Method for detecting anomaly of variable pitch system of wind turbine generator and variable pitch controller

Abstract

An abnormality detection method of a variable pitch system of a wind turbine generator set and a variable pitch controller are disclosed. The abnormality detection method comprises: in response to a torque value of a variable pitch motor fluctuating within a predetermined time period, calculating a ratio of the torque value and a current value of the variable pitch motor at each sampling time within the predetermined time period; and in response to the variable pitch system being in a pitch adjusting state, determining whether the variable pitch system is abnormal based on the calculated ratio of the torque value and the current value of the variable pitch motor. The abnormality detection method of the variable pitch system of the wind turbine generator set and the variable pitch controller can accurately detect the abnormality of the variable pitch system and the cause of the abnormality.

Description

Technical Field

[0001] This disclosure generally relates to the field of wind power generation technology, and more specifically, to a method for detecting anomalies in the pitch system of a wind turbine generator and a pitch controller. Background Technology

[0002] The pitch system of a wind turbine plays a crucial role in maximum power tracking and ensuring safe shutdown of the wind turbine. Specifically, a major function of the pitch system is to act as the main braking system of the wind turbine, ensuring its safe and stable operation through various detection and control methods and multiple redundancy designs.

[0003] The mechanical principle of a pitch system is as follows: the blades of the wind turbine are mounted on the moving ring of the pitch bearing, and the fixed ring of the pitch bearing is mounted on the hub of the wind turbine. Simultaneously, the moving ring of the pitch bearing is mechanically connected to the mechanical output side of the gearbox via gears (or toothed belts), and the mechanical input side of the gearbox is mechanically connected to the output shaft of the pitch motor. In a pitch system, the pitch bearing needs to withstand a large overturning moment and is partially exposed, making it susceptible to contamination from sand, water mist, and ice.

[0004] Various factors, such as excessive load, insufficient lubrication, mechanical abnormalities, high vibration, and unbalanced forces, can lead to a certain degree of wear on pitch gears. When pitch gears wear, on the one hand, it affects the pitch control accuracy of the pitch system; on the other hand, the small iron slag or powder formed after wear accelerates the wear process. Deeper, more extensive cracks or multiple pits caused by tooth surface fatigue may merge together due to material failure, inducing larger areas of metal detachment from the gear surface, resulting in spalling. Furthermore, pitch gears move and transmit power while two gears mesh together. Therefore, there is mutual interaction between the points of contact between the gears. If, at a certain moment, the contact point is at the tip of a gear tooth, the gear tooth acts like a suspended beam, bearing excessive bending stress at the root of the gear. Under such circumstances, a sudden overload or impact can easily cause fracture at the tooth root due to overload. Therefore, the reliability of pitch bearings and pitch gears directly affects the performance and even the safety of the pitch system.

[0005] Traditional methods for detecting pitch system anomalies include those relying on manual experience. These methods often require frequent disassembly of the pitch gears, increasing maintenance costs and extending maintenance cycles. They are also frequently affected by the subjective factors of maintenance personnel, leading to high rates of misdiagnosis and missed diagnosis. In methods that incorporate vibration sensors, the limited mechanical space and rotating nature of the pitch gears and bearings make sensor installation and signal transmission difficult. Furthermore, the complexity of vibration signals can easily lead to misinterpretations during signal identification. Methods analyzing pitch motor torque typically employ waveform characteristics such as variance, peak factor, impulse factor, and margin factor. While these methods can reveal certain waveform characteristics, the varying rotational speeds of the pitch motor, along with differences in wind speed, direction, and gravitational loads on the impeller during rotation, cause the torque signal's period, duty cycle, and amplitude to constantly change due to component anomalies, such as those in the bearings or gears, or electrical signal anomalies. This makes accurate identification and detection difficult. Especially when the pitch system is adjusting the pitch normally, the pitch motor will have a large torque value at the moment of startup, and its waveform will also show torque fluctuations, which can be easily confused with gear abnormalities or electrical component abnormalities. Summary of the Invention

[0006] The embodiments of this disclosure provide an anomaly detection method and pitch controller for a wind turbine generator pitch system, which can accurately detect anomalies in the pitch system and the causes of the anomalies.

[0007] In one general aspect, a method for detecting anomalies in the pitch system of a wind turbine generator is provided. The method includes: in response to fluctuations in the torque value of the pitch motor within a predetermined time period, calculating the ratio of the torque value to the current value of the pitch motor at each sampling moment within the predetermined time period; and in response to the pitch system being in a pitch adjustment state, determining whether an anomaly has occurred in the pitch system based on the calculated ratio of the torque value to the current value of the pitch motor.

[0008] Optionally, the step of determining whether the pitch system has malfunctioned includes: determining that the pitch system has malfunctioned in response to the ratio meeting a preset condition.

[0009] Optionally, the step of determining that the pitch system has malfunctioned includes: determining that the pitch system has malfunctioned in response to the ratio falling into a first preset range.

[0010] Optionally, in response to the number of times the ratio calculated within the predetermined time period falls within a first preset range exceeding a first preset value, it is determined that the electrical components of the pitch system are malfunctioning.

[0011] Optionally, the step of determining that the pitch system has malfunctioned includes: determining that the pitch system has malfunctioned in response to a statistical value of the ratio calculated within the predetermined time period satisfying a preset condition.

[0012] Optionally, in response to the statistical value being less than a first threshold, it is determined that an abnormality has occurred in the mechanical components of the pitch system.

[0013] Optionally, the step of determining that the pitch system has malfunctioned includes: determining that the pitch system has malfunctioned in response to the fact that the signs of the ratios at two consecutive sampling times within the preset time period are different.

[0014] Optionally, in response to the number of times the signs of the ratio at two consecutive sampling times within the preset time period differ exceeding a preset number, it is determined that the pitch system has jammed.

[0015] Optionally, the anomaly detection method further includes: in response to the pitch system not being in pitch control mode, determining whether the pitch system is in an abnormal operating state based on the ratio.

[0016] Optionally, the step of determining whether the pitch system is in an abnormal operating state further includes: determining that the pitch system is in an abnormal operating state in response to the ratio being greater than a second threshold.

[0017] Optionally, in response to the number of times the ratio calculated within the predetermined time period is greater than the second threshold exceeding a second preset value, it is determined that the pitch system is in an abnormal operating state.

[0018] Optionally, based on the statistical values ​​of the pitch motor torque value within the predetermined time period, it can be determined whether the pitch motor torque value fluctuates within the predetermined time period.

[0019] In another general aspect, a computer-readable storage medium is provided that stores a computer program, which, when executed by a processor, implements the anomaly detection method as described above.

[0020] In one general aspect, a pitch controller is provided, the pitch controller comprising: a processor; and a memory storing a computer program that, when executed by the processor, implements the anomaly detection method as described above.

[0021] In one general aspect, a wind turbine generator set is provided, characterized in that the wind turbine generator set includes a pitch controller as described above.

[0022] According to the embodiments of the present disclosure, the method for detecting abnormalities in the pitch system of a wind turbine generator set and the pitch controller can accurately detect abnormalities in mechanical components, electrical devices, and pitch jamming by analyzing intermediate variables composed of the torque and current values ​​of the pitch motor, and can also identify abnormal operation of the pitch system caused by control abnormalities.

[0023] According to the anomaly detection method and pitch controller of the wind turbine generator pitch system according to embodiments of this disclosure, the detection of intermediate variables consisting of the torque and current values ​​of the pitch motor is not limited by changes in the signal sampling period and time window. Therefore, the detection of intermediate variables is easier to implement, and compared with conventional detection methods such as variance, kurtosis, and impulse factor, the intermediate variables have higher recognition accuracy, do not produce false alarms, and are less susceptible to interference signals or small fluctuations. In addition, since the abrupt change of the intermediate variables has only one period, it is no longer necessary to set parameters such as time window and frequency threshold during detection, making the anomaly detection method simpler and more accurate.

[0024] The anomaly detection method and pitch controller for the pitch system of a wind turbine generator according to embodiments of this disclosure are unaffected by external conditions such as pitch adjustment speed, degree of mechanical failure, rotor azimuth angle, wind force and direction, and can achieve uniform anomaly detection without causing false detections or missed detections. Compared with traditional vibration detection methods, the anomaly detection method is not affected by high signal frequency and small signal amplitude, and is therefore simpler and more direct to implement.

[0025] The anomaly detection method and pitch controller for the pitch system of a wind turbine generator set according to the embodiments of this disclosure are applicable to any type of pitch motor and have high calculation accuracy for low speed data. Attached Figure Description

[0026] The above and other objects and features of the embodiments of this disclosure will become clearer from the following description taken in conjunction with the accompanying drawings illustrating the embodiments, wherein:

[0027] Figure 1 It is a graph showing the torque of the pitch motor under the first operating condition;

[0028] Figure 2 This is a graph showing the torque of the pitch motor under the second operating condition;

[0029] Figure 3 This is a graph showing the torque of the pitch motor under the third operating condition;

[0030] Figure 4 This is a graph showing an example of the ratio of torque to current in a pitch motor;

[0031] Figure 5 This is another example of a graph showing the ratio of torque to current in a pitch motor;

[0032] Figure 6 This is another example of a graph showing the ratio of torque to current in a pitch motor;

[0033] Figure 7 This is a flowchart illustrating an anomaly detection method for the pitch system of a wind turbine generator according to an embodiment of the present disclosure;

[0034] Figure 8 This is a block diagram illustrating a pitch controller according to an embodiment of the present disclosure. Detailed Implementation

[0035] The following detailed embodiments are provided to aid the reader in gaining a comprehensive understanding of the methods, apparatus, and / or systems described herein. However, various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but may be changed as will become clear upon understanding this disclosure, except for operations that must occur in a specific order. Furthermore, for clarity and conciseness, descriptions of features known in the art may be omitted.

[0036] The following describes the operating conditions of the pitch system of a wind turbine generator set and the working principle of the anomaly detection method for the pitch system of a wind turbine generator set according to an embodiment of this disclosure.

[0037] Figure 1 This is a graph showing the torque of the pitch motor under the first operating condition.

[0038] Reference Figure 1 Curve 101 represents the torque curve of the pitch motor during normal operation of the pitch system, and curve 102 represents the torque curve of the pitch motor when the brake valve of the pitch system is worn. The horizontal axis represents the time value, and the vertical axis represents the torque value. Figure 1 As shown, when the brake valve wears out, the torque of the pitch motor will fluctuate significantly because the gravitational force on the blades changes continuously with the blade azimuth angle during impeller rotation. In contrast, the torque of the pitch system tends to be stable during normal operation.

[0039] Figure 2 This is a graph showing the torque of the pitch motor under the second operating condition.

[0040] Reference Figure 2 The horizontal axis represents the time value, and the vertical axis represents the torque value. Curve 201 represents the torque curve of the pitch motor when the pitch bearing malfunctions. Figure 2 As shown, when the pitch bearing malfunctions, the torque of the corresponding pitch motor fluctuates significantly. This is because the pitch bearing uses a ball bearing structure, so its malfunction intermittently affects the pitch motor's current. As the load increases, it affects the main magnetic flux of the pitch motor, causing armature reaction. In this case, the pitch motor's current also increases to counteract the load-induced reaction, keeping the total magnetic flux essentially constant. Furthermore, after the pitch bearing malfunctions, the torque of the pitch bearing will fluctuate significantly during blade rotation. Figure 2 As shown, the amplitude fluctuates. In addition, the fluctuation frequency and amplitude of curves 201 and 102 are different, with the fluctuation frequency and amplitude of curve 201 being higher than those of curve 102.

[0041] Figure 3 This is a graph showing the torque of the pitch motor under the third operating condition.

[0042] Reference Figure 3 Curve 301 represents the pitch angle curve during abnormal intermittent start-stop of the pitch system. In this curve, the horizontal axis represents the time value, and the vertical axis represents the angle value. Curve 302 represents the torque curve of the pitch motor during abnormal intermittent start-stop of the pitch system. In this curve, the horizontal axis represents the time value, and the vertical axis represents the torque value. It should be noted that because a characteristic of the pitch motor is that the torque is greatest at the moment of startup, when the pitch system is running normally, the torque of the pitch motor will also show a similar phenomenon during the startup process. Figure 3 The phenomenon of continuous pulsation shown is therefore easily confused with... Figure 1 and Figure 2 The pulsation phenomenon shown is confusing.

[0043] like Figures 1 to 3 As shown, when a serious abnormality occurs in the pitch system, the torque of the pitch motor will exhibit pulsation. However, using existing methods for detecting torque pulsation to detect abnormalities in the pitch system has the following drawbacks.

[0044] Existing methods for detecting torque pulsation analyze waveform characteristics such as variance, peak factor, impulse factor, and margin factor. While these methods can reveal certain waveform features, when there are abnormalities in the pitch bearing, pitch gear, or electrical signals, the period, duty cycle, and amplitude of the torque signal will vary and constantly change due to differences in the pitch motor's rotational speed, wind speed, wind direction, and gravity load on the impeller during rotation. Therefore, accurate identification and detection of the torque signal is difficult. Furthermore, when the pitch system is frequently adjusted and started, the pitch motor torque will also experience sudden changes. This torque pulsation phenomenon is easily confused with and difficult to distinguish from the torque pulsation phenomenon caused by abnormalities in mechanical components or electrical devices.

[0045] Furthermore, existing methods for detecting torque pulsations can analyze the frequency. While this method can achieve continuous detection for high-frequency, continuous pulse signals, it cannot accurately detect pulse signals with low duty cycles. In particular, the Fourier transform is frequently used for frequency detection; however, the Fourier transform has limitations in handling non-stationary processes. Specifically, for pitch control systems, when the pitch speed decreases, causing the frequency of pitch motor torque pulsations to decrease, the pulse period becomes longer, and the Fourier transform cannot effectively distinguish this change.

[0046] According to the abnormal detection method of the pitch system of the wind turbine generator set according to the embodiments of the present disclosure, the torque of the pitch motor is analyzed by combining the characteristic formula of the pitch motor, and the constant (intermediate variable) during the operation of the pitch motor is derived, thereby realizing the detection of abnormal mechanical components and electrical components of the pitch system, as well as the detection of abnormal operation of the pitch system caused by abnormal control signals.

[0047] The operating formula of the motor is shown in the following equation (1):

[0048] T=F×D=C×Φ×I×D (1)

[0049] Taking a pitch motor as an example, T represents the pitch motor's torque, F represents the pitch motor's electromagnetic force, D represents the pitch motor's shaft radius, C is the motor constant, Φ represents the pitch motor's magnetic flux, and I represents the pitch motor's current. When the pitch motor is operating normally, Φ is a constant, therefore T = Ca × I, where Ca = C × Φ × D, meaning that the pitch motor's torque is directly proportional to its current.

[0050] The formula for the torque and speed of the motor is shown in equation (2) below:

[0051] T=9550p / n (2)

[0052] Where p represents the power of the pitch motor and n represents the speed of the pitch motor.

[0053] The power formula for the motor is shown in equation (3) below:

[0054]

[0055] Where U represents the voltage of the pitch motor. This indicates the power factor of the pitch motor.

[0056] By combining equations (1), (2), and (3), we can obtain the following equation (4):

[0057]

[0058] Therefore, it can be seen that the speed of the pitch motor is directly proportional to its voltage. Furthermore, the speed of the pitch motor is directly proportional to its voltage, and its torque is directly proportional to its current. Using this characteristic, the relationship between the pitch motor's torque and current can be derived, enabling the conversion of the pitch motor's torque into a pulse waveform.

[0059] As shown in equation (4), under normal circumstances, T / I is a constant because U / n is a constant. However, when an anomaly occurs in the pitch system, the pitch drive will briefly increase the pitch motor voltage U in order to maintain a constant magnetic flux of the pitch motor, thereby causing a short-term change in the value of U / n, which in turn leads to a change in the value of T / I. Furthermore, since the pitch drive is not malfunctioning at this time, this process only lasts for a short period of time.

[0060] The reason and significance of converting the torque waveform of the pitch motor in this disclosure is as follows: Figure 1 , Figure 2 , Figure 3As shown, the characteristics of torque fluctuations vary under different operating conditions, including frequency, fluctuation amplitude, curve symmetry, pulsation width, amplitude and duration of decline, and time interval between two fluctuations. Therefore, existing methods for detecting torque pulsation are difficult to cover all waveform conditions, and the selection and adjustment of parameters are also difficult to cover all waveform conditions. In this case, the direct problems that are likely to occur are: (1) If the detection conditions are too strict or the parameters are too small, it is easy to cause frequent or even batch triggering of faults in wind turbine generators; if the wind turbine generators are falsely triggered, on the one hand, the shutdown of a single wind turbine generator will cause additional power loss; on the other hand, if the wind turbine generators are disconnected from the grid in batches, it will also cause grid fluctuations or even paralysis; (2) If the detection conditions are too broad or the parameters are too large, it will lead to missed faults, that is, after the key components of the pitch system are abnormal, the fault cannot be detected in time, and in severe cases, it will also affect the operational safety of the wind turbine generator; (3) Furthermore, since the time width of the torque pulse is uncertain, the extreme value filtering or average value filtering method cannot be used to detect the waveform of the torque pulse.

[0061] Based on the above analysis, the anomaly detection method for the pitch system of a wind turbine generator set according to the embodiments of this disclosure can be briefly described as follows. First, the pitch controller can acquire the speed value and current value of the pitch motor collected by the pitch driver, and acquire the angle value measured by the encoder. Then, the pitch controller can calculate the pitch speed value based on the angle value to determine whether the pitch motor is in operation. Next, the pitch controller can divide the torque value and the current value at each moment to obtain T / I, and determine whether an anomaly has occurred in the pitch system based on the value of T / I. The main significance of the anomaly detection method for the pitch system of a wind turbine generator set according to the embodiments of this disclosure is that: Figure 3 For example, the torque value pulsates multiple times, but the pulse has a certain time width. Existing methods for detecting torque pulsations cannot accurately match the pulse width dynamically: if the time window is too small, the pulse will not be detected; if the time window is too large, it may cover two pulses in one window (i.e., the torque values ​​at the two sampling time points are close, so the pulse cannot be detected). The frequency, amplitude, and pulse time width are all greatly related to external conditions such as pitch speed, mechanical failure degree, impeller azimuth angle, wind force and direction, so it is difficult to achieve a unified detection method.

[0062] Figure 4 This is a graph showing an example of the ratio of torque to current in a pitch motor.

[0063] Reference Figure 4 Curve 401 represents Figure 3The curve shown represents the ratio of torque to current of the pitch motor during abnormal intermittent start-stop of the pitch system. The horizontal axis represents the time value, and the left vertical axis represents the ratio of torque to current. Curve 402 represents the pitch angle curve, with the horizontal axis representing the time value and the right vertical axis representing the pitch angle value. Figure 4 As shown, when the torque value fluctuates between 251 and 751, the ratio of torque to current (T / I) undergoes a single-cycle transient change. By detecting this abrupt change, an abnormality in the pitch system can be identified. Furthermore, since the T / I abrupt change occurs over only one cycle, it is no longer necessary to set parameters such as time windows and frequency thresholds when detecting T / I abrupt changes, making detection simpler and more accurate.

[0064] Figure 5 This is another example of a graph showing the ratio of torque to current in a pitch motor.

[0065] Reference Figure 5 Curve 501 represents Figure 1 The curve shown represents the ratio of torque to current of the pitch motor when the brake valve of the pitch system is worn. The horizontal axis represents the time value, and the left vertical axis represents the ratio of torque to current. Curve 502 represents the pitch angle curve, with the horizontal axis representing the time value and the right vertical axis representing the pitch angle value. From... Figure 5 As can be seen, when the torque value fluctuates, the T / I value undergoes a single-cycle transient change. Furthermore, during pitch system startup and commutation, the torque value (T) experiences significant abrupt changes, reaching a maximum of 200, while during normal operation of the pitch system, the torque value still exhibits smaller abrupt changes, approximately 2-3. Additionally, as... Figure 5 As shown, during commutation of the pitch system, the value of T / I changes only in one direction, while... Figure 4 As shown, the T / I value undergoes abrupt changes in both positive and negative directions during pitch system commutation. Based on this characteristic, the anomaly detection method for the pitch system of a wind turbine generator set according to embodiments of this disclosure can also determine whether continuous pitch jamming has occurred in the pitch system.

[0066] Figure 6 This is another example of a graph showing the ratio of torque to current in a pitch motor.

[0067] Reference Figure 6 Curve 601 represents Figure 2 The curve shown represents the ratio of torque to current of the pitch motor when the pitch bearing malfunctions. The horizontal axis represents the time value, and the left vertical axis represents the ratio of torque to current. Curve 602 represents the pitch speed curve, with the horizontal axis representing the time value and the right vertical axis representing the pitch speed value. Figure 6 As shown, with Figure 2Compared to the torque curve 201 shown, the torque-to-current ratio curve 601 is relatively stable. This indicates that the pitch control system is not malfunctioning, but rather experiencing mechanical lag, thus allowing for smoother operation. Figure 4 , Figure 5 The situations shown are effectively distinguished to ensure the accuracy of the anomaly detection method.

[0068] Figure 7 This is a flowchart illustrating an anomaly detection method for the pitch system of a wind turbine generator set according to an embodiment of the present disclosure. The anomaly detection method can be executed by individual pitch controllers of the wind turbine generator set, or by the main controller and / or other dedicated controllers of the wind turbine generator set.

[0069] Reference Figure 7 In step S701, in response to fluctuations in the torque value of the pitch motor within a predetermined time period, the ratio of the torque value to the current value of the pitch motor at each sampling moment within the predetermined time period is calculated.

[0070] According to embodiments of this disclosure, the pitch controller can acquire the torque, current, and pitch angle of the pitch motor through various sensors, receive a given pitch speed from the main controller of the wind turbine generator, and read the encoder angle value to calculate the actual pitch speed. For example, the pitch controller calculates the actual pitch speed based on the encoder angle values ​​at two consecutive sampling times and the sampling period.

[0071] Optionally, it can be determined whether the torque value of the pitch motor fluctuates within a predetermined time period based on statistical values ​​of the pitch motor's torque value within that time period. For example, the root mean square (RMS) value and / or variance of the pitch motor's torque value within the predetermined time period can be calculated, and when the calculated RMS value is greater than a first threshold (e.g., but not limited to 500) and / or the calculated variance is greater than a second threshold (e.g., but not limited to 2500), it can be determined that the pitch motor's torque value fluctuates within the predetermined time period.

[0072] Next, in step S702, in response to the pitch system being in pitch control mode, it is determined whether an abnormality has occurred in the pitch system based on the calculated ratio of the torque value to the current value of the pitch motor.

[0073] According to embodiments of this disclosure, it can be determined whether the pitch speed (e.g., but not limited to the actual pitch speed) is continuously zero within a predetermined time period. When the pitch speed is continuously zero, it can be determined that the pitch system is not in a pitch control state; when the pitch speed is not continuously zero, it can be determined that the pitch system is in a pitch control state.

[0074] According to embodiments of this disclosure, when the calculated ratio meets a preset condition, it is determined that the pitch system has malfunctioned. Specifically, when the calculated ratio falls within a first preset range, it is determined that the pitch system has malfunctioned. Here, the first preset range can be a range greater than 1.2 and less than 10. Further, when the number of calculated ratios falling within the first preset range within a predetermined time period exceeds a first preset value, it is determined that the electrical components (e.g., brake valves, brake relays, etc.) of the pitch system have malfunctioned. On the other hand, when the number of calculated ratios falling within the first preset range within a predetermined time period does not exceed the first preset value, it is determined that the pitch system has not malfunctioned. Here, the first preset value can be, for example, 3 to 5, but is not limited to this. According to embodiments of this disclosure, the calculated ratio falling within the first preset range multiple times reflects the following phenomenon: during operation, the pitch system experiences an operational anomaly due to resistance, resulting in a slower speed, thereby increasing the value of U / n, i.e., increasing the value of T / I.

[0075] Optionally, when the statistical value of the ratio calculated within a predetermined time period meets a preset condition, it is determined that the pitch system has malfunctioned. For example, when the statistical value of the calculated ratio is less than a first threshold, it is determined that the mechanical components of the pitch system (e.g., pitch bearings, pitch gears, etc.) have malfunctioned. On the other hand, when the statistical value of the calculated ratio is greater than or equal to the first threshold, it is determined that the pitch system has not malfunctioned. Here, the statistical value can be, for example, variance, and the first threshold can be, for example, 0.01, but is not limited to these.

[0076] Optionally, when the calculated ratios at two consecutive sampling times within a preset time period have different signs, it is determined that the pitch system has malfunctioned. Further, when the number of times the calculated ratios at two consecutive sampling times within a preset time period have different signs exceeds a preset number, it is determined that the pitch system has jammed. On the other hand, when the number of times the calculated ratios at two consecutive sampling times within a preset time period have different signs does not exceed the preset number, it is determined that the pitch system has not malfunctioned. Here, the preset number can be 3 to 5 times, but is not limited to this. According to embodiments of this disclosure, since the T / I mutation has only one cycle, it is no longer necessary to set parameters such as time windows and frequency thresholds when detecting T / I mutations.

[0077] The anomaly detection method for the pitch system of a wind turbine generator set according to an embodiment of this disclosure may further include the following steps: in response to the pitch system not being in a pitch adjustment state, determining whether the pitch system is in an abnormal operating state based on the calculated ratio of the torque value to the current value of the pitch motor. Specifically, in response to the calculated ratio being greater than a second threshold, determining that the pitch system is in an abnormal operating state. Here, the pitch system being in an abnormal operating state may indicate an abnormal operating state caused by an abnormal control signal. For example, the pitch system may be running in reverse due to an abnormal control signal, or performing pitch adjustment when it should not be running. Optionally, when the number of calculated ratios greater than the second threshold within a predetermined time period exceeds a second preset value, determining that the pitch system is in an abnormal operating state. On the other hand, when the number of calculated ratios greater than the second threshold within a predetermined time period does not exceed the second preset value, determining that the pitch system is in a normal operating state. Here, the second threshold may be 40, and the second preset value may be 3 to 5, but is not limited thereto. As described above, since the T / I change has only one cycle, it is not necessary to set a time window when detecting the T / I change.

[0078] The method for detecting anomalies in the pitch system of a wind turbine generator set according to embodiments of the present disclosure analyzes intermediate variables consisting of the torque and current values ​​of the pitch motor, which can easily and accurately detect mechanical component anomalies, electrical component anomalies, and pitch jamming anomalies in the pitch system, and can also identify abnormal operation of the pitch system caused by control anomalies.

[0079] Figure 8 This is a block diagram illustrating a pitch controller according to an embodiment of the present disclosure.

[0080] Reference Figure 8 The pitch controller 800 according to embodiments of the present disclosure may include a processor 810 and a memory 820. The processor 810 may include (but is not limited to) a central processing unit (CPU), a digital signal processor (DSP), a microcomputer, a field-programmable gate array (FPGA), a system-on-a-chip (SoC), a microprocessor, an application-specific integrated circuit (ASIC), etc. The memory 820 may store computer programs to be executed by the processor 810. The memory 820 may include high-speed random access memory and / or non-volatile computer-readable storage media. When the processor 810 executes the computer program stored in the memory 820, the anomaly detection method of the pitch system of the wind turbine generator described above can be implemented.

[0081] Optionally, the pitch controller 800 can communicate with various other components in the wind turbine generator via wired or wireless communication, and can also communicate with other devices in the wind farm via wired or wireless communication. Furthermore, the pitch controller 800 can communicate with devices outside the wind farm via wired or wireless communication.

[0082] According to embodiments of this disclosure, a wind turbine generator set including a pitch controller 800 can be provided.

[0083] The anomaly detection method for the pitch system of a wind turbine generator according to embodiments of this disclosure can be programmed into a computer program and stored on a computer-readable storage medium. When the computer program is executed by a processor, the anomaly detection method for the pitch system of a wind turbine generator as described above can be implemented. Examples of computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disc storage, hard disk drive (HDD), solid-state drive (SSD), card storage (such as multimedia cards, secure digital (SD) cards, or ultra-fast digital (XD) cards), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid-state drive, and any other device configured to store a computer program and any associated data, data files, and data structures in a non-transitory manner and to provide the computer program and any associated data, data files, and data structures to a processor or computer so that the processor or computer can execute the computer program. In one example, the computer program and any associated data, data files, and data structures are distributed across a networked computer system, such that the computer program and any associated data, data files, and data structures are stored, accessed, and executed in a distributed manner through one or more processors or computers.

[0084] According to the embodiments of the present disclosure, the method for detecting abnormalities in the pitch system of a wind turbine generator set and the pitch controller can accurately detect abnormalities in mechanical components, electrical devices, and pitch jamming by analyzing intermediate variables composed of the torque and current values ​​of the pitch motor, and can also identify abnormal operation of the pitch system caused by control abnormalities.

[0085] Furthermore, the anomaly detection method and pitch controller for the pitch system of a wind turbine generator according to embodiments of this disclosure do not limit the detection of intermediate variables, consisting of the torque and current values ​​of the pitch motor, to changes in the signal sampling period and time window. Therefore, the detection of intermediate variables is easier to implement, and compared to conventional detection methods such as variance, kurtosis, and impulse factor, the intermediate variables have higher recognition accuracy, do not produce false alarms, and are less susceptible to interference signals or minor fluctuations. Moreover, since the abrupt change of the intermediate variables has only one period, it is no longer necessary to set parameters such as time windows and frequency thresholds during detection, making the anomaly detection method simpler and more accurate.

[0086] Furthermore, the anomaly detection method and pitch controller for the pitch system of a wind turbine generator according to embodiments of this disclosure are unaffected by external conditions such as pitch adjustment speed, degree of mechanical failure, rotor azimuth angle, wind force, and wind direction, enabling uniform anomaly detection without false or missed detections. Compared to traditional vibration detection methods, this anomaly detection method is not affected by high signal frequency or low signal amplitude, making it simpler and more direct to implement.

[0087] Furthermore, the anomaly detection method and pitch controller of the pitch system of the wind turbine generator set according to the embodiments of this disclosure are applicable to any type of pitch motor and have high calculation accuracy for low speed data.

[0088] While some embodiments of this disclosure have been shown and described, those skilled in the art will understand that modifications may be made to these embodiments without departing from the principles and spirit of this disclosure, which are defined by the claims and their equivalents.

Claims

1. A method for detecting anomalies in the pitch system of a wind turbine generator set, characterized in that, The anomaly detection method includes: In response to fluctuations in the torque value of the pitch motor within a predetermined time period, the ratio of the torque value to the current value of the pitch motor at each sampling moment within the predetermined time period is calculated. In response to the pitch system being in pitch control mode, the system determines whether an anomaly has occurred based on the calculated ratio of the pitch motor's torque to its current. The steps to determine whether the pitch system is malfunctioning include: If the number of times the ratio calculated within the predetermined time period falls within the first preset range exceeds the first preset value, it is determined that the electrical components of the pitch system are malfunctioning. In response to the statistical value of the ratio calculated within the predetermined time period being less than a first threshold, it is determined that an abnormality has occurred in the mechanical components of the pitch system; If the number of times the signs of the ratio at two consecutive sampling times within the predetermined time period are different exceeds a preset number, it is determined that the pitch system has jammed.

2. The anomaly detection method as described in claim 1, characterized in that, The anomaly detection method further includes: In response to the pitch system not being in pitch control mode, the system is determined to be in an abnormal operating state based on the ratio.

3. The anomaly detection method as described in claim 2, characterized in that, The step of determining whether the pitch system is in an abnormal operating state further includes: determining that the pitch system is in an abnormal operating state in response to the ratio being greater than a second threshold.

4. The anomaly detection method as described in claim 3, characterized in that, When the number of ratios calculated within the predetermined time period that are greater than a second threshold exceeds a second preset value, it is determined that the pitch system is in an abnormal operating state.

5. The anomaly detection method as described in claim 1, characterized in that, Based on the statistical values ​​of the pitch motor torque during the predetermined time period, it is determined whether the pitch motor torque value fluctuates during the predetermined time period.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the anomaly detection method as described in any one of claims 1 to 5.

7. A pitch controller, characterized in that, The pitch controller includes: processor; and A memory that stores a computer program, which, when executed by a processor, implements the anomaly detection method as described in any one of claims 1 to 5.

8. A wind turbine generator set, characterized in that, The wind turbine generator set includes the pitch controller as described in claim 7.

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