Wind power coupling slip fault intelligent detection method based on image recognition

Abstract

The invention belongs to the technical field of wind power generation, and discloses a wind power coupling slip fault intelligent detection method based on image recognition, which comprises the following steps: pasting reflective adhesive tapes at two ends of a wind power coupling flange, and arranging a camera above a cabin to collect image data of a wind power coupling; acquiring first coupling image data and second coupling image data; converting the first coupling image data and the second coupling image data into two-dimensional plane vectors based on pixel colors, and analyzing an actual deviation angle; according to the acquired first deviation angle data and the second deviation angle data, the dislocation condition of the wind power coupling is detected in real time, the slip fault of the wind power coupling is analyzed in combination with the real-time rotating speed data and the real-time torque data, and a corresponding early warning prompt is given out to prompt a worker to overhaul. And under the condition that safe operation of the wind turbine generator is guaranteed, the shutdown overhaul time is shortened, the manual maintenance cost is reduced, and the availability of the generator is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, and in particular to an intelligent detection method for slippage faults in wind turbine couplings based on image recognition. Background Technology

[0002] A wind turbine is a device that converts the kinetic energy generated by airflow into electrical energy through a wind turbine unit. The wind turbine coupling is a crucial transmission component connecting the gearbox output shaft and the generator input shaft. Its main function is to transmit power to the generator as the impeller rotates, thereby generating electrical energy. It plays a vital role in torque transmission, compensating for multiple displacement deviations, absorbing shock vibrations, and providing electrical isolation.

[0003] Because wind turbine couplings operate at high speeds for extended periods during grid-connected operation, any unexpected slippage beyond design limits can lead to torque transmission failure, overheating due to friction, resonance, and secondary system problems. Therefore, proper maintenance and fault detection of wind turbine couplings are essential for the safe and stable operation of wind turbines.

[0004] In existing technologies, the detection of slippage faults in wind turbine couplings is usually done by comparing the speed difference between the gearbox and the generator. However, due to data misreporting issues during sensor detection and signal transmission, the detection accuracy is low. This requires manual onboard inspection and analysis, which increases maintenance costs and affects the availability of the unit. Summary of the Invention

[0005] To address some or all of the technical problems existing in the prior art, this invention provides an intelligent detection method for slippage faults in wind turbine couplings based on image recognition.

[0006] The technical solution of the present invention is as follows: A method for intelligent detection of slippage faults in wind turbine couplings based on image recognition is provided, including: Apply reflective tape to both ends of the wind turbine coupling flange; A camera is installed above the nacelle of the wind turbine coupling to collect image data of the wind turbine coupling according to a preset time period, thereby obtaining image data of the first coupling and image data of the second coupling. Based on pixel color, the first coupling image data and the second coupling image data are converted into two-dimensional plane vectors to analyze the actual deviation angle and obtain the first deviation angle data and the second deviation angle data. When there is a difference between the first deviation angle data and the second deviation angle data, the deviation angle parameter and the number of historical deviations are recorded. When the deviation angle parameter exceeds the preset parameter or the number of historical deviations exceeds the preset number, it is determined that the wind power coupling has a slippage fault. The system collects real-time speed and torque data of the wind turbine generator set. Based on the real-time speed data, it detects whether the wind turbine coupling has a speed deviation fault. When a speed deviation fault is detected, it checks whether the real-time torque data exceeds the slippage torque parameter. When the real-time torque data is greater than the slippage torque parameter, it checks whether the deviation angle parameter is greater than a preset parameter. When the deviation angle parameter is greater than the preset parameter, it is determined that the wind turbine coupling has a slippage fault. When a slippage fault is detected in the wind turbine coupling, a corresponding early warning is issued to remind staff to take appropriate measures to address the issue.

[0007] In some optional implementations, the step of: installing a camera above the nacelle of the wind turbine coupling, acquiring image data of the wind turbine coupling at preset time intervals, and obtaining first coupling image data and second coupling image data; includes: When a wind turbine fails and shuts down, image data is collected using a camera.

[0008] In some optional implementations, the step of: installing a camera above the nacelle of the wind turbine coupling, acquiring image data of the wind turbine coupling at preset time intervals, and obtaining first coupling image data and second coupling image data; includes: When the wind turbine's rotational speed is lower than the preset speed, image data is collected via a camera.

[0009] In some optional implementations, the step of converting the first coupling image data and the second coupling image data into two-dimensional planar vectors based on pixel color, analyzing the actual deviation angle, and obtaining first deviation angle data and second deviation angle data includes: The first coupling image data is converted into a two-dimensional plane vector based on pixel color to obtain the first coupling image processing data. Obtain the first displacement deviation of the parallel lines of the first coupling image processing data pixels, and calculate the first deviation angle data: ; in, This is the first deviation angle data. The first displacement deviation of the parallel lines of the pixel points in the image processing data of the first coupling. The ratio of the pixel size to the actual size of the image processing data for the first coupling. The radius of the wind turbine coupling is given.

[0010] In some optional implementations, the step of converting the first coupling image data and the second coupling image data into two-dimensional planar vectors based on pixel color, analyzing the actual deviation angle, and obtaining first deviation angle data and second deviation angle data includes: When there is no difference between the first deviation angle data and the second deviation angle data, it is determined that the wind turbine coupling does not have a slippage fault. The wind turbine coupling is checked for a speed deviation fault based on the real-time speed data of the wind turbine. If a speed deviation fault is detected in the wind turbine coupling, it is determined that the sensor is faulty. If no speed deviation fault is detected in the wind turbine coupling, it is determined that the wind turbine coupling is working normally.

[0011] In some optional implementations, the steps of: collecting real-time speed data and real-time torque data of the wind turbine generator set; detecting whether the wind turbine coupling has a speed deviation fault based on the real-time speed data; when a speed deviation fault is detected in the wind turbine coupling, detecting whether the real-time torque data exceeds a slippage torque parameter; when the real-time torque data is greater than the slippage torque parameter, detecting whether the deviation angle parameter is greater than a preset parameter; and when the deviation angle parameter is greater than the preset parameter, determining that the wind turbine coupling has a slippage fault; include: The system detects whether the wind turbine coupling has a speed deviation fault based on the real-time speed data. If the system detects that the wind turbine coupling does not have a speed deviation fault but has a slippage fault, then the sensor is determined to be faulty.

[0012] In some optional implementations, the steps of: collecting real-time speed data and real-time torque data of the wind turbine generator set; detecting whether the wind turbine coupling has a speed deviation fault based on the real-time speed data; when a speed deviation fault is detected in the wind turbine coupling, detecting whether the real-time torque data exceeds a slippage torque parameter; when the real-time torque data is greater than the slippage torque parameter, detecting whether the deviation angle parameter is greater than a preset parameter; and when the deviation angle parameter is greater than the preset parameter, determining that the wind turbine coupling has a slippage fault; include: The system detects whether the real-time torque data exceeds the slippage torque parameter. If the real-time torque data is less than the slippage torque parameter, it determines that the wind turbine coupling has a slippage fault.

[0013] In some optional implementations, the steps of: collecting real-time speed data and real-time torque data of the wind turbine generator set; detecting whether the wind turbine coupling has a speed deviation fault based on the real-time speed data; when a speed deviation fault is detected in the wind turbine coupling, detecting whether the real-time torque data exceeds a slippage torque parameter; when the real-time torque data is greater than the slippage torque parameter, detecting whether the deviation angle parameter is greater than a preset parameter; and when the deviation angle parameter is greater than the preset parameter, determining that the wind turbine coupling has a slippage fault; include: The system detects whether the deviation angle parameter is greater than a preset parameter. If the deviation angle parameter is less than the preset parameter, it is determined that the wind power coupling has experienced a momentary overload.

[0014] In some optional implementations, the step of: issuing a corresponding early warning when a slippage fault is detected in the wind turbine coupling to remind personnel to take appropriate measures to handle the wind turbine coupling; includes: When a slippage fault is detected in the wind turbine coupling, an early warning is issued to remind staff to board the aircraft for inspection and repair, and to replace the corresponding spare parts.

[0015] In some optional implementations, the step of: issuing a corresponding early warning when a slippage fault is detected in the wind turbine coupling to remind personnel to take appropriate measures to handle the wind turbine coupling; includes: When a momentary overload is detected in the wind turbine coupling, the corresponding overload data is recorded, and the wind turbine coupling is controlled to operate normally.

[0016] The main advantages of the technical solution of this invention are as follows: This invention discloses an intelligent detection method for wind turbine coupling slippage faults based on image recognition. By attaching conspicuous reflective tape to both sides of the slippage location on the wind turbine coupling, and using a camera to acquire images and identify features, the method performs real-time detection of misalignment of the wind turbine coupling markings. Combining real-time speed and torque data, it analyzes the wind turbine coupling slippage faults and issues corresponding early warning prompts to remind personnel to perform maintenance. This effectively avoids the shortcomings of traditional technologies that rely on single sensor detection, improves the detection accuracy of wind turbine coupling slippage faults, reduces downtime for maintenance and power generation loss while ensuring the safe operation of wind turbine units, lowers labor maintenance costs, and effectively improves unit availability. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and constitute a part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart illustrating an intelligent detection method for slippage faults in wind turbine couplings based on image recognition, provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] The technical solutions provided by the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] refer to Figure 1 This invention provides an intelligent detection method for slippage faults in wind turbine couplings based on image recognition, comprising: Apply reflective tape to both ends of the wind turbine coupling flange; A camera is installed above the nacelle of the wind turbine coupling to collect image data of the wind turbine coupling according to a preset time period, thereby obtaining image data of the first coupling and image data of the second coupling. Based on pixel color, the image data of the first coupling and the image data of the second coupling are converted into two-dimensional plane vectors to analyze the actual deviation angle and obtain the first deviation angle data and the second deviation angle data. When there is a difference between the first deviation angle data and the second deviation angle data, the deviation angle parameter and the number of historical deviations are recorded. When the deviation angle parameter exceeds the preset parameter or the number of historical deviations exceeds the preset number, it is determined that the wind turbine coupling has a slippage fault. The system collects real-time speed and torque data of the wind turbine. Based on the real-time speed data, it detects whether there is a speed deviation fault in the wind turbine coupling. When a speed deviation fault is detected in the wind turbine coupling, it checks whether the real-time torque data exceeds the slippage torque parameter. When the real-time torque data is greater than the slippage torque parameter, it checks whether the deviation angle parameter is greater than the preset parameter. When the deviation angle parameter is greater than the preset parameter, it is determined that the wind turbine coupling has a slippage fault. When a slippage fault is detected in the wind turbine coupling, a corresponding early warning will be issued to remind staff to take appropriate measures to handle the wind turbine coupling.

[0021] In this embodiment of the invention, before applying reflective tape, it is necessary to ensure that the wind turbine coupling is accurately aligned, the bolt torque is in place, the insulation is intact, and it is in the correct operating state. The reflective tape is applied in a horizontally aligned state and disconnected at the connection position to replace the function of the wind turbine coupling in inspecting the position of the line of sight, and to improve the visual effect of the acquired image data through prominent marking.

[0022] In this embodiment of the invention, by attaching multiple sets of reflective tape around the wind turbine coupling, the camera can collect image data of the first coupling containing the reflective tape and the second coupling containing the reflective tape from different angles, thereby enabling the camera to acquire image data with high contrast color features under different lighting conditions.

[0023] In this embodiment of the invention, reflective tape is pasted on both ends of the wind turbine coupling flange, and images are acquired by a camera inside the nacelle to obtain first deviation angle data and second deviation angle data. The actual deviation angle is analyzed based on the offset trend of the pixels to obtain first deviation angle data and second deviation angle data. When there is a difference between the first deviation angle data and the second deviation angle data, the deviation angle parameter and the number of historical deviations are recorded. If the deviation angle parameter exceeds the preset parameter or the number of historical deviations exceeds the preset number, it is determined that the wind turbine coupling has a slippage fault. Real-time speed data and real-time torque data of the wind turbine are collected. Based on the real-time speed data, it is detected whether the wind turbine coupling has a speed deviation fault. When a speed deviation fault is detected, it is checked whether the real-time torque data exceeds the slippage torque parameter. If the real-time torque data is greater than the slippage torque parameter, it is checked whether the deviation angle parameter is greater than the preset parameter. If the deviation angle parameter is greater than the preset parameter, it is determined that the wind turbine coupling has a slippage fault. When a slippage fault is detected, a corresponding early warning is issued to remind the staff to take appropriate measures to handle the wind turbine coupling.

[0024] In this embodiment of the invention, by recording the power parameters, torque parameters, engine speed parameters, and gearbox speed parameters of the wind turbine before the fault is triggered, it is possible to detect whether the engine speed and gearbox speed are synchronized, and then analyze the sensor fault or the wind turbine coupling fault.

[0025] In this embodiment of the invention, conspicuous reflective tape is affixed to both sides of the slippage location of the wind turbine coupling, and images are acquired and features are identified by a camera. The misalignment of the markings on the wind turbine coupling is detected in real time. Combined with real-time speed data and real-time torque data, the slippage fault of the wind turbine coupling is analyzed, and corresponding early warning prompts are issued to remind staff to carry out maintenance. This effectively avoids the defects of traditional technology that relies on single sensor detection, improves the detection accuracy of wind turbine coupling slippage faults, reduces downtime for maintenance and the resulting power generation loss while ensuring the safe operation of the wind turbine unit, lowers labor maintenance costs, and effectively improves the availability of the unit.

[0026] In this embodiment of the invention, the steps include: installing a camera above the nacelle of the wind turbine coupling, acquiring image data of the wind turbine coupling according to a preset time period, and obtaining first coupling image data and second coupling image data; including: When a wind turbine fails and shuts down, image data is collected using a camera.

[0027] When the wind turbine's rotational speed is lower than the preset speed, image data is collected via a camera.

[0028] In this embodiment of the invention, when the wind turbine is operating normally, image data is collected according to a preset time period (e.g., every 48 hours) to obtain image data of the first coupling and image data of the second coupling.

[0029] In this embodiment of the invention, when the wind turbine fails to shut down or when the wind turbine speed is lower than the preset speed (50 rpm), the camera is controlled to collect image data.

[0030] In this embodiment of the invention, image data is collected according to a preset time period when the wind turbine is working normally, or when the wind turbine is malfunctioning. This avoids the camera working for a long time, effectively reduces detection power consumption and detection cost, and improves the detection efficiency of wind turbine coupling slippage faults.

[0031] In this embodiment of the invention, the steps include: converting the first coupling image data and the second coupling image data into two-dimensional plane vectors based on pixel color, analyzing the actual deviation angle, and obtaining the first deviation angle data and the second deviation angle data; including: The first coupling image data is converted into a two-dimensional plane vector based on pixel color to obtain the first coupling image processing data; Obtain the first displacement deviation of the parallel lines of the first coupling image processing data pixels, and calculate the first deviation angle data: ; in, This is the first deviation angle data. The first displacement deviation of the parallel lines of the pixel points in the image processing data of the first coupling. The ratio of the pixel size to the actual size of the image processing data for the first coupling. The radius of the wind turbine coupling is given.

[0032] In this embodiment of the invention, image feature recognition is performed on the image data of the first coupling based on the color characteristics of the reflective tape, the color pixels are converted into two-dimensional planar vector analysis, and the first deviation angle data of the reflective tape at both ends in the image processing data of the first coupling is calculated.

[0033] In this embodiment of the invention, the steps include: converting the first coupling image data and the second coupling image data into two-dimensional plane vectors based on pixel color, analyzing the actual deviation angle, and obtaining the first deviation angle data and the second deviation angle data; including: When there is no difference between the first deviation angle data and the second deviation angle data, it is determined that there is no slippage fault in the wind turbine coupling. The wind turbine coupling is then checked for speed deviation fault based on the real-time speed data of the wind turbine. If a speed deviation fault is detected in the wind turbine coupling, it is determined that the sensor is faulty; if no speed deviation fault is detected in the wind turbine coupling, it is determined that the wind turbine coupling is working normally.

[0034] In this embodiment of the invention, when there is no difference between the first deviation angle data and the second deviation angle data, the wind turbine coupling is checked for speed deviation faults based on the real-time speed data of the wind turbine. If no speed deviation fault is detected in the wind turbine coupling, it is determined that the wind turbine coupling is working normally; if a speed deviation fault is detected in the wind turbine coupling, it is determined that the speed sensor of the wind turbine has malfunctioned and the wind turbine coupling has not slipped.

[0035] In this embodiment of the invention, the steps are as follows: Collecting real-time speed data and real-time torque data of the wind turbine generator set; detecting whether the wind turbine coupling has a speed deviation fault based on the real-time speed data; when a speed deviation fault is detected in the wind turbine coupling, detecting whether the real-time torque data exceeds the slippage torque parameter; when the real-time torque data is greater than the slippage torque parameter, detecting whether the deviation angle parameter is greater than a preset parameter; when the deviation angle parameter is greater than the preset parameter, determining that the wind turbine coupling has a slippage fault; including: The system detects whether there is a speed deviation fault in the wind turbine coupling based on real-time speed data. If no speed deviation fault is detected in the wind turbine coupling, but there is a slippage fault in the wind turbine coupling, then the sensor is determined to be faulty.

[0036] The system detects whether the real-time torque data exceeds the slippage torque parameter. If the real-time torque data is less than the slippage torque parameter, it is determined that the wind turbine coupling has a slippage fault.

[0037] The system detects whether the deviation angle parameter is greater than the preset parameter. If the deviation angle parameter is less than the preset parameter, it determines that the wind turbine coupling has experienced a momentary overload.

[0038] In this embodiment of the invention, if the wind turbine coupling is found to have no speed deviation fault based on real-time speed data, but has a slippage fault, then the speed sensor is determined to be faulty; if the real-time torque data is less than the slippage torque parameter, then the wind turbine coupling is determined to have a slippage fault; if the deviation angle parameter is less than the preset parameter, then the wind turbine coupling is determined to have experienced a momentary overload disengagement, maintaining the normal operation of the wind turbine unit and allowing slippage offset within the normal preset range under occasional extreme operating conditions.

[0039] In this embodiment of the invention, the step is as follows: when a slippage fault is detected in the wind turbine coupling, a corresponding early warning is issued to remind personnel to take appropriate measures to handle the wind turbine coupling; including: When a slippage fault is detected in the wind turbine coupling, an early warning is issued to remind staff to board the aircraft for inspection and repair, and to replace the corresponding spare parts.

[0040] When a momentary overload is detected in the wind turbine coupling, the corresponding overload data is recorded to control the wind turbine coupling to operate normally.

[0041] In this embodiment of the invention, when a slippage fault is detected in the wind turbine coupling, an early warning is issued, and the operating power of the wind turbine coupling is limited to remind staff to board the machine for inspection and maintenance, and to replace the corresponding spare parts. When a momentary overload is detected in the wind turbine coupling, the corresponding overload data is recorded, and the wind turbine coupling is controlled to operate normally. This achieves pre-analysis of the wind turbine coupling slippage fault handling, effectively reducing the number of times and time required for staff to register for inspection and maintenance, thereby improving the utilization rate of the wind turbine unit.

[0042] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Additionally, the terms "front," "back," "left," "right," "upper," and "lower" in this document refer to the placement shown in the accompanying drawings.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent detection of slippage faults in wind turbine couplings based on image recognition, characterized in that, include: Apply reflective tape to both ends of the wind turbine coupling flange; A camera is installed above the nacelle of the wind turbine coupling to collect image data of the wind turbine coupling according to a preset time period, thereby obtaining image data of the first coupling and image data of the second coupling. Based on pixel color, the first coupling image data and the second coupling image data are converted into two-dimensional plane vectors to analyze the actual deviation angle and obtain the first deviation angle data and the second deviation angle data. When there is a difference between the first deviation angle data and the second deviation angle data, the deviation angle parameter and the number of historical deviations are recorded. When the deviation angle parameter exceeds the preset parameter or the number of historical deviations exceeds the preset number, it is determined that the wind power coupling has a slippage fault. The system collects real-time speed and torque data of the wind turbine generator set. Based on the real-time speed data, it detects whether the wind turbine coupling has a speed deviation fault. When a speed deviation fault is detected, it checks whether the real-time torque data exceeds the slippage torque parameter. When the real-time torque data is greater than the slippage torque parameter, it checks whether the deviation angle parameter is greater than a preset parameter. When the deviation angle parameter is greater than the preset parameter, it is determined that the wind turbine coupling has a slippage fault. When a slippage fault is detected in the wind turbine coupling, a corresponding early warning is issued to remind staff to take appropriate measures to address the issue.

2. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: installing a camera above the nacelle of the wind turbine coupling, collecting image data of the wind turbine coupling according to a preset time period, and obtaining image data of the first coupling and the second coupling; including: When a wind turbine fails and shuts down, image data is collected using a camera.

3. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: installing a camera above the nacelle of the wind turbine coupling, collecting image data of the wind turbine coupling according to a preset time period, and obtaining image data of the first coupling and the second coupling; including: When the wind turbine's rotational speed is lower than the preset speed, image data is collected via a camera.

4. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: converting the first coupling image data and the second coupling image data into two-dimensional plane vectors based on pixel color, analyzing the actual deviation angle, and obtaining the first deviation angle data and the second deviation angle data; including: The first coupling image data is converted into a two-dimensional plane vector based on pixel color to obtain the first coupling image processing data. Obtain the first displacement deviation of the parallel lines of the first coupling image processing data pixels, and calculate the first deviation angle data: ； in, This is the first deviation angle data. The first displacement deviation of the parallel lines of the pixel points in the image processing data of the first coupling. The ratio of the pixel size to the actual size of the image processing data for the first coupling. The radius of the wind turbine coupling is given.

5. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: converting the first coupling image data and the second coupling image data into two-dimensional plane vectors based on pixel color, analyzing the actual deviation angle, and obtaining the first deviation angle data and the second deviation angle data; including: When there is no difference between the first deviation angle data and the second deviation angle data, it is determined that the wind turbine coupling does not have a slippage fault. The wind turbine coupling is checked for a speed deviation fault based on the real-time speed data of the wind turbine. If a speed deviation fault is detected in the wind turbine coupling, it is determined that the sensor is faulty. If no speed deviation fault is detected in the wind turbine coupling, it is determined that the wind turbine coupling is working normally.

6. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: collecting real-time speed and torque data of the wind turbine generator set; detecting whether the wind turbine coupling has a speed deviation fault based on the real-time speed data; when a speed deviation fault is detected, checking whether the real-time torque data exceeds a slippage torque parameter; if the real-time torque data exceeds the slippage torque parameter, checking whether the deviation angle parameter exceeds a preset parameter; and if the deviation angle parameter exceeds the preset parameter, determining that the wind turbine coupling has a slippage fault. The system detects whether the wind turbine coupling has a speed deviation fault based on the real-time speed data. If the system detects that the wind turbine coupling does not have a speed deviation fault but has a slippage fault, then the sensor is determined to be faulty.

7. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: collecting real-time speed and torque data of the wind turbine generator set; detecting whether the wind turbine coupling has a speed deviation fault based on the real-time speed data; when a speed deviation fault is detected, checking whether the real-time torque data exceeds a slippage torque parameter; if the real-time torque data exceeds the slippage torque parameter, checking whether the deviation angle parameter exceeds a preset parameter; and if the deviation angle parameter exceeds the preset parameter, determining that the wind turbine coupling has a slippage fault. The system detects whether the real-time torque data exceeds the slippage torque parameter. If the real-time torque data is less than the slippage torque parameter, it determines that the wind turbine coupling has a slippage fault.

8. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: collecting real-time speed and torque data of the wind turbine generator set; detecting whether the wind turbine coupling has a speed deviation fault based on the real-time speed data; when a speed deviation fault is detected, checking whether the real-time torque data exceeds a slippage torque parameter; if the real-time torque data exceeds the slippage torque parameter, checking whether the deviation angle parameter exceeds a preset parameter; and if the deviation angle parameter exceeds the preset parameter, determining that the wind turbine coupling has a slippage fault. The system detects whether the deviation angle parameter is greater than a preset parameter. If the deviation angle parameter is less than the preset parameter, it is determined that the wind power coupling has experienced a momentary overload.

9. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: when a slippage fault is detected in the wind turbine coupling, issuing a corresponding early warning to remind personnel to take appropriate measures to address the wind turbine coupling; including: When a slippage fault is detected in the wind turbine coupling, an early warning is issued to remind staff to board the aircraft for inspection and repair, and to replace the corresponding spare parts.

10. The wind turbine coupling slippage fault detection method based on image recognition according to claim 1, characterized in that, The steps include: when a slippage fault is detected in the wind turbine coupling, issuing a corresponding early warning to remind personnel to take appropriate measures to address the wind turbine coupling; including: When a momentary overload is detected in the wind turbine coupling, the corresponding overload data is recorded, and the wind turbine coupling is controlled to operate normally.

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