Wind turbine generator fault monitoring system and method

Abstract

The present invention relates to the technical field of wind turbine generator fault monitoring, and specifically relates to a wind turbine generator fault monitoring system and method. The system comprises: a collection module, configured to perform data collection on a wind turbine generator; a simulation module, configured to simulate a fault of the wind turbine generator to generate a data threshold for fault determination; a monitoring module, configured to, on the basis of the operation data of the wind turbine generator and the data threshold, identify the fault of the wind turbine generator to generate a fault alarm; and a processing module, configured to perform fault processing on the wind turbine generator on the basis of the fault alarm. The fault type is quickly determined by using input data of a simulation model, thereby greatly shortening the time for fault detection.

Description

A wind turbine fault monitoring system and method Technical Field

[0001] This invention relates to the field of wind turbine fault monitoring technology, and more specifically to a wind turbine fault monitoring system and method. Background Technology

[0002] A wind power generation system consists of a wind turbine generator set, a tower supporting the generator set, a battery charging controller, an inverter, a load unloader, a grid connection controller, and a battery bank.

[0003] Due to the large size of the equipment, maintenance is relatively difficult. Therefore, whenever a wind turbine needs maintenance, a long period of fault detection is required to determine the location of the fault and select an appropriate maintenance method. This results in time-consuming and labor-intensive maintenance, which also affects the normal operation of the equipment. Therefore, this invention proposes a wind turbine fault monitoring system and method. Summary of the Invention

[0004] In view of this, the present invention provides a wind turbine fault monitoring system and method.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] Preferably, the wind turbine fault monitoring system described above includes:

[0007] The data acquisition module is used to acquire data from the wind turbine.

[0008] The simulation module is used to simulate faults in wind turbine units and generate data thresholds for fault judgment.

[0009] The monitoring module identifies faults in the wind turbine based on its operating data and the data thresholds, and generates fault alarms.

[0010] The processing module performs fault handling on the wind turbine unit based on the fault alarm.

[0011] Preferably, in the above-mentioned wind turbine fault monitoring system, the acquisition module includes:

[0012] Temperature unit, equipped with temperature sensors to collect temperature data of various components inside the wind turbine;

[0013] The noise unit has noise sensors installed inside and outside the wind turbine gearbox to collect noise data from the gearbox.

[0014] The camera unit is configured with cameras installed diagonally on the bolts of each wind turbine blade, and the infrared beams are adjusted to be aimed at the top of the bolts.

[0015] The voltage and current unit is used to collect the voltage and current values ​​of the wind turbine during operation.

[0016] Preferably, in the above-mentioned wind turbine fault monitoring system, the simulation module includes:

[0017] Model unit, used to build a simulation model of the wind turbine;

[0018] The temperature simulation unit, based on the simulation model, uses the temperature values ​​of each component of the model wind turbine when a fault occurs as the corresponding temperature thresholds for each component of the wind turbine.

[0019] The noise simulation unit, based on the simulation model, simulates the noise data inside and outside the wind turbine gearbox when the internal oil is completely consumed, and uses it as the noise threshold of the wind turbine gearbox.

[0020] Preferably, in the above-mentioned wind turbine fault monitoring system, the monitoring module includes:

[0021] The temperature monitoring unit acquires the real-time temperature of each component of the wind turbine and compares it with the corresponding temperature threshold. When the deviation between the real-time temperature and the temperature threshold exceeds the preset temperature deviation range, a temperature alarm is generated.

[0022] The noise monitoring unit acquires the real-time noise of the wind turbine gearbox and compares it with the noise threshold. When the deviation between the real-time noise and the noise threshold exceeds the preset noise deviation range, a gearbox alarm is generated.

[0023] The loosening monitoring unit acquires image data from the camera unit. When the difference between the infrared rays in the image data and the horizontal plane exceeds a preset difference threshold, a bolt loosening alarm is generated.

[0024] The power monitoring unit acquires the voltage and current data of the wind turbine. When the voltage and current values ​​are 0, a power alarm is generated.

[0025] Preferably, in the above-mentioned wind turbine fault monitoring system, the processing module includes:

[0026] The fault simulation unit generates fault alarm information, inputs the data information at the time of the fault occurrence into the simulation model to simulate the fault. If the same fault occurs, the fault alarm information is confirmed; if the same fault does not occur, the fault alarm information is canceled, and the three sets of data with the shortest interval time are obtained, the data are averaged, and the fault is re-judged.

[0027] The backup power unit is used to activate the backup power supply to ensure the normal operation of the wind turbine when the wind turbine generates a power alarm.

[0028] The auxiliary cooling unit is used to activate the cooling device to lower the temperature when the wind turbine generates a temperature alarm.

[0029] Based on the aforementioned wind turbine fault monitoring system, a preferred wind turbine fault monitoring method includes:

[0030] S1, data acquisition for wind turbine units;

[0031] S2, simulates faults in wind turbine units and generates data thresholds for fault judgment;

[0032] S3, Based on the operating data of the wind turbine and the data threshold, identify the faults of the wind turbine and generate a fault alarm;

[0033] S4, Perform fault handling on the wind turbine unit based on the fault alarm.

[0034] A preferred method for monitoring wind turbine faults includes the following steps in step S1:

[0035] S11. Set up temperature sensors to collect temperature data of various components inside the wind turbine.

[0036] S12. Noise sensors are installed inside and outside the wind turbine gearbox to collect noise data from the gearbox.

[0037] S13. Install the camera at the diagonal of the blade bolts of each wind turbine generator set, and adjust the infrared beam to be aimed at the top of the blade bolts.

[0038] S14. Collect the voltage and current values ​​of the wind turbine during operation.

[0039] A preferred method for monitoring wind turbine faults, step S2 is as follows:

[0040] S21. Establish a simulation model of the wind turbine unit;

[0041] S22. Based on the simulation model, the temperature values ​​of each component of the model wind turbine when a fault occurs are used as the corresponding temperature thresholds of each component of the wind turbine.

[0042] S23. Based on the simulation model, simulate the noise data inside and outside the wind turbine gearbox when the internal oil is completely consumed, and use it as the noise threshold of the wind turbine gearbox.

[0043] A preferred method for monitoring wind turbine faults, step S3 is as follows:

[0044] S31. Obtain the real-time temperature of each component of the wind turbine and compare it with the corresponding temperature threshold. When the deviation between the real-time temperature and the temperature threshold exceeds the preset temperature deviation range, generate a temperature alarm.

[0045] S32. Obtain the real-time noise of the wind turbine gearbox and compare it with the noise threshold. When the deviation between the real-time noise and the noise threshold exceeds the preset noise deviation range, generate a gearbox alarm.

[0046] S33. Obtain image data from the camera unit. When the difference between the infrared rays and the horizontal plane in the image data exceeds a preset difference threshold, generate a bolt loosening alarm.

[0047] S34. Obtain the voltage and current data of the wind turbine. When the voltage and current values ​​are 0, generate a power alarm.

[0048] A preferred method for monitoring wind turbine faults, step S4 is as follows:

[0049] S41. After generating the fault alarm information, input the data information at the time of the fault occurrence into the simulation model to simulate the fault. If the same fault occurs, confirm the fault alarm information; if the same fault does not occur, cancel the fault alarm information, obtain the three sets of data with the shortest interval time, perform average processing on the data, and re-judge the fault.

[0050] S42. If the fault alarm information is a power alarm, start the backup power supply to ensure the normal operation of the wind turbine; and record the operating data of the wind turbine within a preset time period, and simulate the fault through the simulation model. If no fault information appears, confirm the power alarm.

[0051] S43. If the fault alarm information is a temperature alarm, start the cooling device to cool down, record the operating data of the wind turbine unit within a preset time period, and simulate the fault through the simulation model. If no fault information appears, confirm the temperature alarm.

[0052] As can be seen from the above technical solution, compared with the prior art, the beneficial effects of the present invention are as follows:

[0053] 1. This invention collects safety data of wind turbines through simulation models and historical data. By using the input data from the simulation model, the type of fault can be quickly determined, thereby greatly reducing the fault detection time. At the same time, it can issue a signal at the first moment of the fault and indicate the type of fault. Furthermore, this invention also simulates and confirms the fault information to ensure the accuracy of the fault information and avoid misjudgment due to system errors, which would result in the loss of human and material resources. The design of the backup power supply can greatly ensure the normal operation of the wind turbine and ensure that it can continue to work using the backup power supply in the event of a power failure. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0055] Figure 1 is a functional schematic diagram of the system of the present invention.

[0056] Figure 2 is a schematic flowchart of the method of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] In this invention, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance; the term "multiple" refers to two or more unless otherwise explicitly defined. The terms "install," "connect," "link," and "fix" should be interpreted broadly. For example, "connect" can be a fixed connection, a detachable connection, or an integral connection; "link" can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0059] In the description of this invention, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or unit referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0060] In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0061] Example 1

[0062] This invention discloses a wind turbine fault monitoring system, comprising:

[0063] The data acquisition module is used to acquire data from the wind turbine.

[0064] This includes a temperature unit, which uses temperature sensors to collect temperature data from various components inside the wind turbine.

[0065] The noise unit has noise sensors installed inside and outside the wind turbine gearbox to collect noise data from the gearbox.

[0066] The camera unit is configured with cameras installed diagonally on the bolts of each wind turbine blade, and the infrared beams are adjusted to be aimed at the top of the bolts.

[0067] The voltage and current unit is used to collect the voltage and current values ​​of the wind turbine during operation.

[0068] The temperature sensor, noise sensor, camera, and voltage and current detection technologies mentioned above are all existing technologies. The camera, in particular, has a built-in infrared sensor.

[0069] The simulation module is used to simulate faults in wind turbine units and generate data thresholds for fault judgment.

[0070] This includes model units, used to build simulation models of wind turbine units;

[0071] The temperature simulation unit, based on the simulation model, uses the temperature values ​​of each component of the model wind turbine when a fault occurs as the corresponding temperature thresholds for each component of the wind turbine.

[0072] The noise simulation unit, based on a simulation model, simulates the noise data inside and outside the wind turbine gearbox when the internal oil is completely consumed, and uses this data as the noise threshold for the wind turbine gearbox.

[0073] In the above embodiments, a model is established for the wind turbine generator. By using historical data and other methods, a model can be created for high-temperature faults in wind turbine components and abnormal noise from gearbox gear friction, and threshold values ​​can be generated as a reference for fault judgment.

[0074] The monitoring module identifies faults in the wind turbine based on its operating data and data thresholds, and generates fault alarms.

[0075] This includes a temperature monitoring unit that acquires the real-time temperature of each component of the wind turbine and compares it with the corresponding temperature threshold. When the deviation between the real-time temperature and the temperature threshold exceeds the preset temperature deviation range, a temperature alarm is generated.

[0076] The noise monitoring unit acquires the real-time noise of the wind turbine gearbox and compares it with the noise threshold. When the deviation between the real-time noise and the noise threshold exceeds the preset noise deviation range, a gearbox alarm is generated.

[0077] The loosening monitoring unit acquires image data from the camera unit. When the difference between the infrared rays in the image data and the horizontal plane exceeds a preset difference threshold, a bolt loosening alarm is generated.

[0078] The power monitoring unit acquires the voltage and current data of the wind turbine. When the voltage and current values ​​are 0, a power alarm is generated.

[0079] In the above embodiments, the temperature deviation range is 0.5℃~5℃; the noise deviation range is 20 dB~100 dB; and the threshold value for bolt loosening is 2 cm.

[0080] In the above embodiments, the alarm level is determined by the magnitude of the value exceeding a preset range. The specific process is as follows:

[0081] When determining the level of temperature alarms, the following preset temperature difference values ​​are set: first preset temperature difference V1, second preset temperature difference V2, third preset temperature difference V3, and fourth preset temperature difference V4, where V1 < V2 < V3 < V4; and first alarm level B1, second alarm level B2, third alarm level B3, fourth alarm level B4, and fifth alarm level B5, which are ordered according to their importance: B1 < B2 < B3 < B4 < B5.

[0082] The alarm level for temperature alarms is determined based on the relationship between the magnitude V of the deviation between the real-time temperature and the temperature threshold exceeding the preset temperature deviation range and various preset temperature differences.

[0083] When V < V1, the alarm level of the temperature alarm is determined to be the first alarm level B1;

[0084] When V1≤V<V2, the alarm level of the temperature alarm is determined to be the second alarm level B2;

[0085] When V2≤V<V3, the alarm level for the temperature alarm is determined to be the third alarm level B3;

[0086] When V3≤V<V4, the alarm level for the temperature alarm is determined to be the fourth alarm level B4.

[0087] When V4≤V, the alarm level of the temperature alarm is determined to be the fifth alarm level B5, and the temperature alarm information is directly confirmed.

[0088] When judging the level of transmission alarm, the following preset noise difference values ​​are set: first preset noise difference Q1, second preset noise difference Q2, third preset noise difference Q3, and fourth preset noise difference Q4, where Q1 < Q2 < Q3 < Q4; and first alarm level W1, second alarm level W2, third alarm level W3, fourth alarm level W4, and fifth alarm level W5, which are ordered according to their importance: W1 < W2 < W3 < W4 < W5.

[0089] The alarm level of the transmission alarm is determined based on the relationship between the magnitude Q of the deviation between real-time noise and the noise threshold exceeding the preset noise deviation range and various preset noise differences.

[0090] When Q < Q1, the alarm level of the transmission alarm is determined to be the first alarm level W1;

[0091] When Q1≤Q<Q2, the alarm level of the transmission alarm is determined to be the second alarm level W2;

[0092] When Q2≤Q<Q3, the alarm level of the transmission alarm is determined to be the third alarm level W3;

[0093] When Q3≤Q<Q4, the alarm level of the transmission alarm is determined to be the fourth alarm level W4;

[0094] When Q4≤Q, the alarm level of the transmission alarm is determined to be the fifth alarm level W5, and the transmission alarm information is directly confirmed.

[0095] When determining the level of bolt loosening alarm, the following preset distance differences are set: first preset distance difference A1, second preset distance difference A2, third preset distance difference A3, and fourth preset distance difference A4, where A1 < A2 < A3 < A4; and first alarm level S1, second alarm level S2, third alarm level S3, fourth alarm level S4, and fifth alarm level S5, which are ordered according to their importance: S1 < S2 < S3 < S4 < S5.

[0096] Based on the relationship between the distance difference A between the infrared rays and the horizontal plane in the image data that exceeds a preset difference threshold and various preset distance differences, the alarm level for bolt loosening alarm is determined.

[0097] When A < A1, the alarm level for the loose bolt alarm is determined to be the first alarm level S1;

[0098] When A1≤A<A2, the alarm level for the loose bolt alarm is determined to be the second alarm level S2;

[0099] When A2≤A<A3, the alarm level for the loose bolt alarm is determined to be the third alarm level S3;

[0100] When A3≤A<A4, the alarm level for the loose bolt alarm is determined to be the fourth alarm level S4;

[0101] When A4≤A, the alarm level for the loose bolt alarm is determined to be the fifth alarm level S5, and the loose bolt alarm information is directly confirmed.

[0102] The processing module handles faults in the wind turbine based on fault alarms.

[0103] This includes: a fault simulation unit that generates fault alarm information, inputs the data information at the time of the fault into the simulation model to simulate the fault, confirms the fault alarm information if the same fault occurs, cancels the fault alarm information if the same fault does not occur, and obtains the three sets of data with the shortest interval time, performs average processing on the data, and re-judges the fault.

[0104] The backup power unit is used to activate the backup power supply to ensure the normal operation of the wind turbine when the wind turbine generates a power alarm.

[0105] The auxiliary cooling unit is used to activate the cooling device to lower the temperature when the wind turbine generates a temperature alarm.

[0106] In the above embodiments, the backup power supply and auxiliary cooling device are standard features of wind turbine generators.

[0107] The beneficial effects of the above embodiments are as follows: Simulating fault data ensures the accuracy of fault information and avoids misjudgments due to system errors, thus preventing losses of manpower and resources. When a manageable fault is confirmed, it is addressed first, preventing the wind turbine from shutting down and providing maintenance personnel with more time for repairs.

[0108] Example 2

[0109] Based on the aforementioned wind turbine fault monitoring system, a wind turbine fault monitoring method includes:

[0110] S1, data acquisition for wind turbine units;

[0111] S11. Set up temperature sensors to collect temperature data of various components inside the wind turbine.

[0112] S12. Noise sensors are installed inside and outside the wind turbine gearbox to collect noise data from the gearbox.

[0113] S13. Install the camera at the diagonal of the blade bolts of each wind turbine generator set, and adjust the infrared beam to be aimed at the top of the blade bolts.

[0114] S14. Collect the voltage and current values ​​of the wind turbine during operation.

[0115] S2, simulates faults in wind turbine units and generates data thresholds for fault judgment;

[0116] S21. Establish a simulation model of the wind turbine unit;

[0117] S22. Based on the simulation model, the temperature values ​​of each component of the model wind turbine when a fault occurs are used as the corresponding temperature thresholds for each component of the wind turbine.

[0118] S23. Based on the simulation model, simulate the noise data inside and outside the wind turbine gearbox when the internal oil is exhausted, and use it as the noise threshold of the wind turbine gearbox.

[0119] S3 identifies faults in the wind turbine based on its operating data and data thresholds, and generates fault alarms.

[0120] S31. Obtain the real-time temperature of each component of the wind turbine and compare it with the corresponding temperature threshold. When the deviation between the real-time temperature and the temperature threshold exceeds the preset temperature deviation range, generate a temperature alarm.

[0121] S32. Obtain the real-time noise of the wind turbine gearbox and compare it with the noise threshold. When the deviation between the real-time noise and the noise threshold exceeds the preset noise deviation range, generate a gearbox alarm.

[0122] S33. Acquire image data from the camera unit. When the difference between the infrared rays and the horizontal plane in the image data exceeds the preset difference threshold, generate a bolt loosening alarm.

[0123] S34. Obtain the voltage and current data of the wind turbine. When the voltage and current values ​​are 0, generate a power alarm.

[0124] S4, handle the fault of the wind turbine according to the fault alarm.

[0125] S41. After generating the fault alarm information, input the data information at the time of the fault into the simulation model to simulate the fault. If the same fault occurs, confirm the fault alarm information; if the same fault does not occur, cancel the fault alarm information, obtain the three sets of data with the shortest interval, perform average processing on the data, and re-judge the fault.

[0126] S42. If the fault alarm information is a power alarm, start the backup power supply to ensure the normal operation of the wind turbine; and record the operating data of the wind turbine within a preset time period, and simulate the fault through the simulation model. If no fault information appears, confirm the power alarm.

[0127] S43. If the fault alarm information is a temperature alarm, start the cooling device to cool down, record the operating data of the wind turbine in the next preset time period, and simulate the fault through the simulation model. If no fault information appears, confirm the temperature alarm.

[0128] The working principle of the above embodiments is as follows:

[0129] 1) First, install temperature sensors on various components inside the wind turbine, such as frequency converters and voltage regulators. Distribute noise sensors inside and outside the gearbox. Then, install miniature cameras at the diagonal points of each bolt and adjust the infrared beam to be aligned with the top of the bolt. Connect current and voltage detectors and signal amplifiers in parallel on the circuit. Use the above devices to collect data, classify and process the data, and then upload it to the monitoring system.

[0130] 2) Establish a simulation model of the wind turbine, determine the fault judgment threshold by simulating and training the historical data of the wind turbine, normalize the data, build a model using the normalized data, define the cost function and optimizer, iteratively train the model, and then save the model.

[0131] 3) When wind turbine fault monitoring begins, a set of data is collected every 0.5 hours, including temperature data, noise data, image data, and current and voltage data, and uploaded to the monitoring system. The monitoring system classifies the data and inputs it into the established simulation model. The input values ​​are matched with judgment thresholds or preset thresholds. Specifically, if the temperature data deviation is 0.5℃~5℃, a temperature fault is judged; if the noise data difference is 20dB~100dB, a gearbox fault is judged; if the difference in the horizontal plane of the infrared rays in the image data reaches more than 2cm, a bolt loosening fault is judged; and if the current and voltage detection values ​​are 0, a power supply fault is judged. The fault type of the wind turbine is determined based on the above values.

[0132] 4) When the system determines a fault, it simulates whether the same fault occurs under the same value based on the simulation model. If it does, the fault type is confirmed and the fault signal is uploaded to the maintenance station. If they are different, the three sets of data with the shortest interval are recorded, the average value of the data is processed, and the fault is re-determined.

[0133] 5) At this point, the fault signal is sent to the maintenance station. After receiving the signal, the maintenance personnel will identify the cause of the fault and carry out targeted repairs.

[0134] It should be noted that the above embodiments are merely illustrative examples of the division of functional modules. In practical applications, the functions described above can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be further decomposed or combined. For example, the modules in the above embodiments can be merged into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are merely for distinguishing the various modules or steps and are not considered as an improper limitation of the present invention.

[0135] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent in such process, method, article, or apparatus / device.

[0136] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0137] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims and their equivalents, this invention is also intended to include these modifications and variations in the above description of the disclosed embodiments, enabling those skilled in the art to implement or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, this invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A wind turbine generator system failure monitoring system, characterized by, The method comprises the following steps: The acquisition module is used for collecting data of the wind turbine; The simulation module is used for simulating the fault of the wind turbine to generate data threshold for fault judgment; The monitoring module is used for identifying the fault of the wind turbine according to the operation data of the wind turbine and the data threshold to generate a fault alarm; The processing module is used for processing the fault of the wind turbine according to the fault alarm.

2. A wind turbine system fault monitoring system according to claim 1, wherein, The acquisition module comprises: The temperature unit is provided with a temperature sensor to collect temperature data of each component inside the wind turbine; The noise unit is provided with noise sensors installed inside and outside the gearbox of the wind turbine to collect noise data of the gearbox; The camera unit is provided with a camera installed at the diagonal of each wind turbine blade bolt, and the infrared ray is adjusted to point to the top of the blade bolt; The voltage and current unit is used for collecting voltage and current values when the wind turbine is running.

3. A wind turbine fault monitoring system according to claim 2, wherein, The simulation module comprises: The model unit is used for establishing a simulation model of the wind turbine; The temperature simulation unit is used for obtaining temperature values of each component of the wind turbine when the component fails based on the simulation model, and taking the temperature values as corresponding temperature threshold values of each component of the wind turbine; The noise simulation unit is used for simulating noise data inside and outside the gearbox of the wind turbine when the gearbox runs out of oil based on the simulation model, and taking the noise data as noise threshold values of the gearbox.

4. A wind turbine system fault monitoring system according to claim 3, wherein, The monitoring module comprises: The temperature monitoring unit is used for comparing real-time temperature of each component of the wind turbine with the corresponding temperature threshold value, and generating a temperature alarm when the deviation between the real-time temperature and the temperature threshold value exceeds a preset temperature deviation range; The noise monitoring unit is used for comparing real-time noise of the gearbox of the wind turbine with the noise threshold value, and generating a gearbox alarm when the deviation between the real-time noise and the noise threshold value exceeds a preset noise deviation range; The loosening monitoring unit is used for obtaining image data in the camera unit, and generating a bolt loosening alarm when the difference between the infrared ray and the horizontal plane in the image data exceeds a preset difference threshold value; The power monitoring unit is used for obtaining voltage and current data of the wind turbine, and generating a power alarm when the voltage and current values are 0.

5. A wind turbine system fault monitoring system according to claim 4, wherein, The processing module comprises: The fault simulation unit is used for inputting data information when the fault occurs into the simulation model to simulate the fault after generating the fault alarm information, confirming the fault alarm information if the same fault occurs, canceling the fault alarm information if the same fault does not occur, obtaining three groups of data with the shortest interval time, and processing the data by using an average value to re-judge the fault; The standby power unit is used for starting a standby power source to ensure normal operation of the wind turbine when the wind turbine generates a power alarm; The auxiliary cooling unit is used for starting a cooling device to cool down when the wind turbine generates a temperature alarm.

6. A wind turbine fault monitoring system, a wind turbine fault monitoring method according to claims 1-5, characterized in that, The method comprises the following steps: S1, collecting data of the wind turbine; S2, simulating the fault of the wind turbine to generate data threshold for fault judgment; S3, identifying the fault of the wind turbine according to the operation data of the wind turbine and the data threshold to generate a fault alarm; S4, processing the fault of the wind turbine according to the fault alarm.

7. A method of monitoring for faults in a wind turbine as defined in claim 6, wherein, The step S1 is specifically as follows: S11, set temperature sensors to collect temperature data of each component of the wind turbine; S12, install noise sensors inside and outside the gearbox of the wind turbine to collect noise data of the gearbox; S13, set a camera to be installed at the diagonal of the bolt of each wind turbine blade, and adjust the infrared rays to point to the top of the bolt; S14, collect voltage and current values when the wind turbine is running.

8. A method of monitoring for faults in a wind turbine as defined in claim 7, wherein, Step S2 is specifically as follows: S21, establish a simulation model of the wind turbine; S22, based on the simulation model, set the temperature value of each component of the wind turbine when a fault occurs as the corresponding temperature threshold of each component of the wind turbine; S23, based on the simulation model, simulate the noise data inside and outside the gearbox when the gearbox oil is almost consumed, and set the noise data as the noise threshold of the gearbox.

9. A method of monitoring for faults in a wind turbine as defined in claim 8, wherein, Step S3 is specifically as follows: S31, compare the real-time temperature of each component of the wind turbine with the corresponding temperature threshold, and generate a temperature alarm when the deviation between the real-time temperature and the temperature threshold exceeds the preset temperature deviation range; S32, compare the real-time noise of the gearbox of the wind turbine with the noise threshold, and generate a gearbox alarm when the deviation between the real-time noise and the noise threshold exceeds the preset noise deviation range; S33, obtain image data in the camera unit, and generate a bolt loosening alarm when the difference between the infrared rays in the image data and the horizontal plane exceeds the preset difference threshold; S34, obtain voltage and current data of the wind turbine, and generate a power alarm when the voltage and current values are 0.

10. A method of monitoring for faults in a wind turbine as defined in claim 9, wherein, Step S4 is specifically as follows: S41, after generating the fault alarm information, input the data information when the fault occurs into the simulation model to simulate the fault, if the same fault occurs, confirm the fault alarm information, if the same fault does not occur, cancel the fault alarm information, obtain three groups of data with the shortest interval time, process the data with average value, and re-judge the fault; S42, if the fault alarm information is a power alarm, start the standby power supply to ensure the normal operation of the wind turbine, record the operation data of the wind turbine in the next preset time period, and simulate the fault through the simulation model, if no fault information occurs, confirm the power alarm; S43, if the fault alarm information is a temperature alarm, start the cooling device to cool down, record the operation data of the wind turbine in the next preset time period, and simulate the fault through the simulation model, if no fault information occurs, confirm the temperature alarm.

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