Pitch Bearing Abnormal Detection Method and Device for Wind Turbine

Abstract

Disclosed are a method and a device for detecting abnormalities of a pitch bearing of a wind turbine. The method for detecting abnormalities of the pitch bearing includes: obtaining the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each shaft of the wind turbine; determining whether the pitch speeds and pitch angles of the respective shafts are consistent; and in response to the pitch speeds and pitch angles of the respective shafts being consistent, determining whether there is an abnormality in the pitch bearing of the wind turbine based on the pitch motor voltage and pitch motor current of the respective shafts.

Description

Technical Field

[0001] The present disclosure generally relates to the technical field of wind power generation, and more specifically, to a method and a device for detecting anomalies in a pitch bearing of a wind turbine generator. Background Art

[0002] With the gradual expansion of the scale of wind turbine generators and the increasing improvement of unit safety protection, the power generation performance of the operation of wind turbine generators, that is, increasing the power generation and availability of wind turbine generators, has received more and more attention. On the other hand, while pursuing power generation benefits, the safety of wind turbine generators must be strictly ensured.

[0003] In a wind turbine generator set, a main function of the pitch system is to act as the pneumatic braking system of the unit. The electric pitch system ensures the safe and stable operation of the wind turbine generator through various detection and control means and multiple redundant designs. Any fault-induced shutdown will cause the servo motor of the pitch system to release the brake and drive the blade to the feathering position of 89 degrees. At the same time, since the blade angle range of the pitch system is 0 to 89 degrees, when the blade is feathered to the 89-degree position, the servo motor of the pitch system needs to stop the pitch motor and apply the brake, the purpose of which is to prevent the blade position from sliding under the action of gravity and rotating out of the limit position.

[0004] The mechanical principle of the pitch system is as follows: The blades of the wind turbine generator are installed on the moving ring of the pitch bearing, the fixed ring of the pitch bearing is installed on the hub of the wind turbine generator. At the same time, the moving ring of the pitch bearing is mechanically connected to the mechanical output side of the reducer through a gear or toothed belt drive, and the mechanical input side of the reducer is mechanically connected to the output shaft of the pitch motor. The pitch bearing has to bear a large overturning moment and is partially exposed, making it vulnerable to pollution and damage by sand, dust, water mist, ice, etc. Therefore, surface anti-corrosion treatment needs to be carried out to meet the requirements throughout the service life.

[0005] However, due to various reasons such as excessive root load, under-lubrication, mechanical anomalies, large vibrations, and unbalanced forces, the pitch bearing may experience mechanical failure or even fracture. Since the blade is directly installed on the moving ring of the pitch bearing, in severe cases, the blade may even fall off, resulting in serious accidents. Therefore, it is very important and significant to monitor the operation of the pitch bearing.

[0006] However, in reality, since the pitch bearing is a mechanical component without electrical feedback points and cannot be installed with electrical components, it is difficult to identify and detect faults. The reasons are as follows: After the pitch bearing shows abnormalities (such as fractures or wear), since there is no resistance on the motor side, the rotational torque acting on the pitch bearing is relatively large, so it will not have an obvious impact on the pitch speed. That is to say, when the pitch bearing has an abnormality, it will not cause the pitch system to trigger a fault, nor will it cause the wind turbine to shut down. However, once the pitch bearing fails, the resulting safety hazards are huge.

[0007] In the existing methods, the methods for checking and eliminating pitch bearing abnormalities are generally the methods of shutting down the machine and manual inspection, that is, during quarterly, semi-annual, or annual maintenance, manual inspection and elimination are carried out on the mechanical components of the wind turbine. This method has a great lag on the one hand, and the discovery of fault points has a great contingency on the other hand. Summary of the Invention

[0008] Therefore, the present disclosure analyzes the mechanical structure characteristics of the pitch bearing and the operating mechanism of the pitch system, and proposes a method and device for detecting pitch bearing abnormalities based on the operating data of the pitch system. The method and device for detecting pitch bearing abnormalities can analyze and judge whether the pitch bearing is abnormal by comparing the data during continuous pitching (unfurling or feathering) of the pitch system, so as to send out early warning information in advance, notify the operation and maintenance personnel to conduct troubleshooting of the cause of the fault, and prevent major accidents from occurring.

[0009] In one general aspect, a method for detecting pitch bearing abnormalities of a wind turbine is provided. The method for detecting pitch bearing abnormalities includes: obtaining the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each axis of the wind turbine; determining whether the pitch speeds and pitch angles of each axis are consistent; and in response to the pitch speeds and pitch angles of each axis, determining whether the pitch bearing of the wind turbine is abnormal based on the pitch motor voltage and pitch motor current of each axis.

[0010] Optionally, the method for detecting pitch bearing abnormalities further includes: in response to the pitch bearing of the wind turbine being abnormal, outputting an alarm message indicating the pitch bearing abnormality.

[0011] Optionally, the step of determining whether the pitch bearing of the wind turbine is abnormal based on the pitch motor voltage and pitch motor current of each axis includes: calculating the sum of the pitch motor voltages of each axis within a predetermined time, and calculating the sum of the pitch motor currents of each axis within the predetermined time; and determining whether the pitch bearing of the wind turbine is abnormal based on the sum of the pitch motor voltages of each axis within the predetermined time and the sum of the pitch motor currents of each axis within the predetermined time.

[0012] Optionally, the step of determining whether there is an abnormality in the pitch bearing of the wind turbine based on the sum of the pitch motor voltages of each axis and the sum of the pitch motor currents of each axis within the predetermined time includes: determining whether there is a deviation in the sum of the pitch motor voltages of each axis within the predetermined time; in response to there being a deviation in the sum of the pitch motor voltages of each axis within the predetermined time, determining whether there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time; in response to there being a deviation in the sum of the pitch motor currents of each axis within the predetermined time, determining that there is an abnormality in the pitch bearing of the wind turbine.

[0013] Optionally, the step of determining whether there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time includes: determining whether the ratio between the sums of the pitch motor currents of each axis within the predetermined time is greater than a first predetermined threshold; in response to the ratio between the sums of the pitch motor currents of each axis within the predetermined time being greater than the first predetermined threshold, determining that there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time.

[0014] Optionally, the step of determining that there is an abnormality in the pitch bearing of the wind turbine in response to there being a deviation in the sum of the pitch motor currents of each axis within the predetermined time includes: in response to there being a deviation in the sum of the pitch motor currents of each axis within the predetermined time, determining whether the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates; in response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, determining that there is an abnormality in the pitch bearing of the wind turbine.

[0015] Optionally, calculate the variance of the pitch motor current of the axis with the largest sum of pitch motor currents, and in response to the calculated variance being greater than a second predetermined threshold, determine that the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates.

[0016] Optionally, the step of determining that there is an abnormality in the pitch bearing of the wind turbine further includes: in response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, determining that there is an abnormality in the pitch bearing corresponding to the axis with the largest sum of pitch motor currents.

[0017] In another general aspect, there is provided an abnormal detection device for a pitch bearing of a wind turbine, the abnormal detection device for the pitch bearing includes: a data acquisition unit configured to acquire the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each axis of the wind turbine; a consistency determination unit configured to determine whether the pitch speeds and pitch angles of each axis are consistent; an abnormality determination unit configured to, in response to the pitch speeds and pitch angles of each axis, determine whether there is an abnormality in the pitch bearing of the wind turbine based on the pitch motor voltage and pitch motor current of each axis.

[0018] Optionally, the pitch bearing anomaly detection device further includes an alarm unit configured to output an alarm message indicating an anomaly of the pitch bearing in response to an anomaly of the pitch bearing of the wind turbine.

[0019] Optionally, the anomaly determination unit is configured to: calculate the sum of the pitch motor voltages of each axis within a predetermined time, and calculate the sum of the pitch motor currents of each axis within the predetermined time; determine whether the pitch bearing of the wind turbine is abnormal based on the sum of the pitch motor voltages of each axis and the sum of the pitch motor currents of each axis within the predetermined time.

[0020] Optionally, the anomaly determination unit is configured to: determine whether there is a deviation in the sum of the pitch motor voltages of each axis within the predetermined time; in response to there being a deviation in the sum of the pitch motor voltages of each axis within the predetermined time, determine whether there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time; in response to there being a deviation in the sum of the pitch motor currents of each axis within the predetermined time, determine that the pitch bearing of the wind turbine is abnormal.

[0021] Optionally, the anomaly determination unit is configured to: determine whether the ratio between the sums of the pitch motor currents of each axis within the predetermined time is greater than a first predetermined threshold; in response to the ratio between the sums of the pitch motor currents of each axis within the predetermined time being greater than the first predetermined threshold, determine that there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time.

[0022] Optionally, the anomaly determination unit is configured to: in response to there being a deviation in the sum of the pitch motor currents of each axis within the predetermined time, determine whether the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates; in response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, determine that the pitch bearing of the wind turbine is abnormal.

[0023] Optionally, calculate the variance of the pitch motor current of the axis with the largest sum of pitch motor currents, and in response to the calculated variance being greater than a second predetermined threshold, determine that the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates.

[0024] Optionally, the anomaly determination unit is further configured to: in response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, determine that the pitch bearing corresponding to the axis with the largest sum of pitch motor currents is abnormal.

[0025] In another general aspect, there is provided a computer-readable storage medium storing a computer program, characterized in that when the computer program is executed by a processor, the method for detecting an anomaly of the pitch bearing of a wind turbine as described above is implemented.

[0026] In another general aspect, there is provided a controller including: a processor; and a memory storing a computer program which, when executed by the processor, implements the method for detecting abnormality of a pitch bearing of a wind turbine as described above.

[0027] In another general aspect, there is provided a computer program product including a computer program which, when executed by a processor, implements the method for detecting abnormality of a pitch bearing of a wind turbine as described above.

[0028] The method for detecting abnormality of a pitch bearing of a wind turbine and the device for detecting abnormality of a pitch bearing according to embodiments of the present disclosure can effectively detect abnormalities of the pitch bearing and prevent serious faults from occurring in the wind turbine. In addition, the method for detecting abnormality of a pitch bearing and the device for detecting abnormality of a pitch bearing evaluate the operating condition of the pitch bearing through analysis of the operating data of the pitch system, without the need to install additional hardware, so it is easy to implement and can save costs. In addition, the method for detecting abnormality of a pitch bearing and the device for detecting abnormality of a pitch bearing can be effectively distinguished from situations such as pitch jamming, brake valve wear, speed abnormality, encoder abnormality, etc. through comparison of various data.

[0029] Additional aspects and / or advantages of the general concept of the present disclosure will be partially set forth in the following description, and in part will be obvious from the description, or may be learned through the implementation of the general concept of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Through the following description with reference to the drawings showing embodiments, the above and other objects and features of the embodiments of the present disclosure will become clearer, where:

[0031] Figure 1 A current curve graph of a pitch motor when a pitch bearing is abnormal is shown;

[0032] Figure 2 A voltage curve graph of a pitch motor when a pitch bearing is abnormal is shown;

[0033] Figure 3 A blade pitch angle curve graph when a pitch bearing is abnormal is shown;

[0034] Figure 4 is a flowchart showing a method for detecting abnormality of a pitch bearing of a wind turbine according to an embodiment of the present disclosure;

[0035] Figure 5 shows Figure 4 a flowchart of step S403 in

[0036] Figure 6 is a block diagram showing a device for detecting abnormality of a pitch bearing of a wind turbine according to an embodiment of the present disclosure;

[0037] Figure 7 is a block diagram showing a controller of a wind turbine according to an embodiment of the present disclosure. Detailed implementation manners

[0038] The following detailed implementation manners are provided to help the reader obtain a comprehensive understanding of the methods, devices, and / or systems described herein. However, after understanding the disclosure of the present application, various changes, modifications, and equivalents of the methods, devices, and / or systems described herein will be clear. For example, the order of operations described herein is merely an example and is not limited to those set forth herein. Rather, it may be changed as will be clear after understanding the disclosure of the present application, except for operations that must occur in a specific order. In addition, descriptions of features known in the art may be omitted for greater clarity and conciseness.

[0039] The features described herein may be implemented in different forms and should not be construed as limited to the examples described herein. On the contrary, the examples described herein are provided only to illustrate some of the many feasible ways of implementing the methods, devices, and / or systems described herein, which will be clear after understanding the disclosure of the present application.

[0040] As used herein, the term "and / or" includes any one of the associated listed items and any combination of any two or more.

[0041] Although terms such as "first", "second", and "third" may be used herein to describe various members, components, regions, layers, or parts, these members, components, regions, layers, or parts should not be limited by these terms. On the contrary, these terms are only used to distinguish one member, component, region, layer, or part from another. Thus, the first member, first component, first region, first layer, or first part referred to in the examples described herein may also be referred to as the second member, second component, second region, second layer, or second part without departing from the teachings of the examples.

[0042] In the specification, when an element (such as a layer, region, or substrate) is described as "on" another element, "connected to" or "coupled to" another element, the element may be directly "on" another element, directly "connected to" or "coupled to" another element, or there may be one or more other elements therebetween. On the contrary, when an element is described as "directly on" another element, "directly connected to" or "directly coupled to" another element, there may be no other elements therebetween.

[0043] The terms used herein are for describing various examples only and are not intended to limit the disclosure. Unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. The terms "comprising", "including" and "having" specify the presence of the described features, quantities, operations, components, elements and / or combinations thereof, but do not preclude the presence or addition of one or more other features, quantities, operations, components, elements and / or combinations thereof.

[0044] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains after understanding this disclosure. Unless explicitly defined herein, terms (such as those defined in a general dictionary) shall be construed to have a meaning consistent with their meaning in the context of the relevant art and this disclosure, and shall not be interpreted in an idealized or overly formal manner.

[0045] In addition, in the description of the examples, when it is considered that a detailed description of related structures or functions that are well-known will cause a blurred interpretation of this disclosure, such detailed descriptions will be omitted.

[0046] The following specifically explains the principles of the pitch bearing anomaly detection method and the pitch bearing anomaly detection device for a wind turbine according to the embodiments of this disclosure.

[0047] Figure 1 Shows the pitch motor current curve when the pitch bearing is abnormal. In Figure 1 , the abscissa represents the time value, and the 0 time represents the time when the wind turbine triggers a fault shutdown. The ordinate represents the current value of the pitch motor. Curve 11 represents the operation data of axis 1 of the pitch system of the wind turbine (i.e., the current value of the pitch motor), curve 12 represents the operation data of axis 2 of the pitch system, and curve 13 represents the operation data of axis 3 of the pitch system, where an anomaly occurs in axis 2 of the pitch system.

[0048] From Figure 1 , it can be seen that the current values of axis 1 and axis 3 are basically equivalent, while the current value of axis 2 is much higher than those of axis 1 and axis 3 and fluctuates greatly. The reason is that due to the ball structure of the pitch bearing, when the pitch bearing is abnormal, it has an intermittent impact on the pitch motor current. For the pitch driver, the principle is that as the load continuously increases, it acts on the pitch motor flux, that is, the armature reaction. In this case, the input current will also increase to offset the reaction caused by the load and keep the total flux basically unchanged. When the pitch bearing is abnormal, during the rotation of the blade, the load of the pitch bearing will be large or small, so it will cause current change characteristics as shown in Figure 1 .

[0049] Figure 2Shows the pitch motor voltage curve when the pitch bearing is abnormal. At Figure 2 , the abscissa represents the time value, and the 0 time represents the time when the wind turbine triggers a fault shutdown. The ordinate represents the voltage value of the pitch motor. Curve 21 represents the operating data of shaft 1 of the pitch system of the wind turbine (i.e., the voltage value of the pitch motor), curve 22 represents the operating data of shaft 2 of the pitch system, and curve 23 represents the operating data of shaft 3 of the pitch system. Among them, an abnormality occurs in shaft 2 of the pitch system.

[0050] From Figure 2 , it can be seen that the voltage values of shaft 1 and shaft 3 are basically the same, while the voltage value of shaft 2 is slightly higher than that of shaft 1 and shaft 3. The reason is that: due to the increased resistance of the blade during the pitch adjustment process, the magnetic flux of the pitch drive will change, resulting in an increase in the pitch voltage, but the increase amplitude is small. For the pitch drive, the relationship between the output voltage and the magnetic flux change rate is: U = 4.44fwΦ (where U represents the pitch motor voltage, f represents the operating frequency of the pitch motor, w represents the number of turns of the pitch motor coil, and Φ represents the magnetic flux of the pitch motor). The higher the magnetic flux change rate, the greater the electromotive force, that is, the greater the voltage. In Figure 1 , due to the large amplitude and high frequency of the current fluctuation, the magnetic flux change rate will increase, resulting in an increase in the pitch motor voltage.

[0051] Figure 3 Shows the blade pitch angle curve when the pitch bearing is abnormal. At Figure 3 , the abscissa represents the time value, and the 0 time represents the time when the wind turbine triggers a fault shutdown. The ordinate represents the blade pitch angle. Curves 31, 32, and 33 represent the operating data of the pitch system shaft of the wind turbine (i.e., the pitch angles of each blade). Among them, an abnormality occurs in shaft 2 of the pitch system.

[0052] From Figure 3 , it can be seen that the blade pitch angles of shaft 1, shaft 2, and shaft 3 are exactly the same, and the actual pitch speeds are also exactly the same. The reason is that: during the feathering process of the blade, the electrical components, encoders, brake relays, brake valves, and drivers of the three shafts are in normal states, so the actual execution speeds of the drivers are exactly the same. In addition, since there is no resistance on the motor side, the rotational torque acting on the pitch bearing is relatively large, and this torque value can overcome the resistance generated by the pitch bearing abnormality, so the blade does not show a stuck or paused phenomenon, that is, the abnormality of the pitch bearing will not have an obvious impact on the pitch speed of the blade.

[0053] The following further explains the principles of the pitch bearing abnormality detection method and the pitch bearing abnormality detection device for a wind turbine according to an embodiment of the present disclosure.

[0054] Since the impeller of the wind turbine rotates periodically, and under normal circumstances, the pitch angles of the three blades are the same and the change speeds are the same, the sum of the currents of the three pitch motors respectively (i.e., the sum of the currents of the pitch motors within a predetermined time) is consistent under normal circumstances. Further, at each azimuth angle position of the impeller, due to different positions, the gravitational forces on the three blades are different, and their current values are different. However, since each blade experiences a rotation process of 0 to 360 degrees, the total currents of the three pitch motors respectively are the same over a long period of time.

[0055] The operating formula of the motor is M = F×D = C×Φ×I×D, where M is the pitch motor torque, D is the pitch motor rotation radius, F is the electromagnetic force, C is the motor constant, Φ is the magnetic flux of the pitch motor, and I is the pitch motor current. When the pitch motor operates normally, Φ can be regarded as a constant. Therefore, M = Ca×I, where Ca = C×Φ×D. According to the above formula, it can be determined that the torque of the pitch motor is proportional to the current.

[0056] The torque formula of the motor is M = 9550p / n, where p is the power of the pitch motor and n is the rotational speed of the pitch motor. The power formula of the motor is where U is the pitch motor voltage and I is the pitch motor current, is the power factor of the pitch motor. According to the operating formula, torque formula, and power formula of the motor, it can be obtained that: It can be seen therefrom that the rotational speed of the pitch motor is proportional to the pitch motor voltage.

[0057] However, as described above, for the pitch driver, the relationship between the output voltage and the magnetic flux change rate is: U = 4.44fwΦ, that is, the higher the magnetic flux change rate, the greater the electromotive force, that is, the higher the voltage. Therefore, when an abnormality occurs in the pitch bearing, since the current fluctuation amplitude is very large and the fluctuation frequency is very high, the magnetic flux change rate of the driver will increase, resulting in an increase in the pitch motor voltage.

[0058] Therefore, according to the pitch bearing abnormality detection method and pitch bearing abnormality detection device of the wind turbine according to the embodiments of the present disclosure, during continuous operation of the pitch system, the pitch speed is detected, and the three-axis pitch speeds are compared. If the sum of the three-axis pitch speeds is consistent, and the pitch motor voltage sum and current sum of a certain axis are on the high side, and the pitch motor current shows a large amplitude of pulsation, it is determined that an abnormality has occurred in the pitch bearing.

[0059] The following will refer to Figures 4 to 6 A detailed description will be given to the pitch bearing abnormality detection method and pitch bearing abnormality detection device of the wind turbine according to the embodiments of the present disclosure.

[0060] Figure 4It is a flowchart showing a method for detecting abnormalities in a pitch bearing of a wind turbine according to an embodiment of the present disclosure.

[0061] The method for detecting abnormalities in the pitch bearing of a wind turbine according to an embodiment of the present disclosure can be run in the main controller of the wind turbine. However, the present disclosure is not limited thereto, and the method for detecting abnormalities in the pitch bearing of the wind turbine can also be run in each pitch controller of the wind turbine or in other controllers or dedicated processors of the wind turbine. Optionally, the method for detecting abnormalities in the pitch bearing of the wind turbine can also be run in the controller of the wind farm or in any other controller capable of communicating with the wind turbine.

[0062] Refer to Figure 4 , in step S401, obtain the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each axis of the wind turbine. Here, the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each axis of the wind turbine can be obtained by various methods, and the present disclosure does not limit this.

[0063] Next, in step S402, determine whether the pitch speeds and pitch angles of each axis are consistent. For example, it can be determined whether the average values of the pitch speeds of each axis within a period of time are consistent. Here, when the difference between the pitch speeds of each axis is less than a preset speed threshold and the difference between the pitch angles of each axis is less than a preset angle threshold, it can be determined that the pitch speeds and pitch angles of each axis are consistent. Specifically, for all axes, compare the pitch speeds and pitch angles axis by axis in pairs, so as to determine whether the pitch speeds and pitch angles of each axis are consistent. Here, the speed threshold and the angle threshold can be set by those skilled in the art according to actual needs. For example, the speed threshold can be 0.5 degrees / second, and the angle threshold can be 2 degrees, but it is not limited thereto.

[0064] By determining whether the pitch speeds and pitch angles of each axis are consistent, situations such as mechanical jamming on the motor side, abnormal brake valves, and abnormal encoders can be excluded.

[0065] In step S403, in response to the pitch speeds and pitch angles of each axis being consistent, based on the pitch motor voltage and pitch motor current of each axis, determine whether there is an abnormality in the pitch bearing of the wind turbine. However, if the pitch speeds and pitch angles of each axis are inconsistent, it indicates that there are situations such as mechanical jamming, abnormal brake valves, and abnormal encoders. Therefore, the method for detecting abnormalities in the pitch bearing of the wind turbine according to the embodiment of the present disclosure can be exited for other corresponding processing.

[0066] Specifically, in step S403, the sum of the pitch motor voltages of each axis within a predetermined time T can be calculated first, and the sum of the pitch motor currents of each axis within the predetermined time T can be calculated. Then, based on the sum of the pitch motor voltages of each axis and the sum of the pitch motor currents of each axis within the predetermined time T, it is determined whether there is an abnormality in the pitch bearing of the wind turbine. Here, the length of the predetermined time T can be, for example but not limited to, 30 seconds. The sum of the pitch motor voltages / sum of the pitch motor currents of each axis within the predetermined time T can be the sum of the pitch motor voltages / pitch motor currents obtained at each sampling point within the predetermined time T. The following refers to Figure 5 Specifically describe the steps of determining whether there is an abnormality in the pitch bearing of the wind turbine based on the sum of the pitch motor voltages of each axis and the sum of the pitch motor currents of each axis within the predetermined time T.

[0067] Figure 5 It shows Figure 4 The flowchart of step S403 in

[0068] Referring to Figure 5 , in step S501, it is determined whether there is a deviation in the sum of the pitch motor voltages of each axis within the predetermined time T. Here, it can be determined whether the ratio between the sums of the pitch motor voltages of each axis within the predetermined time T is greater than a preset threshold (for example but not limited to 1.1), and in response to the ratio between the sums of the pitch motor voltages of each axis within the predetermined time T being greater than the preset threshold, it is determined that there is a deviation in the sum of the pitch motor voltages of each axis within the predetermined time T. As described above, for all axes, the sums of the pitch motor voltages can be compared pairwise to determine whether there is a deviation in the sum of the pitch motor voltages of each axis. If there is a deviation in the sum of the pitch motor voltages of each axis, it indicates that the magnetic fluxes of each axis are inconsistent.

[0069] Next, in step S502, in response to there being a deviation in the sum of the pitch motor voltages of each axis within the predetermined time T, it is determined whether there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time T. Here, it can be determined whether the ratio between the sums of the pitch motor currents of each axis within the predetermined time T is greater than a first predetermined threshold (for example but not limited to 3), and in response to the ratio between the sums of the pitch motor currents of each axis within the predetermined time T being greater than the first predetermined threshold, it is determined that there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time T. As described above, for all axes, the sums of the pitch motor currents can be compared pairwise to determine whether there is a deviation in the sum of the pitch motor currents of each axis.

[0070] On the other hand, if there is no deviation in the sum of the pitch motor voltages of each axis within the predetermined time T, it indicates that the magnetic fluxes of each axis are consistent, so the pitch bearing abnormality detection method for the wind turbine according to the embodiments of the present disclosure can be exited.

[0071] In step S503, in response to a deviation in the sum of the pitch motor currents of each axis within a predetermined time T, it is determined that an abnormality has occurred in the pitch bearing of the wind turbine. Specifically, in response to a deviation in the sum of the pitch motor currents of each axis within a predetermined time T, it is possible to determine whether the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates, and in response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, it is determined that an abnormality has occurred in the pitch bearing of the wind turbine. Here, the variance of the pitch motor current of the axis with the largest sum of pitch motor currents can be calculated, and when the calculated variance is greater than a second predetermined threshold, it is determined that the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates. For example, the pitch motor current can be sampled within a preset time (such as but not limited to 1 second), and the variance of the pitch motor current can be calculated. When the calculated variance is greater than a second predetermined threshold (such as but not limited to 1000), it can be determined that the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates. In addition, in response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, it can be determined that an abnormality has occurred in the pitch bearing corresponding to the axis with the largest sum of pitch motor currents.

[0072] On the other hand, if there is no deviation in the sum of the pitch motor currents of each axis within the predetermined time T, it indicates that there is no abnormality in the pitch bearing, so the pitch bearing abnormality detection method of the wind turbine according to the embodiments of the present disclosure can be exited.

[0073] Optionally, the pitch bearing abnormality detection method of the wind turbine according to the embodiments of the present disclosure may further include the following steps (not shown): in response to an abnormality occurring in the pitch bearing of the wind turbine, an alarm message indicating the pitch bearing abnormality is output. For example, an alarm message indicating the pitch bearing abnormality can be output externally in the form of sound, light, electricity, vibration, etc. In addition, the alarm message indicating the pitch bearing abnormality can be output to the control center of the wind farm or a site outside the wind farm.

[0074] The pitch bearing abnormality detection method of the wind turbine according to the embodiments of the present disclosure can effectively detect pitch bearing abnormalities and prevent serious failures from occurring in the wind turbine. In addition, the pitch bearing abnormality detection method evaluates the operating condition of the pitch bearing through the analysis of the operating data of the pitch system, without the need to install additional hardware, so it is easy to implement and can save costs. In addition, the pitch bearing abnormality detection method can effectively distinguish from situations such as pitch jamming, brake valve wear, speed abnormality, encoder abnormality, etc. through multiple data comparisons.

[0075] Figure 6FIG. is a block diagram showing a pitch bearing abnormality detection device for a wind turbine according to an embodiment of the present disclosure. The pitch bearing abnormality detection device for a wind turbine according to an embodiment of the present disclosure may be provided in the main controller of the wind turbine, in each pitch controller, or in other dedicated processors, or may be implemented as a dedicated device in the wind turbine.

[0076] Referring to Figure 6 , the pitch bearing abnormality detection device 600 of the wind turbine may include a data acquisition unit 610, a consistency determination unit 620, and an abnormality determination unit 630. The data acquisition unit 610 may acquire the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each axis of the wind turbine. The consistency determination unit 620 may determine whether the pitch speeds and pitch angles of each axis are consistent. The abnormality determination unit 630 may, in response to the pitch speeds and pitch angles of each axis being consistent, determine whether an abnormality has occurred in the pitch bearing of the wind turbine based on the pitch motor voltage and pitch motor current of each axis. Optionally, the pitch bearing abnormality detection device 600 may further include an alarm unit (not shown). The alarm unit may output an alarm message indicating an abnormality of the pitch bearing in response to an abnormality occurring in the pitch bearing of the wind turbine.

[0077] Specifically, the abnormality determination unit 630 may first calculate the sum of the pitch motor voltages of each axis within a predetermined time, and calculate the sum of the pitch motor currents of each axis within a predetermined time, and then determine whether an abnormality has occurred in the pitch bearing of the wind turbine based on the sum of the pitch motor voltages of each axis within the predetermined time and the sum of the pitch motor currents of each axis within the predetermined time.

[0078] Furthermore, the abnormality determination unit 630 may determine whether there is a deviation in the sum of the pitch motor voltages of each axis within a predetermined time. In response to the sum of the pitch motor voltages of each axis within the predetermined time having a deviation, the abnormality determination unit 630 may determine whether there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time. In response to the sum of the pitch motor currents of each axis within the predetermined time having a deviation, the abnormality determination unit 630 may determine that there is an abnormality in the pitch bearing of the wind turbine. According to an embodiment of the present disclosure, the abnormality determination unit 630 may determine whether the ratio between the sums of the pitch motor currents of each axis within the predetermined time is greater than a first predetermined threshold. In response to the ratio between the sums of the pitch motor currents of each axis within the predetermined time being greater than the first predetermined threshold, the abnormality determination unit 630 may determine that there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time. In response to the sum of the pitch motor currents of each axis within the predetermined time having a deviation, the abnormality determination unit 630 may determine whether the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates. In response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, the abnormality determination unit 630 may determine that there is an abnormality in the pitch bearing of the wind turbine. Here, the abnormality determination unit 630 may calculate the variance of the pitch motor current of the axis with the largest sum of pitch motor currents, and in response to the calculated variance being greater than a second predetermined threshold, determine that the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates. Alternatively, in response to the pitch motor current of the axis with the largest sum of pitch motor currents fluctuating, the abnormality determination unit 630 may determine that there is an abnormality in the pitch bearing corresponding to the axis with the largest sum of pitch motor currents.

[0079] Figure 7 is a block diagram showing a controller of a wind turbine according to an embodiment of the present disclosure.

[0080] Referring to Figure 7 , the controller 700 of the wind turbine according to an embodiment of the present disclosure may be, but is not limited to, the main controller of the wind turbine. For example, the controller 700 of the wind turbine according to an embodiment of the present disclosure may be a controller of a wind farm, or a dedicated controller provided in the wind turbine. The controller 700 of the wind turbine according to an embodiment of the present disclosure may include a processor 710 and a memory 720. The processor 710 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 chip (SoC), a microprocessor, an application specific integrated circuit (ASIC), etc. The memory 720 stores a computer program to be executed by the processor 710. The memory 720 includes a high-speed random access memory and / or a non-volatile computer-readable storage medium. When the processor 710 executes the computer program stored in the memory 720, the pitch bearing abnormality detection method of the wind turbine as described above may be implemented.

[0081] Optionally, the controller 700 can communicate with other components in the wind turbine in a wired / wireless communication manner, and can also communicate with other devices in the wind farm in a wired / wireless communication manner. In addition, the controller 700 can communicate with devices outside the wind farm in a wired / wireless communication manner.

[0082] The pitch bearing abnormality detection method for a wind turbine according to an embodiment of the present disclosure can be written as a computer program and stored on a computer-readable storage medium. When the computer program is executed by a processor, the pitch bearing abnormality detection method for the wind turbine 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 memory, hard disk drive (HDD), solid state drive (SSD), cartridge memory (such as, multimedia card, secure digital (SD) card or extreme digital (XD) card), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk, and any other device configured to store the computer program and any associated data, data files, and data structures in a non-transitory manner and provide the computer program and any associated data, data files, and data structures to a processor or computer such 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 by one or more processors or computers.

[0083] On the other hand, the pitch bearing abnormality detection method for a wind turbine according to an embodiment of the present disclosure can be implemented as a computer program product including a computer program, and when the computer program is executed by a processor, the pitch bearing abnormality detection method for the wind turbine as described above is implemented.

[0084] The pitch bearing anomaly detection method and pitch bearing anomaly detection device of a wind turbine according to an embodiment of the present disclosure can effectively detect pitch bearing anomalies and prevent serious failures from occurring in the wind turbine. In addition, the pitch bearing anomaly detection method and pitch bearing anomaly detection device evaluate the operating conditions of the pitch bearing by analyzing the operating data of the pitch system, without the need to install additional hardware, so it is easy to implement and can save costs. In addition, the pitch bearing anomaly detection method and pitch bearing anomaly detection device can be effectively distinguished from situations such as pitch jamming, brake valve wear, speed anomalies, encoder anomalies, etc. through multiple data comparisons.

[0085] Although some embodiments of the present disclosure have been shown and described, those skilled in the art should understand that these embodiments can be modified without departing from the principles and spirit of the present disclosure as defined by the claims and their equivalents.

Claims

1. A method for detecting abnormalities in a pitch bearing of a wind turbine, characterized in that, the method for detecting abnormalities in the pitch bearing includes: Obtain the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each axis of the wind turbine; Determine whether the pitch speeds and pitch angles of each axis are consistent; In response to the pitch speeds and pitch angles of each axis being consistent, based on the pitch motor voltage and pitch motor current of each axis, determine whether there is an abnormality in the pitch bearing of the wind turbine, wherein, the step of determining whether there is an abnormality in the pitch bearing of the wind turbine based on the pitch motor voltage and pitch motor current of each axis includes: Calculate the sum of the pitch motor voltages of each axis within a predetermined time, and calculate the sum of the pitch motor currents of each axis within the predetermined time; Based on the sum of the pitch motor voltages of each axis and the sum of the pitch motor currents of each axis within the predetermined time, determine whether there is an abnormality in the pitch bearing of the wind turbine.

2. The method for detecting abnormalities in a pitch bearing according to claim 1, characterized in that, the method for detecting abnormalities in the pitch bearing further includes: In response to an abnormality in the pitch bearing of the wind turbine, output an alarm message indicating the abnormality of the pitch bearing.

3. The method for detecting abnormalities in a pitch bearing according to claim 1, characterized in that, the method for detecting abnormalities in the pitch bearing further includes: In response to the pitch speeds and pitch angles of each axis being inconsistent, determine that at least one of mechanical jamming, brake valve abnormality, pitch speed abnormality, and encoder abnormality occurs in the wind turbine.

4. The method for detecting abnormalities in a pitch bearing according to claim 1, characterized in that, the step of determining whether there is an abnormality in the pitch bearing of the wind turbine based on the sum of the pitch motor voltages of each axis and the sum of the pitch motor currents of each axis within the predetermined time includes: Determine whether there is a deviation in the sum of the pitch motor voltages of each axis within the predetermined time; In response to a deviation in the sum of the pitch motor voltages of each axis within the predetermined time, determine whether there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time; In response to a deviation in the sum of the pitch motor currents of each axis within the predetermined time, determine that there is an abnormality in the pitch bearing of the wind turbine.

5. The method for detecting abnormalities in a pitch bearing according to claim 4, characterized in that, the step of determining whether there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time includes: Determine whether the ratio between the sums of the pitch motor currents of each axis within the predetermined time is greater than a first predetermined threshold; In response to the ratio between the sums of the pitch motor currents of each axis within the predetermined time being greater than the first predetermined threshold, determine that there is a deviation in the sum of the pitch motor currents of each axis within the predetermined time.

6. The method for detecting abnormalities in a pitch bearing according to claim 4, characterized in that, the step of determining that there is an abnormality in the pitch bearing of the wind turbine in response to a deviation in the sum of the pitch motor currents of each axis within the predetermined time includes: In response to a deviation in the sum of the pitch motor currents of each axis within the predetermined time, determine whether the pitch motor current of the axis with the largest sum of pitch motor currents fluctuates; In response to the pitch motor current fluctuation of the axis with the largest sum of pitch motor currents, it is determined that the pitch bearing of the wind turbine is abnormal.

7. The pitch bearing abnormality detection method according to claim 6, wherein, calculate the variance of the pitch motor current of the axis with the largest sum of pitch motor currents, and in response to the calculated variance being greater than a second predetermined threshold, determine the pitch motor current fluctuation of the axis with the largest sum of pitch motor currents.

8. The pitch bearing abnormality detection method according to claim 6, wherein, the step of determining that the pitch bearing of the wind turbine is abnormal further includes: in response to the pitch motor current fluctuation of the axis with the largest sum of pitch motor currents, determine that the pitch bearing corresponding to the axis with the largest sum of pitch motor currents is abnormal.

9. A pitch bearing abnormality detection device for a wind turbine, wherein, the pitch bearing abnormality detection device includes: a data acquisition unit configured to acquire the pitch speed, pitch angle, pitch motor voltage, and pitch motor current of each axis of the wind turbine; a consistency determination unit configured to determine whether the pitch speeds and pitch angles of each axis are consistent; an abnormality determination unit configured to, in response to the pitch speeds and pitch angles of each axis being consistent, determine whether the pitch bearing of the wind turbine is abnormal based on the pitch motor voltage and pitch motor current of each axis, wherein the abnormality determination unit is configured to: calculate the sum of the pitch motor voltages of each axis within a predetermined time, and calculate the sum of the pitch motor currents of each axis within the predetermined time; determine whether the pitch bearing of the wind turbine is abnormal based on the sum of the pitch motor voltages of each axis within the predetermined time and the sum of the pitch motor currents of each axis within the predetermined time.

10. A computer-readable storage medium storing a computer program, wherein, when the computer program is executed by a processor, the pitch bearing abnormality detection method for a wind turbine according to any one of claims 1 to 8 is implemented.

11. A controller, wherein, the controller includes: a processor; and a memory storing a computer program, when the computer program is executed by the processor, the pitch bearing abnormality detection method for a wind turbine according to any one of claims 1 to 8 is implemented.

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