In the illustrated example in <FIG>, the method <NUM> may comprise receiving load signals <NUM> representative of edgewise loads acting on the wind turbine blade at block <NUM>. The load signals may e.g. be received from strain gauges. It has been found that using edgewise loads can increase reliability of the determination of the state of the blades, since they are subjected to less aerodynamic damping. Other types of load signals may also be received and treated according to method <NUM>, such as for example load signals representative of flapwise loads.

Further, the method <NUM> may comprise, before block <NUM>, filtering <NUM> the signals <NUM> representative of loads acting on the wind turbine blade <NUM> with rotor rotational speed. The rotor frequency (associated with rotor rotational speed) should be understood as the frequency at which the rotor hub <NUM> rotates. This frequency is also referred in the art as 1P frequency.

In examples, a notch filter may be used to filter the signals representative of loads with rotor frequency (1P). This filtering may be carried out prior to determining the energy at the different frequencies. In other examples, the filtering <NUM> step may comprise using other filtering methods such as a high-pass filter with a cut-off frequency that substantially corresponds to the rotor frequency (1P) or the blade-passing frequency, referred in the art as 3P frequency.

This filtering <NUM> step substantially removing at least loads with 1P frequency allows mitigating the contribution of the blades <NUM> passing the wind turbine tower <NUM> in the energy of the load signal <NUM>. Thus, the subsequent steps of method <NUM> may provide a more precise estimation of the change in the energy of the signal <NUM> at different frequency bands.

Additionally, method <NUM> may comprise a further filtering step (not illustrated in <FIG>), wherein high frequency content from load signals <NUM> is filtered. This filtering step may comprise using a smoothing filter that may be applied to a signal <NUM> in the time domain or in the frequency domain. The smoothing filtering may be a moving average filter, a weighted moving average filter such as a binomial, exponential or polynomial weighted moving average filter, a median filter, or others. Further, the filtering step may comprise resampling the load signals <NUM> before applying a smoothing filter. The filtering step may also comprise a step of outlier removal. Additionally, filtering approaches combining outlier removal and smoothing may be also applied, as for example a Hampel filter.

As can be seen in the example method <NUM> of <FIG>, block <NUM> may comprise a first sub step <NUM> of determining an energy of the load signals <NUM> at a first frequency <NUM>, and a second sub step <NUM> of determining an energy of the load signals <NUM> at a second frequency <NUM>. The sub steps <NUM>, <NUM> may be performed sequentially (in any order) or in parallel, depending for example on computing power available.

A band pass filter may be applied to determine the load signals at the first and second frequencies. A band-pass filter or bandpass filter (BPF) may herein be regarded as a filter that passes frequencies within a certain range and rejects (attenuates) frequencies outside that range. Therefore the load signals at the first frequency and at the second frequency may not necessarily correspond exactly to the load signals at that frequency only, but instead may include a small (narrow) frequency band around the first frequency and a small frequency band around the second frequency. These small frequency bands may also be referred to as "passband".

In examples, the energy may be determined by computing the root-mean-square (RMS) of the load signals. At sub-steps <NUM>, <NUM>, the load signals at the first and second frequencies (and passbands) may be determined. Then the RMS of these signals over a period of time may be calculated. The period of time may be selected appropriately in order to be able to determine the appearance of the phenomenon that is to be detected. In examples, the period of time may be chosen to be between <NUM> minute (including at least a few revolutions of the wind turbine rotor) and <NUM> minutes, specifically between <NUM> minutes and <NUM> minutes. Other approaches than RMS to determine or estimate the energy of the load signals as mentioned before may be used. Also other time periods may be used.

In examples, the order of certain steps of method <NUM> may be altered. For example, it may be possible to receive load signals while the method <NUM> is determining an energy of a previously received load signal, i.e. some steps of method <NUM> may overlap between different loops of method <NUM>. And it is not necessary for one step to finish before another step starts.

In some examples, the natural frequency of the blade <NUM> at the first frequency <NUM> of sub step <NUM> may be the natural frequency of a first normal mode or of a second normal mode of the blade <NUM> in a default state.

A normal mode of an oscillating system is a pattern of motion in which all parts of the system move sinusoidally with the same frequency and with a fixed phase relation. The free motion described by the normal modes takes place at fixed frequencies. These fixed frequencies of the normal modes of a system are known as its natural frequencies or resonant frequencies. The first natural frequency and first normal mode refer to the lowest resonant frequency for the wind turbine and the oscillation mode corresponding to this frequency. The second normal mode and corresponding second natural frequency refer to the second lowest resonant frequency and corresponding oscillation mode.

In examples, the second frequency <NUM> of sub step <NUM> may comprise a frequency mode of the wind turbine blade <NUM> with an accumulation of ice above an allowable threshold. Additionally, the second frequency <NUM> may be obtained through wind turbine blade simulations or through field data.

In some examples, the allowable threshold may represent an accumulation of ice between <NUM>% and <NUM>% of the mass of the blade. In other examples, the allowable threshold may represent a lower or higher accumulation of ice relative to the mass of the wind turbine blade <NUM>. The value of the allowable threshold may at least partially depend on mechanical properties of the blade and on the dynamical response of the blade. The level of the threshold may further depend on the type of flag signal generated.

As illustrated in <FIG>, the example method <NUM> may comprise at block <NUM> the comparison of the energy of the signals at the first and second frequencies. Depending on the result, a flag signal may or may not be generated at block <NUM>.

In examples, the flag signal generated at block <NUM> may comprise a command enable a de-icing system of the wind turbine. Further, the flag signal may comprise a command to stop a wind turbine operation. In other examples, the flag signal may comprise other commands to alert of an incipient accumulation of ice in a wind turbine blade <NUM> or another structural change in the wind turbine blade, e.g. a structural degradation. This may allow carrying out a maintenance task of the wind turbine blade <NUM> before accumulation of ice poses a risk for the normal operation of the wind turbine <NUM>. In examples, multiple thresholds (and more than two frequencies) with corresponding different flag signals may be used.

In some examples, the flag signal may be a signal to derate the wind turbine i.e. power output and/or rotational speed of the wind turbine are reduced in order to reduce loads on the blades. It may happen that such a flag signal is generated in the morning but that temperature rises during the day and this causes the ice to fall off or melt from the blades. With examples of methods and systems of the present disclosure, the determination may be made that the blade appears to have returned to its default state or clean state without ice accumulation (or at least to a significant extent), so that normal operation of the wind turbine can be resumed.

Similarly, if a de-icing operation is carried out, methods and systems of the present disclosure can help to confirm that ice has indeed been removed from the blades. When operation is resumed, it may be determined that the blade has returned (or at least to a significant extent) to the default or clean state. If this is not the case, a new flag signal may be generated and a further de-icing operation might be carried out.

In some examples, therefore the method may comprise deactivating the flag signal or resuming operation as before the flag signal once it has been determined that the load signal at the first frequency has more energy than the load signal at the second frequency.

<FIG> shows a graph with example load signals <NUM>, <NUM> and frequency bands <NUM>, <NUM>. The graph illustrates a power spectral density of the two example load signals <NUM>, <NUM> of arbitrary units (displacement data, force data, acceleration data, or any other suitable data) in the frequency domain. In the graph, a first load signal <NUM> (illustrated with solid line) is schematically representative of a load signal from a wind turbine blade <NUM> in operation in a default state. Further, a second load signal <NUM> (illustrated with broken line) is schematically representative of a load signal from a wind turbine blade in operation wherein ice accretion has occurred. The Power Spectral Density (PSD) diagram of <FIG> thus serves to illustrate the phenomenon that allows detection of a deviation of the blade from a default state in examples of the present disclosure. Within the scope of the present disclosure, it is not necessary to calculate or otherwise estimate the PSD of the load signals. Calculating PSD in a substantially continuous manner during operation requires significant processing power.

As discussed in relation to method <NUM>, a load signal <NUM> (not illustrated) may be treated to estimate an energy at a first frequency <NUM> corresponding substantially to a natural frequency of the blade in a default state. Further, the energy of the load signal <NUM> at a second frequency <NUM> may also be determined. Thus, method <NUM> can compare the energy of the load signal <NUM> at the first frequency <NUM> with the energy of the load signal <NUM> at the second frequency. In case the energy of the load signal <NUM> is greater at the first frequency band <NUM> (this means that the structural behavior of the blade corresponds substantially to its default state) than at the second frequency <NUM>, method <NUM> would not generate a flag final.

As previously discussed, the second frequency (or second frequency band) <NUM> may be a frequency corresponding to a normal mode of the wind turbine blade when an accumulation of ice above an allowable threshold occurs, as can be observed from the peak in the power spectral density of load signal <NUM> at a smaller frequency value compared with load signal <NUM>.

In examples of method <NUM>, the first and second frequencies <NUM>, <NUM> may be selected such that a sufficient separation between the frequencies (or frequency bands) exists which allows reliable determination of a distinction between one frequency and another. At the same time, the frequencies may be selected in accordance with the flag or warning signal generated (stopping operation of the wind turbine is preferably avoided unless necessary, whereas a warning signal may be generated when the change in the blades is not very pronounced yet).

In another aspect of the disclosure, another method <NUM> to detect the state of a wind turbine blade <NUM> is provided. Method <NUM> is schematically illustrated in <FIG>.

The method <NUM> comprises, at block <NUM>, receiving one or more edgewise load signals from one or more sensors <NUM> configured to measure edgewise loads on the wind turbine blade <NUM>. Further, at block <NUM>, the method <NUM> comprises filtering out the edgewise load signals with frequency substantially corresponding to a rotor rotational speed frequency (1P).

The method <NUM> further comprises, at block <NUM>, determining an energy of the edgewise load signals at a first frequency, wherein the first frequency is a frequency substantially corresponding to a natural frequency of the blade in a default state.

Also at block <NUM>, the method comprises determining an energy of the edgewise load signals at a second frequency. Additionally, the method <NUM> comprises, at block <NUM>, comparing the energy of the edgewise load signals at the first frequency to the energy of the load signals at the second frequency. Then, at block <NUM>, the method <NUM> comprises generating a flag signal if the energy of the edgewise load signals in the first frequency band is smaller than the energy of the edgewise load signals in the second frequency band.

Thus, the method <NUM> allows determining the state of a wind turbine blade based on load signals representative of edgewise oscillations in the blade. Since edgewise oscillations are not subjected to severe aerodynamic damping, the method <NUM> may accurately detect changes in the state condition of the wind turbine blade in a precise and reliable manner.

In yet another aspect of the present disclosure, a control system <NUM> for a wind turbine <NUM> is provided. The control system <NUM> comprises a processor and a non-volatile memory. The memory comprises instructions which, when executed by the processor, cause the control system <NUM> to perform a set of operations. One operation comprises receiving <NUM> one or more load signals <NUM> from one or more sensors <NUM> configured to measure loads on the wind turbine blade. Another operation comprises determining <NUM> an energy of the load signals <NUM> in a first frequency band and a second frequency band, wherein the first frequency band is a frequency band comprising a natural frequency of the blade in a default state. Yet another operation comprises comparing <NUM> the energy of the load signals <NUM> in the first frequency band to the energy of the load signals <NUM> in the second frequency band. Further, another operation performed by the processor comprises generating <NUM> a flag signal if the energy of the load signals <NUM> in the first frequency band is smaller than the energy of the load signals <NUM> in the second frequency band.

In some examples, the memory of the control system <NUM> may further comprise load data of the wind turbine blade. This load data may comprise data from wind turbine blade(s) during normal operation in a default state, data from the wind turbine blade during operation under the influence of different amount of ice accumulation, or others. Further, the load data may be predefined data corresponding to loads occurring when an accumulation of ice above an allowable threshold occurs. For example, the load data may be recorded load date, i.e. experimentally recorded under controlled conditions, or load data from wind turbine blade simulations. The load data may be used by the processor to define the first and second frequency bands among others. The load data may include data on the natural frequencies of the blade(s) in different circumstances, e.g. different amounts of ice accretion.

In a further aspect of the disclosure, a wind turbine <NUM> comprising a plurality of blades and a control system <NUM> as previously disclosed is provided. Further, the wind turbine <NUM> may comprise sensors <NUM> configured to measure loads on the wind turbine blades. More specifically, the sensors <NUM> may be strain gauges mounted on the blades. Additionally, in some examples, the sensors <NUM> are configured to provide edgewise loads acting on the blade(s).

In examples, the wind turbine <NUM> may further comprise a communication unit <NUM> configured to send the flag signal to a local wind turbine controller, to a SCADA system or to a Remote Operating Center. In other examples, the control system <NUM> may form part of the local wind turbine controller.

It is noted that all features of the control system <NUM> can be included in methods <NUM>, <NUM> suitable for detecting a state of the wind turbine blade, and vice versa.

Claim 1:
A method (<NUM>; <NUM>; <NUM>) for detecting a state of a wind turbine blade (<NUM>), the method comprising:
receiving (<NUM>; <NUM>) one or more load signals from one or more sensors configured to measure loads on the wind turbine blade (<NUM>);
determining (<NUM>; <NUM>) an energy of the load signals at a first frequency and an energy of the load signals at a second frequency, wherein the first frequency substantially corresponds to a natural frequency of the blade in a default state;
comparing (<NUM>; <NUM>) the energy of the load signals at the first frequency to the energy of the load signals at the second frequency;
generating a flag signal (<NUM>; <NUM>) if the energy of the load signals at the first frequency is smaller than the energy of the load signals at the second frequency.