Patent Description:
Wind turbines are a growing source of electricity primarily due to their low carbon footprint and concerns over the impact of traditional methods of generating electricity on the environment. However, in order to accelerate the replacement of plants that rely on fossil fuels with wind turbines, and to remain competitive with other forms of renewable energy, it is important to continue to reduce the cost of providing electricity with wind turbines. One source of costs with wind turbines is maintaining the turbines. Maintenance must be frequent enough to prevent power disruptions due to component failure but should not be unnecessarily frequent due to the cost of sending a crew to perform inspections. Maintenance of wind turbines is particularly expensive due to many factors, such as the remote nature of many wind farms, the necessity to disrupt the production of electricity while maintenance is performed, and the fact that the turbines are typically on top of tall towers, and thus difficult to reach.

One way of monitoring operation of a wind turbine is to place vibration sensors on or near components that tend to wear out. The need for maintenance is then determined by analysing vibrations received by the sensor to determine if vibrations characteristic of a worn or failing component are present. However, these types of systems add cost and complexity to the wind turbine due to the need for additional sensors, which themselves become potential points of failure. In addition, the sources of noise in wind turbines can be difficult to isolate, which often leads to misdiagnosis of problems and unnecessary maintenance. In particular, operating conditions often affect vibration data, thereby making it difficult to separate noises being generated in different locations in the wind turbine.

Thus, there is a need for improved systems, methods, and computer program products which enable the detection of vibrations in wind turbines and diagnosis of component condition based on the detected vibrations.

<CIT> discloses a system for detecting damage of a pitch bearing of a wind turbine. The pitch bearing is part of a pitch drive system having a plurality of pitch drive motors. The method includes measuring at least one electrical signal of the pitch drive system. The method also includes processing the electrical signal(s) of the pitch drive system and comparing the electrical signals of the pitch drive system with a baseline threshold. Thus, the method also includes determining whether damage is present in the pitch bearing based, at least in part, on the comparison, wherein the electrical signal(s) exceeding the baseline threshold is indicative of damage in the pitch bearing.

<CIT> a method for monitoring a pitch system of a wind turbine which includes monitoring, via one or more first sensors, at least one electrical condition of the pitch system. The method also includes monitoring, via one or more second sensors, at least one mechanical condition of the pitch system. Further, the method includes receiving, via a controller communicatively coupled to the one or more first and second sensors, sensor signals representing the at least one electrical condition and the at least one mechanical condition of the pitch system. Thus, the method includes determining, via the controller, a bearing condition of a pitch bearing of the pitch system based on the at least one electrical condition and the at least one mechanical condition of the pitch system.

<CIT> discloses a method for determining the rotational speed of the rotor of a wind turbine and/or for monitoring the state of a rotor blade of a wind turbine, comprising the following method steps: measuring the current of at least one blade adjustment motor of a wind turbine over a predetermined period of time, characterized in that the rotational speed of the rotor is determined by ascertaining the period of oscillation of the motor current, and the rotor position is determined by way of zero point evaluation and gradient evaluation, and/or the state of the rotor blade is determined with the aid of a time or frequency analysis of the motor current of at least one blade adjustment motor.

In an embodiment of the invention, a system for monitoring operation of a wind turbine including a rotor having a blade is provided. The system includes one or more processors, and a memory coupled to the one or more processors. The memory includes program code that, when executed by the one or more processors, causes the system to receive a time-domain signal indicative of a pitch force being applied to the blade, determine a first spectral density of the time-domain signal, determine a condition of the wind turbine based on a frequency content of the first spectral density, and in response to the condition being indicative of a problem with the wind turbine, generate an alarm signal.

In an aspect of the invention, the time-domain signal is indicative of a pressure of a fluid in a chamber of a hydraulic actuator of a pitch drive that controls a pitch of the blade.

In another aspect of the invention, the program code causes the system to determine the first spectral density by sampling the time-domain signal to generate a discrete time-domain signal, selecting a plurality of samples from the discrete time-domain signal that are within a sampling window, and transforming the plurality of samples from a time-domain to a frequency-domain.

In another aspect of the invention, the rotor rotates in a rotor plane having a plurality of sectors, and the sampling window corresponds to a first period of time when the blade is in a selected sector of the plurality of sectors.

In another aspect of the invention, the blade passes through a horizontal position while the blade moves through the selected sector.

In another aspect of the invention, the plurality of samples is selected so that each sample of the plurality of samples corresponds to a wind speed that is within a predetermined wind speed range or a rate of change in the wind speed that is within a predetermined rate of change in wind speed range.

In another aspect of the invention, the samples are selected so that each sample of the plurality of samples corresponds to a pitch position that is within a predetermined pitch position range or a rate of change in the pitch position that is within a predetermined rate of change in pitch position range.

In another aspect of the invention, the samples are selected so that each sample of the plurality of samples corresponds to a power output of the wind turbine that is within a predetermined power output range or a rate of change in the power output of the wind turbine that is within a predetermined rate of change in power output range.

In another aspect of the invention, the rotor rotates in the rotor plane having the plurality of sectors, the sampling window is one of at least two sampling windows, the samples are selected so that each sample of the plurality of samples is in each sampling window of the at least two sampling windows, and the at least two sampling windows are selected from a first sampling window corresponding to a first period of time when the blade is in a selected sector of the plurality of sectors, a second sampling window corresponding to a wind speed that is within a predetermined wind speed range or a rate of change in the wind speed that is within a predetermined rate of change in wind speed range, a third sampling window corresponding to a pitch position that is within a predetermined pitch position range or a rate of change in the pitch position that is within a predetermined rate of change in pitch position range, and a fourth sampling window corresponding to a power output of the wind turbine that is within a predetermined power output range or a rate of change in the power output of the wind turbine that is within a predetermined rate of change in power output range.

In another aspect of the invention, the samples are selected so that each sample of the plurality of samples corresponds to a load on the blade that is within a predetermined load range.

In another aspect of the invention, the program code causes the system to determine the condition of the wind turbine based on the frequency content of the first spectral density by comparing the first spectral density to a second spectral density determined for the wind turbine during a second period of time when the wind turbine is known to have been operating normally.

In another aspect of the invention, the program code causes the system to determine the condition of the wind turbine based on the first spectral density by defining at least one frequency bin covering a portion of the first spectral density, determining one or more of a maximum amplitude, a mean amplitude, and a minimum amplitude of the portion of the first spectral density covered by the at least one frequency bin, comparing the one or more of the maximum amplitude, the mean amplitude, and the minimum amplitude of the portion of the first spectral density to a respective alarm threshold, and triggering an alarm if the one or more of the maximum amplitude, the mean amplitude, and the minimum amplitude exceeds its respective alarm threshold.

In another aspect of the invention, the at least one frequency bin is one of a plurality of frequency bins each covering a different portion of the first spectral density, and the determining, comparing, and triggering steps are performed for each of the plurality of frequency bins.

In another aspect of the invention, the program code causes the system to determine the condition of the wind turbine based on the first spectral density by defining at least one working-point having a frequency corresponding to a harmonic of a rotation of the rotor, determining one or more of a maximum amplitude, a mean amplitude, and a minimum amplitude for the at least one working-point, comparing the one or more of the maximum amplitude, the mean amplitude, and the minimum amplitude for the at least one working-point to a respective alarm threshold, and triggering an alarm if the one or more of the maximum amplitude, the mean amplitude, and the minimum amplitude of the at least one working-point exceeds the alarm threshold.

In another aspect of the invention, the at least one working-point is one of a plurality of working-points each corresponding to a different harmonic of the rotation of the rotor, and the determining, comparing, and triggering steps are performed for each of the plurality of working-points.

In another aspect of the invention, the program code further causes the system to, in response to the first spectral density including a frequency component having an amplitude above a resonance threshold, activate a resonance control algorithm that dampens resonances corresponding to the frequency component.

In another embodiment of the invention, a method for monitoring operation of the wind turbine including the rotor having the blade is presented. The method includes receiving the time-domain signal indicative of the pitch force being applied to the blade, determining the first spectral density of the time-domain signal, determining the condition of the wind turbine based on the frequency content of the first spectral density, and, in response to the condition being indicative of a problem with the wind turbine, generating an alarm signal.

The above summary presents a simplified overview of some embodiments of the invention to provide a basic understanding of certain aspects of the invention discussed herein. The summary is not intended to provide an extensive overview of the invention, nor is it intended to identify any key or critical elements, or delineate the scope of the invention. The sole purpose of the summary is merely to present some concepts in a simplified form as an introduction to the detailed description presented below.

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate various embodiments of the invention and, together with the general description of the invention given above, and the detailed description of the embodiments given below, serve to explain the embodiments of the invention.

It should be understood that the appended drawings are not necessarily to scale, and may present a somewhat simplified representation of various features illustrative of the basic principles of the invention. The specific design features of the sequence of operations as disclosed herein, including, for example, specific dimensions, orientations, locations, and shapes of various illustrated components, may be determined in part by the particular intended application and use environment. Certain features of the illustrated embodiments may have been enlarged or distorted relative to others to facilitate visualization and a clear understanding. In particular, thin features may be thickened, for example, for clarity or illustration.

Embodiments of the invention determine a condition of a wind turbine based on an amount of force exerted on one or more blades of the wind turbine to control the pitch of the blades. To this end, a time-domain signal indicative of the pitch force being applied to a blade of the wind turbine is received by a monitoring system. This signal may be directly related to the pitch force (e.g., a signal output by a strain gauge measuring the force being applied to the blade by a pitch drive), or may be indirectly related to the pitch force (e.g., a signal output by a pressure sensor measuring the pressure in a hydraulic actuator of the pitch drive). In either case, it has been determined that the frequency content of these types of signals can provide information on the operation of the wind turbine.

A spectral density of the time-domain signal may be obtained by converting the time-domain signal to a frequency-domain signal. The condition of the wind turbine or one or more components of the wind turbine may then be determined based on the spectral density. A sampling window may be applied to the signal in the time-domain that selects which portions of the signal are to be analyzed. Selectively filtering samples in the time-domain based on various operating parameters has been determined to improve the ability of the monitoring system to detect certain conditions of the wind turbine, such as worn bearings or other components which need to be serviced.

<FIG> illustrates an exemplary wind turbine <NUM> in accordance with an embodiment of the invention. The wind turbine <NUM> includes a tower <NUM>, a nacelle <NUM> disposed at the apex of the tower <NUM>, and a rotor <NUM> operatively coupled to a generator in the nacelle <NUM>. In addition to the generator, the nacelle <NUM> typically houses various components needed to convert wind energy into electrical energy and needed to operate and optimize the performance of the wind turbine <NUM>. The tower <NUM> supports the load presented by the nacelle <NUM>, rotor <NUM>, and other wind turbine components housed inside the nacelle <NUM>. The tower <NUM> of wind turbine <NUM> elevates the nacelle <NUM> and rotor <NUM> to a height above ground level that allows the rotor <NUM> to spin freely and at which air currents having lower turbulence and higher velocity are often found.

The rotor <NUM> includes a hub <NUM> and one or more (e.g., three) blades <NUM> attached to the hub <NUM> at locations distributed about the circumference of the hub <NUM>. The blades <NUM> project radially outward from the hub <NUM>, and are configured to interact with passing air currents to produce rotational forces that cause the hub <NUM> to spin about its longitudinal axis. This rotational energy is delivered to the generator housed within the nacelle <NUM> and converted into electrical power. To optimize performance of the wind turbine <NUM>, the pitch of blades <NUM> is adjusted by a pitch system in response to wind speed and other operational conditions.

<FIG> is a front-view of the rotor <NUM> of wind turbine <NUM> showing pitch bearings <NUM> that operatively couple the blades <NUM> to the hub <NUM>. Each pitch bearing <NUM> has an axis of rotation that is generally aligned with a longitudinal axis of the blade <NUM>. The pitch bearings <NUM> are configured so that each blade <NUM> can be rotated relative to the hub <NUM> around the bearing's axis of rotation, and to transfer forces between the hub <NUM> and the blades <NUM>. These forces include those induced by gravity, centrifugal force, wind loading, and the load presented by the generator.

The direction the gravitational force acts on a pitch bearing <NUM> varies depending on the position of the blade <NUM>, and thus produces a varying load <NUM> that tends to repeat over each rotation of the rotor <NUM>. When the rotor <NUM> is rotating, the bearings <NUM> are also subjected to centrifugal force, which mainly produces an axial pull in the pitch bearings <NUM>. The forces produced by wind loading include forces that cause the rotor <NUM> to rotate, and typically produce the greatest load on the pitch bearing <NUM>. The pitch bearing <NUM> is configured to transfer these loads to the hub <NUM>, which in turn transfers these loads to the rest of the wind turbine <NUM>.

Changing the pitch of a blade <NUM> generally changes the amount of lift and drag generated by the blade <NUM> in response to the wind, which changes the driving force provided to the hub <NUM> by the blade <NUM> and lateral forces that are transferred to the tower <NUM>. Thus, pitch systems can be used to help control the wind turbine <NUM>, optimize power production under varying wind conditions, and prevent damage from excessive amounts of wind.

<FIG> presents a perspective view in which the nacelle <NUM> is partially broken away to expose structures housed inside. A main shaft extending from the rotor <NUM> into the nacelle <NUM> may be held in place by a main bearing support <NUM> which supports the weight of the rotor <NUM> and transfers the loads on the rotor <NUM> to the tower <NUM>. The main shaft may be operatively coupled to a gearbox <NUM> that transfers the rotation thereof to a generator <NUM>. The electrical power produced by the generator <NUM> may be supplied to a power grid (not shown) or an energy storage system (not shown) for later release to the grid as understood by a person having ordinary skill in the art. In this way, the kinetic energy of the wind may be harnessed by the wind turbine <NUM> for power generation. The nacelle <NUM> may also house other equipment (not shown) used to operate the wind turbine <NUM>, such as hydraulic pumps, hydraulic accumulators, cooling systems, controllers, sensors, batteries, communication equipment, etc..

The weight of the nacelle <NUM> including the components housed therein may be carried by a load bearing structure <NUM>. The load bearing structure <NUM> may include an outer housing of the nacelle <NUM> and one or more additional structural components such as a framework or lattice, and a gear bell which through a yaw bearing (not shown) operatively couples the load of the nacelle <NUM> to the tower <NUM>. The yaw bearing may be configured to allow the nacelle <NUM> to be rotated into or out of the wind by a yaw system. The hub <NUM> may house at least a portion of a pitch system that includes one or more pitch drives <NUM>. Each pitch drive <NUM> may include one or more pitch actuators <NUM> (e.g., a hydraulic cylinder, electrical actuator, mechanical actuator, etc.) configured to provide a pitch force and that is operatively coupled to a respective blade <NUM> of rotor <NUM> by a linkage <NUM>.

<FIG> illustrates an exemplary control system <NUM> that may be used to control the wind turbine <NUM>. The control system <NUM> includes a wind turbine controller <NUM> in communication with a wind sensor <NUM>, a pitch system <NUM>, a yaw system <NUM>, and a supervisory controller <NUM>. The supervisory controller <NUM> may be configured to implement a system-wide control strategy for a group of wind turbines <NUM> (e.g., a wind farm) that optimizes the collective performance of the wind turbines <NUM>, e.g., to maximize power production of the group and minimize overall maintenance. The yaw system <NUM> may be used by the wind turbine controller <NUM> to control the direction in which the nacelle <NUM> is pointed, and may include one or more yaw controllers, drive systems, position sensors, etc. configured to implement a yaw command signal received from the wind turbine controller <NUM>. The pitch system <NUM> may be configured to adjust the pitch of the blades <NUM> collectively or independently in response to a pitch command signal received from the wind turbine controller <NUM>. The mechanical force, or "pitch force", necessary to pitch the blades <NUM> may be provided by the pitch drive <NUM>.

<FIG> illustrates an exemplary pitch system <NUM> that includes a pitch controller <NUM>, a hydraulic actuator <NUM>, and a hydraulic valve <NUM> (e.g., a proportional valve) that couples the hydraulic actuator <NUM> to a source <NUM> of pressurized hydraulic fluid. The pitch controller <NUM> may be an independent controller configured to control the pitch of one or more blades <NUM> of the wind turbine <NUM>, or may be provided by another controller, such as the wind turbine controller <NUM>.

The hydraulic actuator <NUM> includes a piston <NUM> located within a cylinder <NUM> that is terminated on one end by a cylinder cap <NUM> and on the other end by a cylinder head <NUM>. The piston <NUM> is coupled to a piston rod <NUM> and divides the interior of the cylinder <NUM> into a front chamber <NUM> (also known as a piston rod chamber) through which the piston rod <NUM> passes, and rear chamber <NUM> (also known as a bottom chamber) that is terminated by the cylinder cap <NUM>.

The piston rod <NUM> passes through a sealed opening in the cylinder head <NUM> and includes a distal end operatively coupled to the blade <NUM> by a linkage <NUM>. The linkage may include a ball joint, pivot joint, or other joint that allows rotation between the distal end of the piston rod <NUM> and the blade <NUM> about at least one axis. Movement of the piston rod <NUM> may thereby cause the blade <NUM> to rotate about a longitudinal axis of the pitch bearing <NUM>. The cylinder cap <NUM> may be operatively coupled to the hub <NUM> of rotor <NUM> (e.g., by another joint that allows rotation) so that movement of the piston <NUM> causes an angular displacement of the blade <NUM> relative to the hub <NUM>. The pitch controller <NUM> thereby causes the piston <NUM> to apply a pitch force to the piston rod <NUM> in a forward direction (toward the cylinder head <NUM>) or in a rearward direction (toward the cylinder cap <NUM>) in response to activation of the hydraulic valve <NUM>.

In response to receiving a signal from the pitch controller <NUM>, the hydraulic valve <NUM> may selectively fluidically couple an output port of the fluid source <NUM> to one of the front chamber <NUM> and rear chamber <NUM> of hydraulic actuator <NUM>, and selectively fluidically couple a return port of the fluid source to the other of the front chamber <NUM> and rear chamber of hydraulic actuator <NUM>. The pitch controller <NUM> may thereby control the flow of fluid between the fluid source <NUM> and the hydraulic actuator <NUM> via actuation of the hydraulic valve <NUM>. The fluid source <NUM> may include one or more pumps, valves, accumulators, etc. configured to provide pressurized fluid. The fluid source <NUM> may be dedicated to operation of a single hydraulic actuator <NUM>, or may provide fluid to multiple hydraulic actuators <NUM> controlled by the pitch system <NUM>.

The pitch system <NUM> may further include one or more of a front chamber pressure sensor <NUM>, a rear chamber pressure sensor <NUM>, and a position sensor <NUM>. The front chamber pressure sensor <NUM> is configured to sense the pressure of the fluid in, or that is being provided to, the front chamber <NUM> of hydraulic actuator <NUM>. The rear chamber pressure sensor <NUM> is configured to sense the pressure in, or that is being provided to, the rear chamber <NUM> of hydraulic actuator <NUM>. Each pressure sensor <NUM>, <NUM> may output a respective pressure signal <NUM>, <NUM> indicative of the pressure sensed by the sensor. For example, each signal <NUM>, <NUM> may have one or more characteristics (e.g., a voltage, current, impedance, frequency, phase, etc.) that provide information to the pitch controller <NUM> indicative of the sensed pressure.

The pitch position sensor <NUM> may be configured to provide a pitch position signal <NUM> to the pitch controller <NUM> indicative of the pitch position φ of the blade <NUM> in a similar manner as described above with respect to the pressure sensors <NUM>, <NUM>. By way of example, the pitch position sensor <NUM> may be configured to measure the angular position of the blade <NUM> using one or more sensors, such as optical sensors, magnetic sensors or mechanical sensors, which may be used to generate signals indicative of the pitch position φ of the blade <NUM> to the pitch controller <NUM>.

The pitch controller <NUM> may use the pressure data received from the pressure sensors <NUM>, <NUM> to determine a pitch force being applied to the blade <NUM> by the hydraulic actuator <NUM>. The pitch force may be determined, for example, using the following equation: <MAT> where FP is the pitch force applied by the piston rod <NUM>, PFC is the pressure in the front chamber <NUM>, PRC is the pressure in the rear chamber <NUM>, AFF is the effective area of the piston <NUM> facing the front chamber <NUM>, and ARF is the effective area of the piston <NUM> facing the rear chamber <NUM>. As can be seen from Equation <NUM>, a positive value of pitch force FP indicates the piston rod <NUM> is pushing on the blade <NUM>, and a negative value of force pitch force FP indicates the piston rod <NUM> is pulling on the blade <NUM>. The effective area of the piston <NUM> facing the rear chamber <NUM> is typically larger than the effective area of the piston <NUM> facing the front chamber <NUM> due to the presence of the piston rod <NUM>. Thus, under certain operating conditions (e.g., when the piston <NUM> is not moving), the pressure of the fluid in the front chamber <NUM> may tend to be higher than the pressure of the fluid in the rear chamber <NUM>. In some cases, a force sensor (not shown) may be used to measure the pitch force FP directly. In this case, the pitch force FP can be determined without pressure measurements, or the force may be calculated based on pressure measurements merely to check operation of the force sensor.

<FIG> illustrates an exemplary pitch system <NUM> in accordance with an alternative embodiment of the invention that utilizes a mechanical actuator <NUM> comprising a motor <NUM> (e.g., an electric or hydraulic motor) operatively coupled to a screw <NUM> that provides pitch force to the blade <NUM>. The screw <NUM> may include a cylindrical shaft <NUM> having a helical ridge <NUM> and a threaded collar <NUM> including a hole having a helical grove configured to mesh with the helical ridge <NUM> of cylindrical shaft <NUM>. The screw <NUM> may be configured so that when the motor <NUM> rotates the cylindrical shaft <NUM>, the collar <NUM> is urged longitudinally along an axis of the cylindrical shaft <NUM> in a direction dependent on the direction of rotation.

The collar <NUM> may be coupled to the linkage <NUM> by a connecting rod <NUM> so that the pitch force generated by the screw <NUM> is operatively coupled to the blade <NUM>, i.e., so that movement of the collar <NUM> alters the pitch of the blade <NUM>. The pitch system <NUM> may also include a force sensor <NUM> (e.g., a stress gauge) that provides a signal <NUM> to the pitch controller <NUM> indicative of the pitch force FP being applied to the blade <NUM> by the mechanical actuator <NUM>.

It should be understood that, although the pitch system <NUM> has been generally described with reference to a pitch drive <NUM> including a single pitch actuator <NUM> per blade, the invention is not so limited. Embodiments of the invention may include pitch systems <NUM> having more than one pitch actuator per blade, as well as pitch actuators that rotate the blade <NUM> relative to the hub <NUM> in one or more axes of rotation.

One or more of the wind turbine controller <NUM>, supervisory controller <NUM>, pitch controller <NUM>, or other suitable computing system may be configured to execute a wind turbine monitoring process that collects and analyzes at least one time-domain signal indicative of pitch force. Signals indicative of pitch force may include signals directly related to pitch force (e.g., that are provided by a force sensor), signals indirectly related to pitch force, such as an amount of energy provided to a pitch actuator (e.g., that are provided by torque, current, voltage, or pressure sensors), or any other signal having a value that is correlated to pitch force. The pitch monitoring process may sample one or more time-domain signals indicative of pitch force and store the sampled values, or "samples" in memory as a discrete time-domain signal suitable for analysis. For example, pressure from one or more pitch actuators <NUM> of pitch system <NUM> may be sampled at regular intervals, e.g., with a sampling frequency fS above the Nyquist limit of any subsequent spectral analysis. A typical sampling frequency fS may have a frequency greater than or equal to <NUM>, which would potentially allow for analysis of spectral content up to at least <NUM>.

Samples indicative of pitch force, or "pitch force samples" may be stored in memory local to the wind turbine <NUM> producing the data, and may also be uploaded to a central database for analysis. The pitch monitoring process may thereby enable measurement of time varying characteristics of one or more signals indicative of pitch force. These characteristics may include the spectral content associated with one or more pitch axes and pitch actuators. By way of example, the pressure in a chamber of a hydraulic cylinder of a blade of the wind turbine <NUM> may be sampled and stored.

The spectral density of a signal indicative of pitch force may be analyzed over a predetermined band, such as between <NUM> to <NUM>. The term "spectral density" as used herein refers to the relationship between amplitude and frequency of signals in the frequency-domain, i.e., the power or energy distribution of the signal with respect to frequency. The amplitude of this frequency-domain signal may correspond to an amount of power or energy in the signal at the frequency in question, or in a frequency range centered on the frequency in question.

Other operational parameters of the wind turbine <NUM> may also be measured, sampled, and stored. As described in more detail below, these operational parameters may be indexed to the pitch force samples and used to determine which pitch force samples are selected for analysis and which pitch force samples are excluded from analysis, e.g., ignored or discarded.

<FIG> depict graphs <NUM>-<NUM> including plots <NUM>-<NUM>, <NUM>-<NUM> of exemplary amplitude verses frequency for pitch position φ (graphs <NUM> and <NUM>) and pitch force Fp (graphs <NUM> and <NUM>) for each of three blades <NUM> of a wind turbine <NUM> subject to a wind speed Vw of about <NUM>-<NUM> meters/second (m/s) and having a generating capacity of about <NUM> Mega-watts (MW). Each graph <NUM>-<NUM> includes a respective vertical axis <NUM>-<NUM> corresponding to amplitude, and a horizontal axis <NUM>-<NUM> corresponding to frequency. The vertical axes <NUM>, <NUM> of graphs <NUM>, <NUM> are in units of angular degrees, the vertical axis <NUM>-<NUM> of graphs <NUM>, <NUM> are in units of Newtons, and the horizontal axes <NUM>-<NUM> are in units of Hertz (Hz).

The spectral density of the pitch position φ displayed by graphs <NUM>, <NUM> was generated from position verses time data by a Fast Fourier Transform (FFT) using a four-second sampling window (plots <NUM>-<NUM>) and a <NUM>-second sampling window (plots <NUM>-<NUM>). The pitch system in question included a servo drive having a frequency response fSD = <NUM> that adjusted the pitch of each blade <NUM> based on the pitch command signal received from the wind turbine controller <NUM> and the pitch position signal <NUM>. Plot <NUM> is an exemplary alarm threshold for the pitch position spectral density generated using the four-second sampling window.

The pitch force spectral density displayed by graphs <NUM>, <NUM> was generated from force verses time data using an FFT with a four-second sampling window (plots <NUM>-<NUM>) and a <NUM>-second sampling window (plots <NUM>-<NUM>) for the pitch system described above with respect to plots <NUM>, <NUM>. Plot <NUM> is an exemplary alarm threshold for the pitch force spectral density generated using the four-second sampling window.

It has been determined that relatively short sampling windows (e.g., four seconds) are generally useful for determining spectral content of position or force data for frequencies above <NUM>, and in particular, for frequencies in the range of <NUM>-<NUM>. In contrast, relatively long sampling windows (e.g., <NUM> seconds) are generally useful for determining spectral content for frequencies below <NUM>, such as frequencies related to the rotation of the rotor <NUM>. Frequencies corresponding to the rate the rotor <NUM> is rotating can be seen as amplitude peaks centered at approximately <NUM> (peak <NUM> corresponding to the fundamental frequency or first harmonic of rotation), <NUM> (peak <NUM> corresponding to the second harmonic of rotation), <NUM> (peak <NUM> corresponding to the third harmonic of rotation) <NUM> (peak <NUM> corresponding to the fourth harmonic of rotation), and <NUM> (peak <NUM> corresponding to the fifth harmonic of rotation).

It has been further determined that energy in a spectral region <NUM> generally centered around <NUM> is associated with vibrations of the blade edges. The frequencies produced by edge vibrations are particularly visible in the plots <NUM>-<NUM> of pitch force graph <NUM>, with distinct regions <NUM>, <NUM> of elevated amplitude seen at <NUM> and from <NUM> up to <NUM>. This energy is believed to be generated by the trailing edge of the blade, and manifests itself as a relatively high amplitude in the spectral region <NUM> centered on <NUM> and as a broad peak in the spectral region <NUM> beginning at about <NUM> and ending at about <NUM>. The relatively high spectral density in these spectral regions <NUM>, <NUM> may be related to pitch actuation eigenfrequencies. The relatively high spectral density in these spectral regions <NUM>, <NUM> may also be associated with concurrence of hydraulic cylinder and blade inertia eigenfrequencies, as well as blade eigenfrequencies.

The alarm threshold levels <NUM>, <NUM> may be determined empirically, i.e., by collecting data on one or more wind turbines (e.g., the specific wind turbine to be monitored) that are known to be functioning properly and which are operating under normal operating conditions. The alarm thresholds may then be set with sufficiently high limits to avoid alarms under these conditions to prevent unnecessary down time due to false alarms. In general, short sampling window data may be used for monitoring the wind turbine <NUM>, and the long sampling window data may be used to characterize operation of the wind turbine and set alarm limits.

In an embodiment of the invention, frequency binning may be used to analyze spectral densities generated from pitch force related data. <FIG> illustrates graph <NUM> showing exemplary frequency binning for purposes of describing some binning techniques which may be used for data analysis. In the exemplary embodiment, frequency bins are defined to include a low-frequency bin <NUM> that covers frequencies between <NUM> and <NUM>, a medium frequency bin <NUM> that covers frequencies between <NUM> and <NUM>, and a high-frequency bin <NUM> that covers frequencies above <NUM>. It should be understood that these frequency bins are exemplary only, and the invention is not limited to any particular size or number of frequency bins. Thus, any alternative frequency bins could be defined, e.g., one bin per Hz or even overlapping frequency bins.

In an embodiment of the invention, maximum, mean, and minimum amplitudes of the spectral density may be determined for each frequency bin. By way of example, lines <NUM>-<NUM> indicate the maximum values in each of bins <NUM>-<NUM>, respectively. Maximum, mean, and minimum amplitudes may also be determined for a plurality of "working-points" <NUM>-<NUM> each corresponding to a harmonic of the rotation of the rotor <NUM>. By way of example, for a rotor <NUM> having a time of rotation tR = <NUM> sec (i.e., one <NUM> degree rotation every four seconds), the frequencies of working-points <NUM>-<NUM> may be fx = x<NUM>/tr, x<NUM>/tr, x<NUM>/tr, x<NUM>/tr, x<NUM>/tr, where x<NUM> - x<NUM> are integers (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>). The work-points may be determined in relation to the rotor speed for each time step, so that if the angular velocity of the rotor changes, the work-points <NUM>-<NUM> shift in frequency.

The maximum, minimum, and mean values in each bin and of each working-point may be determined and used for triggering alarms in order to avoid bin values being dominated by averaging over time for a moving window of time, e.g., <NUM> seconds. The maximum, minimum, and mean values may each be compared to a respective limit, and an alarm triggered if at least one of the values exceeds (e.g., rises above or falls below) its limit.

<FIG> illustrates an exemplary user interface <NUM> that includes a plurality of windows <NUM>-<NUM> each displaying data relating to operation of the wind turbine <NUM>. Each window includes a graph <NUM>-<NUM> showing a value verses time for a monitored parameter of the wind turbine <NUM>, and a data box <NUM>-<NUM> that displays statistics values (e.g., maximum, minimum, mean, and standard deviation) relating to the data represented by the respective graph <NUM>-<NUM>. Exemplary parameters include a wind speed graph <NUM> displaying a plot <NUM> of wind speed verses time, a power output graph <NUM> displaying a plot <NUM> of power output verses time for the wind turbine <NUM>, a pitch position graph <NUM> including plots <NUM>-<NUM> of the pitch position φ verses time for each of three blades, and a pitch pressure graph <NUM> including plots <NUM>-<NUM> of a pitch pressure (e.g., front chamber pressure) verses time for each of the three blades.

The frequency-domain data illustrated in <FIG> may be based on the time-domain data collected from sensors in the wind turbine <NUM> and displayed by the graphs <NUM>-<NUM> of user interface <NUM>. Supervision limits may be set so that the supervision is robust with regard to false alarms. Initially, <NUM>-second sampling window values may be used to generate baselines for the supervision values. For example, alarm limits may be set to trigger an alarm with the maximum amplitude levels of the working-points or frequency bands exceed an alarm threshold. An exemplary alarm threshold may be provided by: <MAT> where Talarm is the threshold for the measured or calculated amplitude, and β is a scaling value that depends on the parameter being monitored. Exemplary values for the scaling value may be β = <NUM> for working-points and β = <NUM> for frequency bands. Typically, the lowest frequency values in a frequency band will produce the highest alarm threshold, and this tendency is reflected by the <NUM>/f factor. Alarm thresholds may be active for a period exceeding that of the longest sampling window (e.g., ≥ <NUM> seconds). In response to a monitored parameter exceeding the alarm threshold, an alarm may be detected, and supervision triggered.

For embodiments of the invention in which hydraulic actuators are used to generate pitch force Fp, the frequency content of hydraulic fluid pressure verses time may be used to provide information regarding system resonances and blade stability. This data can be obtained, for example, by determining the frequency content of pressure verses time data taken from a single chamber of a hydraulic cylinder. Sampling the sensor data using a sampling frequency fS = <NUM> has been determined to provide sufficient resolution to enable analysis of frequencies up to at least <NUM>. This frequency content can provide an indication of controller stability, levels of wear or fatigue of hardware components, condition of hydraulic fluid (e.g., high air content changes frequency measurement), the state of the blade, etc..

Changes in the amplitude of monitored frequencies or working-points may indicate changes in system performance and robustness of system design. For example, if the blade and pitch system each have a resonance at about the same frequency, this resonance may produce a spike in spectral density near the resonance. It has been determined that, in general, frequency characteristics are tied to certain fundamental characteristics of the wind turbine, and can therefore provide useful information about how the wind turbine is operating.

Processing to determine spectral densities can be done using a number of different methods. For example, binning may be performed using digital bandpass filters in the time-domain, or using an FFT to convert sampled signals from the time-domain to the frequency-domain. In any case, as can be seen by the difference in smoothness between four-second and <NUM>-second sampling windows, the sampling window should be selected to maximize the utility of the resulting frequency data.

Frequency analysis of pitch force data may provide improved knowledge of components and system at low cost. In cases where the sensors are already present, the only cost may be an increase in the processing load of the controller or other computing device performing the analysis. However, much of this processing can occur during times when the processing load from operating the wind turbine is low, thereby limiting the impact on computing devices in the wind turbine. Additional parameters that may correlate with or otherwise affect the spectral content of the pitch position φ, pitch force Fp, and pressure data include the absolute direction of the wind, the bandwidth of control loops, wind speed, pitch out, and resonances in the edge of the blade.

Frequency analysis of the pressure, force, and position data provides a spectral fingerprint of the wind turbine <NUM> under different operating conditions. This spectral fingerprint may enable identification of problems in specific portions of the pitch system <NUM> (e.g., the control loop) or other components of the wind turbine <NUM>, such as the gearbox. For example, it has been determined that vibrations occurring in the <NUM> - <NUM> range are typically generated by the pitch drive system <NUM>. Thus, changes to the frequency content in this range may be indicative of wear or failure of a component in the pitch drive system <NUM>.

Some sources of vibrations in the blades of the wind turbine may be dependent on which sector of rotation the blade is in, as well as other operational parameters of the wind turbine. For example, a failing pitch bearing may only cause a certain vibration in the pitching system when the blade in question is passing through a certain sector of rotation due to the effect of gravity. By configuring a sampling window to select pitch force samples collected from a blade while the blade is in one or more specified sectors of rotation, embodiments of the invention may isolate these sources of vibrations. In a preferred embodiment, the sampling window may also be adjusted based on other operating conditions so that only samples collected under conditions known to provide good data are used to determine the condition of the wind turbine. The sampling window can also be configured differently depending on the component that is being monitored in order to optimize the ability of the system to determine the condition of the component in question. For example, by selecting samples that correspond to an operating condition that produces certain vibrations in the component.

<FIG> depicts a rotor plane <NUM> that is perpendicular to an axis of rotation of the rotor <NUM> and through which the blades <NUM> of rotor <NUM> rotate. The position of each blade <NUM> in the rotor plane <NUM> may be identified by an azimuth angle θblade of the blade. The azimuth angle θblade of the blade is defined relative to a reference angle θref. In the depicted embodiment, the reference angle θref is defined by a vector <NUM> originating at the axis of rotation and pointing downward through the rotor plane <NUM>, and the value of the azimuth angle θblade increases as the blade <NUM> moves in a clockwise direction away from the reference angle θref as viewed from the front. However, it should be understood that both the position of the reference angle θref and the direction of increasing value of the azimuth angle θblade is arbitrary, and any reference angle and direction of rotation can be used.

The rotor plane <NUM> may be divided into a plurality of sectors <NUM>-<NUM> (e.g., four sectors) each defined by a range of azimuth angles θ. In the depicted embodiment, the sectors <NUM>-<NUM> include a sector <NUM> with azimuth angles between θ<NUM> and θ<NUM> (θ<NUM> < θ < θ<NUM>), a sector <NUM> with azimuth angles between θ<NUM> and θ<NUM> (θ<NUM> < θ < θ<NUM>), a sector <NUM> with azimuth angles between θ<NUM> and θ<NUM> (θ<NUM> < θ < θ<NUM>), and a sector <NUM> with azimuth angles between θ<NUM> and θ<NUM> (θ<NUM> < θ < θ<NUM>), where θ<NUM> = <NUM> degrees for sector <NUM> and θ<NUM> = <NUM> degrees for sector <NUM>. Although <FIG> depicts four sectors, it should be understood that embodiments of the invention are not limited to a specific number or size of sectors, and the rotor plane <NUM> may be divided into any number of sectors each having any size.

The angular position of the rotor <NUM> may be provided by an azimuth sensor configured to measure the azimuth angle θ of the rotor <NUM>, or rotor azimuth angle θrotor. Because the azimuth angle θ of each blade <NUM>, or blade azimuth angle θblade is fixed relative to the rotor azimuth angle θrotor, the sector each blade <NUM> is in at a given time can be determined based on the rotor azimuth angle θrotor.

By way of example, for the above exemplary rotor plane <NUM>, the data received from sensors in the blades may be parsed into windows each corresponding to one of the sectors <NUM>-<NUM> through which the blade passes during each full <NUM> degrees of rotation. Data corresponding to each window may then be converted from the time-domain to the frequency-domain so that that the frequency content of the signal for each sector is isolated. Different spectral fingerprints may then be applied to each sector to increase the resolution and accuracy of the monitoring process.

Origins of peaks in these spectral fingerprints may include resonant frequencies in the blades <NUM> or components thereof, and resonances in the blade pitch drive system, which may be dependent on the blade pitch or angular position of the rotor <NUM>. In cases where resonances of different components or systems are aligned in frequency, they may constructively reinforce each other and thereby causes problems in operation of the wind turbine.

In order to control oscillations in the wind turbine <NUM>, the pitch controller <NUM> may be configured to implement a resonance control algorithm that damps resonances in response to detecting an excessive amount of energy at a particular frequency or in a particular frequency band. Embodiments of the system may also be used to test wind turbine models. For example, each model being tested can be used to predict spectral densities that will be produced by the wind turbine in operation. Models which accurately predict spectral densities similar to those measured may then be considered accurate models.

As described above, samples comprising a discrete time-domain signal indicative of pitch force Fp may be selected for or excluded from analysis based on conditions at the time the sample was taken. For example, whether or not the sample was taken during a period of time when some parameter exceeded a threshold. This selection may be performed by generating a sampling window that selects which pitch force samples are used for analysis according to the desired conditions.

<FIG> depicts a blade azimuth graph <NUM> including a plot <NUM> of blade azimuth angle θblade verses time, and a sampling window graph <NUM> including a plot <NUM> of a sampling window S(t). Graph <NUM> includes a vertical axis <NUM> corresponding to the blade azimuth angle θblade, and a horizontal axis <NUM> corresponding to time. Graph <NUM> includes a vertical axis <NUM> corresponding to whether samples are selected for analysis of the discrete time-domain signal (S = <NUM>) or excluded from analysis of the discrete time-domain signal (S = <NUM>), and a horizontal axis <NUM> corresponding to time. The horizontal axes <NUM>, <NUM> are aligned so that the sampling window plot <NUM> illustrates correspondence between the sampling window S(t) and blade azimuth angle θblade. Graph <NUM> includes horizontal dashed lines <NUM>-<NUM> each corresponding to an azimuth angle θ threshold that defines a boundary between a sector <NUM>-<NUM> of the rotor plane <NUM> during which samples are selected for analysis and a sector <NUM>-<NUM> of the rotor plane <NUM> during which samples are excluded from analysis. Vertical dashed lines <NUM>-<NUM> indicate times t<NUM>-t<NUM> when the azimuth angle θ of the blade <NUM> crosses (i.e., exceeds) one of these thresholds, and illustrate how this defines the sampling window S(t) as shown by sampling window plot <NUM>.

<FIG> depicts sampling window graph <NUM> from <FIG> and a wind speed graph <NUM>. The wind speed graph <NUM> includes a vertical axis <NUM> corresponding to the wind speed Vw, a horizontal axis <NUM> corresponding to time t, and a plot <NUM> of wind speed Vw verses time t. The horizontal axis <NUM> of graph <NUM> is aligned with the horizontal axis <NUM> of graph <NUM>. A horizontal dashed line <NUM> indicates a wind speed threshold above which the wind speed is considered too high to provide good data. Although not shown, embodiments of the invention may also include a wind speed threshold below which the wind speed is considered too low to provide good data. In either case, when the wind speed Vw exceeds a wind speed threshold, samples may be excluded from analysis by the sampling window S(t).

In the depicted example, vertical dashed lines <NUM>, <NUM> indicate times t<NUM>, t<NUM> at which the wind speed Vw exceeds the wind speed threshold. The wind speed Vw exceeds the wind speed threshold at time t<NUM>, and falls back below the threshold at time t<NUM>. Because at time t<NUM> the blade <NUM> is in a sector of rotation from which samples are already excluded by the sampling window S(t), the wind speed Vw exceeding the wind speed threshold does not have an immediate effect on the sampling window S(t). However, as indicated by the grayed-out region <NUM> of the sampling window plot <NUM> between time t<NUM> and t<NUM>, when the blade <NUM> exceeds the blade azimuth threshold corresponding to time t<NUM>, because the wind speed Vw is still above the wind speed threshold, the sampling window plot <NUM> remains at <NUM> until time t<NUM>. when the wind speed Vw falls below the wind speed threshold.

<FIG> depicts sampling window graph <NUM> from <FIG>, and a power output graph <NUM>. The power output graph <NUM> includes a vertical axis <NUM> corresponding to the power output Pwt of the wind turbine <NUM>, a horizontal axis <NUM> corresponding to time t, and a plot <NUM> of power output Pwt verses time t. The horizontal axis <NUM> of graph <NUM> is aligned with the horizontal axis <NUM> of graph <NUM>, and a horizontal dashed line <NUM> indicates a power output threshold above which samples are to be excluded by the sampling window S(t). Vertical dashed lines <NUM>, <NUM> indicate times t<NUM>, t<NUM> at which the power output of the wind turbine <NUM> exceeds this threshold.

In the depicted example, the power output exceeds the power output threshold at time t<NUM>, and falls back below the threshold at time t<NUM>. Because at time t<NUM> the blade <NUM> is in a sector of rotation from which samples are normally included in analysis of the discrete time-domain signal, the power output exceeding the power output threshold has an immediate effect on the sampling window S(t). As can be seen by the grayed-out region <NUM> of the sampling window plot <NUM> between time t<NUM>, and t<NUM>, when the power output of the wind turbine <NUM> exceeds the power output threshold, the sampling window S(t) is modified so that samples are excluded from analysis of the discrete time-domain signal. Because the blade <NUM> has exceeded the blade azimuth threshold corresponding to time t<NUM> before the power output of the wind turbine <NUM> drops back below the power output threshold at time t<NUM>, the sampling window plot <NUM> remains at <NUM> until time t<NUM> when the blade <NUM> enters the next sector in which samples are to be analyzed.

<FIG> depicts sampling window graph <NUM> from <FIG>, and a pitch position graph <NUM>. The pitch position graph <NUM> includes a vertical axis <NUM> corresponding to the pitch position φ of the blade <NUM>, a horizontal axis <NUM> corresponding to time t, and a plot <NUM> of pitch position φ verses time. The horizontal axis <NUM> of graph <NUM> is aligned in time with the horizontal axis <NUM> of graph <NUM>, and a horizontal dashed line <NUM> indicates a pitch position threshold above which samples are to be excluded by the sampling window S(t). Vertical dashed line <NUM> indicates a time t<NUM> at which the pitch position φ of the blade <NUM> exceeds the pitch position threshold.

In the depicted example, the pitch position φ exceeds the pitch position threshold at time t<NUM>. Because at time t<NUM> the blade <NUM> is in a sector of rotation from which samples are normally included in analysis of the discrete time-domain signal, the pitch position φ exceeding the pitch position threshold has an immediate effect on the sampling window S(t). As can be seen by the grayed out region <NUM> of the sampling window plot <NUM> between time t<NUM> and t<NUM>, and the grayed-out region <NUM> after t<NUM>, when the pitch position φ of the blade <NUM> exceeds the pitch position threshold, the sampling window S(t) is modified so that samples are excluded from analysis of the discrete time-domain signal.

<FIG> depicts the sampling window graph <NUM> from <FIG> and a pitch force graph <NUM>. The pitch force graph <NUM> includes a vertical axis <NUM> corresponding to the pitch force Fp being applied to the blade <NUM>, a horizontal axis <NUM> corresponding to time t, and a plot <NUM> of pitch force Fp verses time. The horizontal axis <NUM> of graph <NUM> is aligned with the horizontal axis <NUM> of graph <NUM>, and vertical dashed lines <NUM>-<NUM> indicate times at which the sampling window plot <NUM> changes value between "<NUM>" (select sample) and "<NUM>" (exclude sample).

The sampling window S(t) represented by plot <NUM> shows that samples selected for analysis include those prior to t<NUM>, between time t<NUM> and time t<NUM>, between time t<NUM> and time t<NUM>, between time t<NUM> and time t<NUM>, between time t<NUM> and time t<NUM>, and between time t<NUM> and time t<NUM>. Portions of the pitch force signal represented by plot <NUM> that fall within portions of the sampling window S(t) in which samples are selected for analysis are shown as bold segments <NUM>-<NUM>. These segments <NUM>-<NUM> correspond to periods of time when all the selection parameters are met such that the value of the sampling window S(t) is "<NUM>".

The sample window function S(t) may be implemented as a logical "AND" function with inputs from a plurality of logic conditions each defining a sampling window. For the embodiments described above, S(t) = Sθ(t)×SV(t)×SP(t)×Sφ(t), where the blade azimuth sampling window Sθ(t) = <NUM> when the blade azimuth angle θblade exceeds a blade azimuth threshold, and Sθ(t) = <NUM> when the blade azimuth angle θblade is within the blade azimuth threshold. Likewise, the wind speed sampling window SV(t) = <NUM> when the wind speed Vw exceeds a wind speed threshold, and SV(t) = <NUM> when the wind speed Vw is within the wind speed threshold. The power output sampling window SP(t) = <NUM> when the power output Pwt of the wind turbine <NUM> exceeds a power output threshold, and SP(t) = <NUM> when the power output Pwt of the wind turbine <NUM> is within the power output threshold. The pitch position sampling window Sφ(t) = <NUM> when the pitch position φ of the blade <NUM> exceeds a pitch position threshold, and Sφ(t) = <NUM> when the pitch position φ of the blade <NUM> is within the pitch position threshold.

It should be understood that other embodiments could use different combinations of operational parameters to generate sampling windows. Moreover, in addition to the value of a parameter, the rate of change of the value of the parameter, or the value of the parameter integrated over a time interval may also be used to generate sampling windows. Thus, the invention is not limited to sampling windows based on any particular type or combination of operational parameters, or to sampling windows based on any particular type or combinations of functions applied to the operational parameters.

Referring now to <FIG>, embodiments of the invention described above, or portions thereof, may be implemented using one or more computer devices or systems, such as exemplary computer <NUM>. The computer <NUM> may include a processor <NUM>, a memory <NUM>, an input/output (I/O) interface <NUM>, and a Human Machine Interface (HMI) <NUM>. The computer <NUM> may also be operatively coupled to one or more external resources <NUM> via the network <NUM> or I/O interface <NUM>. External resources may include, but are not limited to, servers, databases, mass storage devices, peripheral devices, cloud-based network services, or any other resource that may be used by the computer <NUM>.

The processor <NUM> may include one or more devices selected from microprocessors, microcontrollers, digital signal processors, microcomputers, central processing units, field programmable gate arrays, programmable logic devices, state machines, logic circuits, analog circuits, digital circuits, or any other devices that manipulate signals (analog or digital) based on operational instructions that are stored in memory <NUM>. Memory <NUM> may include a single memory device or a plurality of memory devices including, but not limited to, read-only memory (ROM), random access memory (RAM), volatile memory, non-volatile memory, static random access memory (SRAM), dynamic random access memory (DRAM), flash memory, cache memory, or data storage devices such as a hard drive, optical drive, tape drive, volatile or non-volatile solid state device, or any other device capable of storing data.

The processor <NUM> may operate under the control of an operating system <NUM> that resides in memory <NUM>. The operating system <NUM> may manage computer resources so that computer program code embodied as one or more computer software applications, such as an application <NUM> residing in memory <NUM>, may have instructions executed by the processor <NUM>.

The I/O interface <NUM> may provide a machine interface that operatively couples the processor <NUM> to other devices and systems, such as the external resource <NUM> or the network <NUM>. The application <NUM> may also have program code that is executed by one or more external resources <NUM>, or otherwise rely on functions or signals provided by other system or network components external to the computer <NUM>.

A database <NUM> may reside in memory <NUM> and may be used to collect and organize data used by the various systems and modules described herein. The database <NUM> may include data and supporting data structures that store and organize the data.

In general, the routines executed to implement the embodiments of the invention, whether implemented as part of an operating system or a specific application, component, program, object, module or sequence of instructions, or a subset thereof, may be referred to herein as "computer program code," or simply "program code. " Program code typically comprises computer-readable instructions that are resident at various times in various memory and storage devices in a computer and that, when read and executed by one or more processors in a computer, cause that computer to perform the operations necessary to execute operations or elements embodying the various aspects of the embodiments of the invention.

The program code embodied in any of the applications/modules described herein is capable of being individually or collectively distributed as a computer program product in a variety of different forms. In particular, the program code may be distributed using a computer-readable storage medium having computer-readable program instructions thereon for causing a processor to carry out aspects of the embodiments of the invention.

In certain alternative embodiments, the functions, acts, or operations specified in the flowcharts, sequence diagrams, or block diagrams may be re-ordered, processed serially, or processed concurrently consistent with embodiments of the invention. Moreover, any of the flowcharts, sequence diagrams, or block diagrams may include more or fewer blocks than those illustrated consistent with embodiments of the invention. It should also be understood that each block of the block diagrams or flowcharts, or any combination of blocks in the block diagrams or flowcharts, may be implemented by a special purpose hardware-based system configured to perform the specified functions or acts, or carried out by a combination of special purpose hardware and computer instructions.

Claim 1:
A system for monitoring operation of a wind turbine (<NUM>) including a rotor (<NUM>) having a blade (<NUM>), wherein the rotor (<NUM>) rotates in a rotor plane (<NUM>) having a plurality of sectors (<NUM>-<NUM>), the system comprising:
one or more processors (<NUM>); and
a memory (<NUM>) coupled to the one or more processors (<NUM>) and including program code (<NUM>) that, when executed by the one or more processors (<NUM>), causes the system to:
receive a time-domain signal (<NUM>) indicative of a pitch force being applied to the blade (<NUM>);
determine a first spectral density (<NUM>) of the time-domain signal (<NUM>) by sampling the time-domain signal (<NUM>) to generate a discrete time-domain signal, selecting a plurality of samples from the discrete time-domain signal that are within a sampling window (S(t)) and transforming the plurality of samples from a time-domain to a frequency-domain;
determine a condition of the wind turbine (<NUM>) based on a frequency content of the first spectral density (<NUM>); and
in response to the condition being indicative of a problem with the wind turbine (<NUM>), generate an alarm signal, wherein
the sampling window (S(t)) corresponds to a first period of time when the blade (<NUM>) is in a selected sector of the plurality of sectors (<NUM>-<NUM>).