GB2620553A

GB2620553A - Wind turbine blade monitoring

Info

Publication number: GB2620553A
Application number: GB2209752.1A
Authority: GB
Inventors: Eritenel Tugan; Crowther Ashley
Original assignee: Insight Analytics Solutions Holdings Ltd
Current assignee: Insight Analytics Solutions Holdings Ltd
Priority date: 2022-07-03
Filing date: 2022-07-03
Publication date: 2024-01-17
Also published as: GB202209752D0; WO2024009069A1

Abstract

Monitoring a blade 108a of a wind turbine to detect a damage event comprises receiving acoustic signal data from a first acoustic sensor 109a1 mounted to the blade and a second acoustic sensor 110 mounted to a hub 101 of the wind turbine; identifying pulses in the acoustic signal data from the first acoustic sensor; and identifying a damage event in the blade for each identified pulse in the acoustic signal data from the first acoustic sensor having a corresponding pulse in the acoustic signal data from the second acoustic sensor that is within a first predefined time range after a time of the identified pulse in the acoustic signal data from the first acoustic sensor. Preferably the received acoustic data comprises data from a third acoustic sensor 109a2 mounted between the first and second sensor on the blade. An alert may be provided upon detection of damage. A wind turbine blade monitoring system is also claimed.

Description

WIND TURBINE BLADE MONITORING

Field of the Invention

The invention relates to a method and system for wind turbine blade monitoring to detect damage events from acoustic signals

Background

Wind turbines are subjected to intermittent and varying loading during use, which leads to wear and damage of various components such as bearings and blades, it is important to monitor such wear and damage so that repair and replacement of worn and damaged components can be carried out before failure. Monitoring of wind turbine blades is particularly important because structural failure can be catastrophic.

Wind turbine blades are generally manufactured from fibre-reinforced composite materials. Such materials will tend to degrade gradually over time due to loading and unloading causing internal cracks to grow, which may eventually lead to structural failure. Regular inspection can detect damage before failure, but some damage may be undetectable due to being within the material itself and not evident externally. A general problem is therefore how to monitor wind turbine blades over time to detect damage events before these lead to failure.

Summary of the Invention

In accordance with a first aspect of the invention there is provided a computer-implemented method of monitoring a blade of a wind turbine to detect a damage event, the method comprising: receiving acoustic signal data from a first acoustic sensor mounted to the blade and a second acoustic sensor mounted to a hub of the wind turbine; identifying pulses in the acoustic signal data from the first acoustic sensor; and identifying a damage event in the blade for each identified pulse in the acoustic signal data from the first acoustic sensor having a corresponding pulse in the acoustic signal data from the second acoustic sensor that is within a first predefined time range after a time of the identified pulse in the acoustic signal data from the first acoustic sensor.

An advantage of the method is that damage events originating in the blade can be distinguished from acoustic signals originating from places other than the blade, for example within the wind turbine gearbox and bearings, by matching identified acoustic pulses with a time-delayed pulse at the hub of the wind turbine The first acoustic sensor may be mounted at a first distance along the blade from the hub, the received acoustic signal data comprising acoustic signal data from a third acoustic sensor mounted to the blade at a second distance along the blade from the hub between the first and second sensors. The first and second distances may be between a rotational axis of the hub and the respective first and third sensors.

Identifying the damage event in the blade may comprise, for each identified pulse in the acoustic signal data from the first acoustic sensor, also identifying a corresponding pulse in the acoustic signal data from the third acoustic sensor occurring within a second predefined time range of the identified pulse in the acoustic signal data from the first acoustic sensor and the corresponding pulse in the acoustic signal data from the second acoustic sensor.

The method may further comprise determining a location in the blade of the damage event, the location of the damage event being: between the first acoustic sensor and the hub if the corresponding pulse in the acoustic signal data from the third acoustic sensor is before the identified pulse in the acoustic signal data from the first acoustic sensor: and at a distance further than the first acoustic sensor if the corresponding pulse in the acoustic signal data from the third acoustic sensor is after the identified pulse in the acoustic signal data from the first acoustic sensor.

The damage event in the blade may be identified if the identified pulse in the acoustic signal data from the first acoustic sensor has a magnitude above a predefined magnitude.

The predefined magnitude may be defined by a count of a number of times the identified pulse crosses a trigger threshold over a first defined time period. The first defined time period may for example be within a range of between 1 and 100 ms, for example aroimd 10 ms.

The method may further comprise providing an alert upon detection of a damage event in which the identified pulse in the acoustic signal data from the first acoustic sensor is above the predetermined magnitude.

The method may further comprise providing an alert upon detection of a preset number of damage events above the predetermined magnitude over a second defined time period. The second defined time period may for example be above around I second, one hour or one day.

The received acoustic signal data may be recorded acoustic signal data.

Receiving the acoustic signal data may comprise comprises receiving recorded data transmitted from a computer mounted on the wind turbine by a remote computer system.

In accordance with a second aspect of the invention there is provided a wind turbine blade monitoring system, comprising: a first acoustic sensor mounted to a blade of a wind turbine; a second acoustic sensor mounted to a hub of the wind turbine; and a computer connected to record acoustic signals from each of the first and second acoustic sensors and configured to periodically transmit recorded acoustic signal data from the first and second acoustic sensors to a remote computer system.

The wind turbine blade monitoring system may further comprise a rotation sensor configured to detect rotation of the hub, the computer configured to receive a rotation signal from the rotation sensor and to transmit the recorded acoustic signal data when the rotation signal indicates the hub is rotating below a threshold rotation speed.

The wind turbine blade monitoring system may further comprise a third acoustic sensor mounted to the blade of the wind turbine between the first and second acoustic sensors, the computer being connected to record acoustic signals from each of the first, second and third acoustic sensors.

The wind turbine blade monitoring system may comprise the remote computer system, the remote computer system being configured to perform the method according to the first aspect.

In accordance with a third aspect of the invention there is provided a computer program comprising instructions for causing a computer to perform the method according to the first aspect. The computer program may for example be provided on a non-transitory computer readable medium.

In each of the above aspects, the wind turbine may comprise a plurality of blades, typically three blades, mounted to a common hub. Each of the blades may have one or more acoustic sensors mounted thereto, with acoustic signals from the second acoustic sensor mounted to the hub used to identify damage events from the first acoustic sensor mounted to any one or more of the plurality of blades.

Detailed Description

The invention is described in further detail below by way of example and with reference to the accompanying drawings, in which: figure 1 is a schematic cutaway view of an example wind turbine; figure 2 is a schematic view of a wind turbine blade incorporating an example system for monitoring the blade; figure 3 is a schematic plot of a sequence of pulses illustrating a method of identifying a damage event using time-delay or phase difference; figure 4 is a schematic diagram of an example wind turbine monitoring system; figure 5 is a schematic flow diagram of an example method of monitoring a wind turbine blade for damage events; and figure 6 is a schematic diagram of an example controller.

Figure 1 is a schematic cutaway view of a portion of an example wind turbine 100, showing the components at and around the hub 101. The hub 101 is connected to a gearbox 102 with a main shaft 113 connected to one or two main bearings 114. In most wind turbine designs, a gearbox 102 drives an electrical generator 103 to generate electrical power when the wind turbine 100 is being driven. Direct-drive wind turbine designs exclude the gearbox 102. A turbine controller 104 controls operation of the wind turbine 100, including controlling orientation of the nacelle 105 relative to the tower 106 on which the nacelle 105 is mounted by driving a motor 107 to rotate the nacelle 105.

Typically three blades 108a-c are mounted for rotation with the hub 101 about a rotation axis I 16. Acoustic sensors 109a1_3, 109b1_3, 109c1_3 are mounted to each blade 108a-c and a further acoustic sensor 110 is mounted to the hub 101. The acoustic sensors 109ai3, I 09131_3, I 09c1_3, 110 may be microphones or accelerometers and are arranged to sense acoustic signals in the form of vibrations or pressure waves in the blades 108a-c and the hub 101. Acoustic signals detected by the acoustic sensors may be in the form of sound waves transmitted as pressure waves through the air and/or waves propagating through the structure. An orientation sensor, for example an accelerometer or an inclinometer 111, may also be mounted to the hub 101 for detection of rotation of the hub 101 and its speed, i.e. to detect when the turbine 100 is operating. An acoustic signal controller 112 may be mounted to the hub 101 and connected to receive and record signals from each of the sensors 109a1_3, 109b1_3, 109c1_3, 110 and the orientation sensor 111. Data is recorded while the turbine 100 is operating from each of the acoustic sensors and the orientation sensor synchronously to allow detection of a time-delay or phase-shift in signals received from the sensors. Sensor data may be processed by an on-board electronic circuit to enhance the acoustic or acceleration signals. Sensor and orientation data acquired during wind turbine operation may be stored locally and transmitted to a remote server when the turbine 100 is not operational, for example when idling or stopped.

Acoustic signals may be received by acoustic sensors 109a1_3, 109131_3, 109c1_3, I 10 from a crack 115 forming or propagating in the blade 108a or from other acoustic events in the blade 108a, for example resulting from an object striking the blade 108a. The signals resulting from these events may be recorded and analysed to determine their location and whether they constitute a reportable damage event, as described in more detail below.

Figure 2 illustrates schematically a wind turbine blade I 08a with multiple sensors 109ai, 3, mounted to the blade 108a at respective distances DI, D2, D3 along the blade 108a from the rotation axis 116 at the centre of the hub 101. A further acoustic sensor 110 is mounted to the hub 101. Each of the sensors 109a1.3, 110 is connected to the controller 112. A damage event 201 occurs in the blade 108a, which may, for example, be a crack propagating within the blade 108a due to loading or an external strike on the blade lOga. The damage event 201 causes acoustic signals 202 to be transmitted along the blade 108a. The acoustic signals 202 are received by the acoustic sensors 109ap3, 109b1-3, 109c1,$ on the blade 108a and the acoustic sensor 110 on the hub 101. The location of the damage event 201 results in the acoustic signals 202 reaching acoustic sensor I 09a2 first, followed by acoustic sensor 109a2, then acoustic sensor 109a3 and finally at acoustic sensor [10 on the hub 101.

Also illustrated in figure 2 is a separate acoustic event 203, which is not a damage event associated with the blade 108a. This acoustic event 203 instead originates in the hub bearing 114 and also creates acoustic signals 204, which travel through the hub and along the blade 108a. in this case, the acoustic signals 204 arrive first at the acoustic sensor 110 mounted on the hub and are received later by the acoustic sensors 109a1,3 on the blade 108a.

All acoustic signals 202, 204 as received by the sensors 109a2_3, 110 are received and recorded by the controller 112. Processing of the signals can allow for any acoustic events originating from locations other than the blade 108a to be rejected and only those events that are known to originate in the blade 108a to be identified as potential damage events. A single acoustic sensor 109a2 on the blade together with the acoustic sensor 110 on the hub would be sufficient to distinguish between acoustic signals from the blade 108a and elsewhere. Multiple acoustic sensors 109a4_3 are arranged in a spatially separated arrangement on the blade 108a to allow the location of the damage event 201 to be determined more accurately, depending on the number of sensors used. in the example shown in figure 2, the damage event 201 can be located as being between the first and second sensors 109al, 109a2 from the timing of the acoustic signal data. Other spatial arrangements may be used for the acoustic sensors I 09a1,3 depending on the spatial resolution required.

Figure 3 illustrates schematically acoustic signal data 300 comprising a series of pulses 301a-d arriving a different times T 1-14. Each pulse represents an acoustic pulse received by acoustic sensors 109a1_3, 110 respectively following an acoustic event. The timing of the pulses 301a-d corresponds to the damage event 201 illustrated in figure 2.

Pulse 301b is received first by acoustic sensor 109a2 at time Ti. followed by pulse 301a received by acoustic sensor 109a, at time T2, pulse 301c received by acoustic sensor 109a3 at time 13 and filially pulse 301d received by acoustic sensor 110 at time 14. Because all acoustic pulses 30Ia-c received on the blade arrive before the acoustic pulse 301d on the hub, it can first be inferred that the acoustic event is a potential damage event occurring on the blade 108a rather than elsewhere. Secondly, it can be inferred that the acoustic event occurred between the first and second acoustic sensors 109a I. 109a2, given that pulse 301b arrives before pulse 301a. Thirdly, knowing the speed of sound through the blade material, it can be calculated where along the blade length the acoustic event occurred by measuring a time difference ATI between pulses 301b, 301a and a time difference AT2 between pulses 301a, 301c. Given a known distance between the first and second acoustic sensors I 09ai, 109a,, an approximate measure of a distance between the acoustic event and the first sensor 109ai along the blade length can be calculated. The location of the event can also be determined by time differences between each of the pulses 301a-301c on the blade and the pulse 301d on the hub.

If only one acoustic sensor 109ai is provided on the blade, the location of the damage event can be determined to be somewhere along the blade. If one more acoustic sensor 109a2 is added at a different position along the blade 108a, the location of the damage event can be determined to be either between the hub 101 and the first acoustic sensor 109a1 or beyond the first acoustic sensor 109at, depending on the relative arrival of the pulse from the other acoustic sensor 109a2. Referring again to figure 3, if pulse 301a arrives before pulse 30 lb, but both arrive before pulse 301d, it can be inferred that the damage event is located beyond the first acoustic sensor 109ai. If, however, pulse 301a arrives after pulse 30 lb, it can be inferred that the damage event is located between the first acoustic sensor 109at and the hub 101. The relative timings of the pulses can be used to more accurately locate the damage event..

Different acoustic events will generate different magnitudes of pulses with different frequency content, and other characteristics, so not all pulses will necessarily be identified as damage events. The magnitude of the pulse 30 la from the first acoustic sensor 109ai may therefore be compared to a first predefined magnitude to exclude pulses below the first predefined magnitude and only identify pulses having a magnitude above this as damage events. A predefined magnitude may for example be defined as a peak amplitude level, a count of a number of times a signal crosses a trigger threshold over a defined time period, a signal energy measurement or an absolute energy measurement (see for example section 4.1.2 of Beattie: Acoustic Emission Non-Destructive Testing of Structures using Source Location Techniques, Sandia National Laboratories, September 2013). The values for the predefined magnitude and trigger threshold will depend on types of acoustic sensors used, in particular their sensitivity to detecting vibrations. Magnitudes and thresholds may be defined in relative terms, for example by calibrating magnitudes relative to the effect of a known impact on a turbine blade. The predefined magnitude based on an acoustic emission count may for example determine whether a given signal magnitude is exceeded by more than x times over a time period At, for example 200 times over a period of 100!is. The controller 112 may also be configured to analyse acoustic events to improve detection of possible damage, for example, by using onboard digital signal processing. Such processing may enable exclusion of events according to other characteristics such as frequency content, shape and duration of detected acoustic events.

An alert may be provided in the event of detection of a damage event if the identified pulse in the acoustic signal data from the first acoustic sensor 109a1 is above a second predefined magnitude. The second predefined magnitude may be higher than the first predefined magnitude, so that an alert is only provided when a damage event may for example result in a need for a site visit to determine the extent of any damage. An alert may alternatively be provided if the first predefined magnitude is exceeded more than a defined number of times over a defined time period. A calibration step or process may for example by used, in which data is collected upon initial startup of the specific turbine/blade/sensor spatial arrangement and/or periodically during operation.

Following such a calibration step, during operation, real-time data can be compared to the calibration data to determine whether a damage event, for example due to cracking, has occurred. In this manner, a history of the acoustic data could be built up to further provide longitudinal information.

Figure 4 illustrates schematically an example system 400 for monitoring a wind turbine blade. The system 400 comprises acoustic sensors 109a1.3 mounted to the blade of the wind turbine and an acoustic sensor 110 mounted to the hub of the wind turbine. A controller 112, i.e. a computer, located on the wind turbine is connected to record acoustic signals from each of the acoustic sensors 109a1-$, 110 and is configured to perform signal processing, decide whether to create an alert based on thresholds and periodically transmit recorded acoustic data from the acoustic sensors 109a1,3, 110 to a remote computer system 401. Transmission of the recorded acoustic data may be done via a wireless connection, for example via a mobile data connection, that connects the controller 112 to the remote server 401 via the internet 402. Signal processing may alternatively be carried out remotely by the remote server 401, with the controller 112 performing data gathering and transmission functions A minimum number of acoustic sensors is one sensor III mounted to the hub together with one sensor (i.e any one of sensors 109,a_3) mounted to the blade, increasing the number of acoustic sensors on the blade above one increases the ability to both distinguish potential damage events on the blade from acoustic events elsewhere and to locate such events more accurately. A typical implementation may include up to 3 or 5 acoustic sensors mounted to the, or each, blade, increasing the number of acoustic sensors on each blade beyond this will tend to result in less improvement for each additional sensor and with increased complexity and processing cost. A practical limit on the number of sensors on the blade may be up to around 15.

A rotation sensor 111 (see also figure 1) may be mounted to the hub 101 to detect rotation of the hub 101. The controller 112 may be configured to receive a rotation signal from the rotation sensor 111 and to transmit the recorded acoustic signal data when the rotation signal indicates the hub 101 is rotating below a threshold rotation speed, for example when the wind turbine is either idling or is stopped. Other triggers may alternatively be used to determined when the controller transmits recorded acoustic signal data, for example at predefined time intervals such as every day or every hour.

Operation of the system 400 is as described above, with processing of the recorded acoustic signal data typically being carried out by the remote computer system 401. The remote computer system 401 may for example be a cloud-based computing service and may receive acoustic signal data from a plurality of wind turbine monitoring systems.

Figure 5 illustrates schematically an example method of monitoring a blade 108a or a wind turbine according to the present disclosure. in a first step 501, acoustic signal data is received from the first acoustic sensor 109a4 mounted to the blade 108a of the wind turbine 100 and a second acoustic sensor 110 mounted to the hub 101 ofthe wind turbine 100. The acoustic signal data may be received in the form of a recording that has been transmitted from a monitoring system mounted on the wind turbine or may be received directly by a computer mounted on board the wind turbine. The acoustic data is then analysed to determine the presence of any damage events, or potential damage events by scanning the acoustic data for pulses. In step 502, an acoustic pulse is identified in I 0 the acoustic signal data from the first acoustic sensor, i.e. an acoustic sensor mounted to the blade. At step 503 a check is made whether there is a corresponding acoustic pulse from a second acoustic sensor mounted to the hub that is received within a defined time range after a time of the identified pulse from the first acoustic sensor. The defined time range may for example be determined by a distance between the first and second acoustic sensors and a known speed of sound within the blade material and may take into account a margin for error. If there is no corresponding pulse, the identified pulse is rejected (step 504) and the process repeats with step 502. If there is a corresponding pulse, the process continues to step 505 where the identified pulse is identified as a damage event, or a potential damage event. The pulse may then be checked against a magnitude threshold (step 506) and an alert provided (step 507) if the pulse is above a defined magnitude. Other checks may also be carried out as part of steps 505 and/or 506 to exclude acoustic events by analysis of other characteristics. If an alert is not triggered, the process repeats with identifying a next pulse (step 502) until all pulses are identified. An alert may also be triggered if a preset number of potential damage events, which may individually be below a threshold value, are detected over a period of time, which may indicate a gradual build-up of damage events that together indicate a need for a site inspection.

A check for the magnitude of the identified pulse may also be included in steps 502 or 505 to discount pulses having a magnitude determined to be too low to be identified as a damage event. The process may thereby include a check against a first magnitude threshold and a higher second magnitude threshold, with damage events corresponding to identified pulses from the first acoustic sensor having corresponding pulses from the second acoustic sensor having a magnitude above the first magnitude threshold and an alert only provided in the event that one or more of the damage events has a magnitude above the second threshold magnitude.

Referring back to figure 1, in an example implementation three acoustic sensors 109ai- 3, 109b1.3, 109ci.3 may be mounted to each blade 108a, 108b, 108c, with a further acoustic sensor 110 and rotation sensor 111 mounted to the hub 101, making a total of 11 sensors. The acoustic sensors 109a1_3, 109b1_3, 10901_3 may for example be mounted around 3m apart along the blade length between the root and tip of each blade 108a-c. During recording of sensor data, a rotation speed is recorded along with acoustic signals from each of the sensors for a set period, for example two minutes. A high-pass filter, for example having a cut-off frequency set at around 2 kHz, may be used to reduce or eliminate noise from acoustic signals deriving from the turbine drivetrain. Recorded data is saved and transmitted for processing. Recordings and transmissions may be repeated continuously.

Referring to Figure 6, the controller 112 includes a non-transitory computer-readable medium with program instructions stored thereon for performing the above-described method. In some embodiments, the controller may include at least one memory 603, at least one processor 602, and a network interface 604. Additionally or alternatively, in other embodiments, the controller 112 may include a different type of computing device operable to carry out the program instructions. For example, in some embodiments, the controller may include an application-specific integrated circuit (ASIC) that performs processor operations, or a field-programmable gate array (FPGA).

While the controller 112 of the system 400 may be included in a single unit and/or provided in a distinct housing 601, as shown in figure 6, in other embodiments at least some portion of the controller may be separate from the housing 601. For example, in some embodiments, one or more parts of the controller 112 may be part of a smartphone, tablet, notebook computer, or wearable device. Further, in some embodiments, the controller 112 may be a client device, i.e., a device actively operated by the user, while in other embodiments, the controller 112 may be a server device, e.g., a device that provides computational services to a client device. Moreover, other types of computational platforms are also possible in embodiments of the disclosure.

The memory 603 is a computer-usable memory, such as random-access memory (RAM), read-only memory (ROM), non-volatile memory such as flash memory, a solid state drive, a hard-disk drive, an optical memory device, and/or a magnetic storage device. The memory 603 may be used to store recorded acoustic data prior to being transmitted.

The processor 602 of the controller 112 includes computer processing elements, e.g., a central processing unit (CPU), a digital signal processor (DSP), or a network processor. In some embodiments, the processor 602 may include register memory that temporarily stores instructions being executed and corresponding data and/or cache memory that temporarily stores performed instructions in certain embodiments, the memory 603 stores program instructions that are executable by the processor 602 for carrying out the methods and operations of the disclosure, as described herein.

The network interface 604 provides a communications medium, such as, but not limited to, a digital and/or an analog communication medium, between the controller 112 and other computing systems or devices. In some embodiments, the network interface 604 may operate via a wireless connection, such as IEEE 802.11 or BLUETOOTH, using an antenna 605 to send and receive signals, while in other embodiments the network interface 604 may operate via a physical wired connection, such as an Ethernet connection. Still in other embodiments, the network interface 346 may communicate using another convention. The network interface 604 may also or alternatively operate according to a wireless telecommunications standard, for example a 30, 40 or 50 standard, to transmit and receive data.

Other embodiments are intentionally within the scope of the invention as defined by the appended claims.

Claims

CLAIMS1. A computer-implemented method of monitoring a blade (108a) of a wind turbine (100) to detect a damage event, the method comprising: receiving acoustic signal data (300) from a first acoustic sensor (109a1) mounted to the blade (108a) and a second acoustic sensor (110) mounted to a hub (101) of the wind turbine (100); identifying pulses (301a) in the acoustic signal data (300) from the first acoustic sensor (109a1); and identifying a damage event (201) in the blade (108a) for each identified pulse (301a) in the acoustic signal data from the first acoustic sensor (109a1) having a corresponding pulse (301d) in the acoustic signal data from the second acoustic sensor (110) that is within a first predefined time range after a time of the identified pulse (301a) in the acoustic signal data (300) from the first acoustic sensor (109a1).
2. The method of claim I. wherein the first acoustic sensor (109a1) is mounted at a first distance (DI) along the blade (108a) from the hub (101), the received acoustic signal data (300) comprising acoustic signal data from a third acoustic sensor (109a2) mounted to the blade (108a) at a second distance (D2) along the blade (108a) from the hub (101) between the first and second sensors (109al, 110).
3. The method of claim 2, wherein identifying the damage event (201) in the blade (108a) comprises, for each identified pulse (301a) in the acoustic signal data (300) from the first acoustic sensor (109a1), also identifying a corresponding pulse (301b) in the acoustic signal data (300) from the third acoustic sensor (109a2) occurring within a second predefined time range of the identified pulse (301a) in the acoustic signal data from the first acoustic sensor ( I 09a1) and the corresponding pulse (301b) in the acoustic signal data from the second acoustic sensor ( I 09a2), 4. The method of claim 3, comprising determining a location in the blade (108a) of the damage event (201), the location of the damage event being: between the first acoustic sensor (109a1) and the hub (101) if the corresponding pulse (301b) in the acoustic signal data from the third acoustic sensor (109a7) is before the identified pulse (301a) in the acoustic signal data from the first acoustic sensor (109a1); and at a distance further than the first acoustic sensor (109a1) if the corresponding pulse (30 lb) in the acoustic signal data from the third acoustic sensor (109a2) is after the identified pulse (301a) in the acoustic signal data from the first acoustic sensor (109a1) The method of any preceding claim, wherein the damage event (201) in the blade (108a) is identified if the identified pulse (301a) in the acoustic signal data from the first acoustic sensor (1093.1) has a magnitude above a predefined magnitude.6. The method of claim 5, wherein the predefined magnitude is defined by a count of a number of times the identified pulse (301a) crosses a trigger threshold over a first defined time period.7. The method of any preceding claim, comprising providing an alert upon detection of a damage event in which the identified pulse in the acoustic signal data from the first acoustic sensor is above the predetermined magnitude.S. The method of any one of claims 1 to 6, comprising providing an alert upon detection of a preset number of damage events above the predetermined magnitude over a second defined time period.9. The method of any preceding claim, wherein the received acoustic signal data is recorded acoustic signal data (300).10. The method of claim 9, wherein receiving the acoustic signal data (300) comprises receiving recorded data transmitted from a controller (112) mounted on the wind turbine ( 100) by a remote computer system (401).11. A wind turbine blade monitoring system (400), comprising: a first acoustic sensor (109a1_3) mounted to a blade (108a) of a wind turbine (100); a second acoustic sensor (110) mounted to a hub (101) of the nd turbine (100); and a controller (112) connected to record acoustic signals from each of the first and second acoustic sensors (109ap3, 110) and configured to periodically transmit recorded acoustic signal data from the first and second acoustic sensors (109a1-3, 110) to a remote computer system (401).12. The wind turbine blade monitoring system (400) of claim II, comprising a rotation sensor (111) configured to detect rotation of the hub (101), the controller (112) configured to receive a rotation signal from the rotation sensor (111) and to transmit the recorded acoustic signal data when the rotation signal indicates the hub (101) is rotating below a threshold rotation speed.13. The wind turbine blade monitoring system (400) of claim 11 or claim 12, comprising a third acoustic sensor (109a2, 109a3) mounted to the blade (108a) of the wind turbine (100) between the first and second acoustic sensors (109al, 110), the controller (112) being connected to record acoustic signals from each of the first, second and third acoustic sensors (109a2, 110, 109a2, 109a3).14. The wind turbine blade monitoring system (400) of any one of claims 11 to 13, comprising the remote computer system (401), the remote computer system (401) being configured to perform the method according to any one of claims 1 to 10.15. A computer program comprising instructions for causing a computer to perform the method according to any one of claims 1 to 10.