Monitoring method, system and equipment for wind driven generator and medium

Abstract

The invention discloses a monitoring method, system and equipment for a wind driven generator and a medium, and relates to the technical field of fan monitoring, and the method comprises the steps: carrying out the three-dimensional modeling based on the wind driven generator, and obtaining an initial three-dimensional model; acquiring operation data of the wind driven generator in real time; performing association fusion on the operation data and the initial three-dimensional model by using a preset data fusion algorithm to obtain a target three-dimensional model; and monitoring the wind driven generator based on the operation data and the target three-dimensional model, wherein the monitoring comprises data monitoring and fault monitoring. The problem that a traditional wind driven generator operation state monitoring system lacks a visual three-dimensional display function and is poor in monitoring effect on a wind driven generator is solved.

Description

Technical Field

[0001] This application relates to the field of wind turbine monitoring technology, and in particular to a monitoring method, system, equipment and medium for wind turbine generators. Background Technology

[0002] Wind power, as a clean and renewable energy source, has received widespread attention and application globally. However, traditional wind turbine operation status monitoring systems mainly rely on data acquisition and display, with operation data presented in the form of data tables or two-dimensional graphs, lacking intuitive three-dimensional display capabilities. This results in poor monitoring effectiveness for wind turbines, making it difficult for maintenance personnel to fully understand the operating status and performance of various components of the wind turbine system. Summary of the Invention

[0003] To overcome the problem that traditional wind turbine operation status monitoring systems lack intuitive three-dimensional display functions and have poor monitoring effects, this application provides a monitoring method, system, equipment, and medium for wind turbines.

[0004] Firstly, in order to solve the above-mentioned technical problems, this application provides a monitoring method for wind turbine generators, comprising: Based on the three-dimensional modeling of the wind turbine, an initial three-dimensional model is obtained; Real-time acquisition of wind turbine operating data; Using a pre-defined data fusion algorithm, the running data is correlated and fused with the initial 3D model to obtain the target 3D model; The monitoring of wind turbines is based on operational data and target 3D models, including data monitoring and fault monitoring.

[0005] Furthermore, based on the wind turbine, a 3D model is created to obtain an initial 3D model, including: Obtain the actual dimensions and design drawings of the wind turbine; Using pre-set 3D modeling software, 3D modeling is performed according to the actual dimensions and design drawings to obtain the initial 3D model.

[0006] Furthermore, the operational data includes component data for multiple parts of the wind turbine during operation; Using a pre-defined data fusion algorithm, the running data is correlated and fused with the initial 3D model to obtain the target 3D model, including: Using a preset data fusion algorithm, data from multiple components are preprocessed to obtain multiple processed data. The preprocessing includes filtering and timestamp alignment. Construct component anchor points for each part of the wind turbine on the initial 3D model; Multiple processed data points are associated with multiple component anchor points according to component type to form a target 3D model.

[0007] Furthermore, monitoring of wind turbines is conducted based on operational data and target 3D models, including: The target 3D model, which incorporates operational data, is displayed in 3D to monitor the data of the wind turbine. Using a pre-defined fault diagnosis algorithm, fault diagnosis is performed on the wind turbine based on the operating data to obtain fault parameters; Faults are displayed on the target 3D model based on fault parameters to monitor faults in wind turbines.

[0008] Furthermore, using a pre-defined fault diagnosis algorithm, fault diagnosis is performed on the wind turbine based on operational data to obtain fault parameters, including: Using a preset fault diagnosis algorithm, abnormal data is filtered out from the operating data according to a preset normal data range; The fault parameters corresponding to the abnormal data are found in the preset fault table. The fault parameters include the fault type and the type of the faulty component.

[0009] Furthermore, the fault parameters include fault type and faulty component type; based on the fault parameters, the fault is displayed on the target 3D model to monitor the faults in the wind turbine, including: Locate the faulty component corresponding to the faulty component type on the target 3D model; Find the warning color corresponding to the fault type in the preset fault severity color table; The faulty components on the target 3D model are rendered and displayed according to the warning colors to monitor the faults of the wind turbine.

[0010] Furthermore, a monitoring method for wind turbines also includes: Obtain user interaction information regarding the target 3D model; Control the target 3D model to respond to interactive information, so as to realize the interaction between the user and the target 3D model.

[0011] Secondly, this application also provides a monitoring system for wind turbines, comprising: The modeling module is used to perform 3D modeling based on wind turbines to obtain an initial 3D model. The data acquisition module is used to collect real-time operating data of the wind turbine. The data fusion module is used to associate and fuse the running data with the initial 3D model using a preset data fusion algorithm to obtain the target 3D model; The wind turbine monitoring module is used to monitor wind turbines based on operating data and target 3D models. The monitoring includes data monitoring and fault monitoring.

[0012] Thirdly, this application also provides a computing device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the monitoring method for a wind turbine generator as described above.

[0013] Fourthly, this application also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform steps of a monitoring method for a wind turbine generator.

[0014] The beneficial effects of this application are as follows: First, a 3D model is created based on the wind turbine to obtain an initial 3D model. Then, using a preset data fusion algorithm, the real-time collected operating data of the wind turbine is correlated and fused with this initial 3D model to obtain a target 3D model. This allows for a direct 3D display of the wind turbine's operating status. Next, data monitoring and fault monitoring are performed on the wind turbine based on the operating data and the target 3D model. In this way, by constructing the target 3D model, a relatively comprehensive 3D monitoring of the operating status and performance of each component in the wind turbine can be achieved. This facilitates maintenance personnel in gaining a timely and comprehensive understanding of the overall condition of the wind turbine, thereby improving the monitoring effectiveness. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart illustrating a monitoring method for a wind turbine generator, which is an exemplary embodiment of this application. Figure 2 This is a schematic diagram illustrating the structure of a monitoring system for a wind turbine generator, as shown in an exemplary embodiment of this application. Detailed Implementation

[0016] The following embodiments are further explanations and supplements to this application and do not constitute any limitation on this application.

[0017] The traditional monitoring scheme for wind turbine operation status monitoring systems is as follows: (1) Establish a chart display mode for the operating parameters of each system component of wind power generation, including key components such as blades, gearboxes, and generators.

[0018] (2) Real-time data collection of wind turbine operation data, including wind speed, wind direction, rotational speed, power, etc., is carried out through sensors and monitoring equipment.

[0019] (3) The collected operating data is displayed in charts to realize the real-time update and display of the operating status of the wind turbine.

[0020] (4) Users can observe the real-time operating status of the wind turbine by observing the operating data of each system in the chart.

[0021] (5) Provide user interaction functions. Users can use input devices such as mouse and keyboard to understand the different real-time operating data of different wind turbines, so as to understand the operating status and performance of wind turbines.

[0022] However, traditional wind turbine operation status monitoring systems mainly rely on data acquisition and display, with operation data displayed in the form of data tables or two-dimensional graphs, lacking intuitive three-dimensional display functions, making it difficult for operation and maintenance personnel to fully understand the operation status and performance of various components of the wind turbine system.

[0023] To address the aforementioned problems, embodiments of this application provide a monitoring method, system, device, and medium for wind turbine generators, which will be described in detail below.

[0024] The monitoring method for wind turbines provided in this application can be specifically executed by a server. It should be noted that the server can be a standalone server, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. No limitation is imposed here.

[0025] This application provides a monitoring method for wind turbines. Through three-dimensional modeling and real-time data fusion technology, it enables intuitive display and monitoring of the operating status of wind turbines, facilitating maintenance personnel to comprehensively analyze and process abnormal operating conditions of components in a certain part of the wind turbine.

[0026] Please see Figure 1 , Figure 1 An exemplary embodiment of this application illustrates a monitoring method for a wind turbine generator, such as... Figure 1 As shown, this application provides a monitoring method for wind turbines, comprising: S11, Based on the wind turbine, a three-dimensional model is created to obtain the initial three-dimensional model; S12, collects real-time operating data of wind turbines; S13, using a preset data fusion algorithm, the running data is correlated and fused with the initial 3D model to obtain the target 3D model; S14 monitors the wind turbine based on operational data and the target 3D model, including data monitoring and fault monitoring.

[0027] The wind turbine monitoring method provided in this application firstly involves creating a 3D model of the wind turbine to obtain an initial 3D model. Then, using a preset data fusion algorithm, real-time collected operating data of the wind turbine is correlated and fused with this initial 3D model to obtain a target 3D model. This target 3D model provides a clear and intuitive 3D display of the wind turbine's operating status. Next, data monitoring and fault monitoring are performed on the wind turbine based on the operating data and the target 3D model. In this way, by constructing the target 3D model, a more comprehensive 3D monitoring of the operating status and performance of each component in the wind turbine can be achieved. This allows maintenance personnel to gain a timely and comprehensive understanding of the overall condition of the wind turbine, thereby improving the monitoring effectiveness.

[0028] In this embodiment, real-time operational data of the wind turbine is collected. The specific steps are as follows: various sensors, such as anemometers, wind vanes, speed sensors, and power meters, are installed on different components of the wind turbine to collect operational data in real time. The collected operational data can be transmitted wirelessly or via wired connection to a data acquisition system, such as a PLC (Programmable Logic Controller) or SCADA (Supervisory Control and Data Acquisition) system, for storage and retrieval for subsequent correlation, fusion, and monitoring.

[0029] Optionally, a three-dimensional model is performed based on the wind turbine to obtain an initial three-dimensional model, including: Obtain the actual dimensions and design drawings of the wind turbine; Using pre-set 3D modeling software, 3D modeling is performed according to the actual dimensions and design drawings to obtain the initial 3D model.

[0030] In the embodiment provided in this application, a pre-defined 3D modeling software is used to create a 3D model based on the actual dimensions and design drawings of the wind turbine. This yields an initial 3D model that meets the size matching requirements, thereby improving the effectiveness of subsequent wind turbine monitoring based on the initial 3D model. The 3D modeling software can be Autodesk Maya or Blender. The initial 3D model includes all key components such as blades, tower, generator, gearbox, and control system. Each key component has sufficient detail for clear 3D visualization in subsequent operations.

[0031] Optionally, the operational data includes component data of multiple components of the wind turbine during operation; Using a pre-defined data fusion algorithm, the running data is correlated and fused with the initial 3D model to obtain the target 3D model, including: Using a preset data fusion algorithm, data from multiple components are preprocessed to obtain multiple processed data. The preprocessing includes filtering and timestamp alignment. Construct component anchor points for each part of the wind turbine on the initial 3D model; Multiple processed data points are associated with multiple component anchor points according to component type to form a target 3D model.

[0032] In the embodiment provided in this application, firstly, a preset data fusion algorithm is used to preprocess data from multiple components to reduce noise and errors introduced by time differences, ensuring that the processed data meets accuracy requirements. Secondly, component anchor points for each component of the wind turbine are constructed on the initial 3D model, and multiple processed data are associated with these component anchor points according to component type to form a target 3D model. This allows each processed data to be displayed in 3D at its matching position on the target 3D model, and the display status of the target 3D model (e.g., blade rotation angle, tower tilt angle, generator output power, etc.) can be updated based on real-time operating data. This improves the intuitiveness of 3D monitoring of the wind turbine and enhances the monitoring effect.

[0033] In this embodiment, the specific steps of the filtering process are as follows: input the data of each component into a Kalman filter for Kalman filtering, and output smooth, reliable filtered data to reduce noise and jitter in the component data.

[0034] The specific steps for timestamp alignment are as follows: For each data acquisition moment, the data acquisition moment is used as a time reference; the timestamps of the filtered data corresponding to the data of each component acquired before and after the data acquisition moment (the acquisition response of some sensors has a lag) are all unified with this time reference to achieve timestamp alignment of each filtered data and obtain multiple processed data.

[0035] Optionally, the wind turbine is monitored based on operational data and a target 3D model, including: The target 3D model, which incorporates operational data, is displayed in 3D to monitor the data of the wind turbine. Using a pre-defined fault diagnosis algorithm, fault diagnosis is performed on the wind turbine based on the operating data to obtain fault parameters; Faults are displayed on the target 3D model based on fault parameters to monitor faults in wind turbines.

[0036] In the embodiment provided in this application, a target 3D model incorporating operational data is displayed in 3D, and a preset fault diagnosis algorithm is used to diagnose the wind turbine based on the operational data to obtain fault parameters. The fault parameters are then displayed on the target 3D model, thereby realizing 3D data monitoring and 3D fault monitoring of the wind turbine to improve the monitoring effect of the wind turbine.

[0037] In this embodiment, when displaying the target 3D model incorporating operational data, a 3D graphics rendering engine, such as Unity or Unreal Engine, is used to display the target 3D model on the screen in a 3D format. Users can perform interactive operations such as scaling, rotating, and translating the 3D target model using input devices such as a mouse, keyboard, or touchscreen. The 3D format includes an overall view of the wind turbine and detailed views of each component. The target 3D model on the screen displays various processing data corresponding to the operational data using a preset display method, which is either fixed annotation display or display triggered by clicking on a component.

[0038] Optionally, a preset fault diagnosis algorithm is used to diagnose faults in the wind turbine based on operating data, obtaining fault parameters, including: Using a preset fault diagnosis algorithm, abnormal data is filtered out from the operating data according to a preset normal data range; The fault parameters corresponding to the abnormal data are found in the preset fault table. The fault parameters include the fault type and the type of the faulty component.

[0039] In the embodiment provided in this application, a preset fault diagnosis algorithm is used to filter out abnormal data from the operating data and find the corresponding fault parameters. This allows for subsequent fault display on the target 3D model based on the fault parameters, enabling 3D fault monitoring of the wind turbine and improving the monitoring effect. The fault types include blade damage, bearing wear, and generator overheating.

[0040] Optionally, the fault parameters include fault type and faulty component type; based on the fault parameters, the fault is displayed on the target 3D model to monitor the fault of the wind turbine, including: Locate the faulty component corresponding to the faulty component type on the target 3D model; Find the warning color corresponding to the fault type in the preset fault severity color table; The faulty components on the target 3D model are rendered and displayed according to the warning colors to monitor the faults of the wind turbine.

[0041] In the embodiment provided in this application, the faulty component corresponding to the faulty component type is found on the target 3D model, and the reminder color corresponding to the fault type is found. The faulty component on the target 3D model is rendered and displayed according to the reminder color to monitor the fault of the wind turbine. This allows the fault in the wind turbine to be highlighted with the reminder color, improving the visual effect of the fault reminder and thus improving the fault monitoring effect.

[0042] In one exemplary embodiment provided in this application, a developed fault diagnosis algorithm automatically diagnoses faults occurring in a wind turbine based on real-time monitored operating data, obtaining fault parameters. The fault diagnosis algorithm can identify common fault types, such as blade damage, bearing wear, and generator overheating, and mark them in real-time in the target 3D model using red or other prominent warning colors for rendering. Simultaneously, it calls upon the wind turbine's professional maintenance manual or fault handling manual to provide corresponding troubleshooting and / or repair suggestions for the fault type.

[0043] Optionally, a monitoring method for wind turbines further includes: Obtain user interaction information regarding the target 3D model; Control the target 3D model to respond to interactive information, so as to realize the interaction between the user and the target 3D model.

[0044] In the embodiment provided in this application, the control target 3D model responds to the user's interactive information on the target 3D model, which enables interaction between the user and the target 3D model. This allows the user to intuitively view and understand the operating data of the wind turbine or components they want to know, thereby improving the user's monitoring effect on the wind turbine.

[0045] In one exemplary embodiment provided in this application, the interaction between the user and the target 3D model is achieved through a user interface. The user interface includes controls such as menus, buttons, and sliders, allowing the user to select different views, adjust display parameters, and view running data. The user can also use input devices such as a mouse, keyboard, or touchscreen to perform interactive operations such as scaling, rotating, and translating the target 3D model displayed in a 3D format on the user interface.

[0046] The monitoring method for wind turbines provided in this application includes the following steps: 1. Establish an initial three-dimensional model of the wind turbine, including key components such as blades, tower, and generator.

[0047] 2. Real-time data collection of wind turbine operation, including wind speed, wind direction, rotational speed, and power, is achieved through sensors and monitoring equipment.

[0048] 3. The collected operational data is correlated and fused with the initial 3D model to obtain the target 3D model. Based on the operational data and the target 3D model, data monitoring and fault monitoring of the wind turbine are performed to realize real-time updates and display of the wind turbine's operating status.

[0049] 4. Using 3D graphics rendering technology, the fused target 3D model is displayed on the screen in a 3D form, allowing users to intuitively observe the operating status and performance of the wind turbine.

[0050] 5. Provides user interaction functions, allowing users to zoom, rotate, and translate the target 3D model using input devices such as a mouse and keyboard, in order to gain a more comprehensive understanding of the wind turbine's operating status.

[0051] Please see Figure 2 , Figure 2 An exemplary embodiment of this application illustrates a monitoring system for a wind turbine, such as... Figure 2 As shown, this application provides a monitoring system 200 for wind turbine generators, comprising: Modeling module 201 is used to perform three-dimensional modeling based on wind turbines to obtain an initial three-dimensional model; The data acquisition module 202 is used to acquire real-time operating data of the wind turbine. The data fusion module 203 is used to associate and fuse the running data with the initial three-dimensional model using a preset data fusion algorithm to obtain the target three-dimensional model; The wind turbine monitoring module 204 is used to monitor the wind turbine based on operating data and the target 3D model. The monitoring includes data monitoring and fault monitoring.

[0052] The wind turbine monitoring system 200 of this embodiment first uses a modeling module 201 to create a 3D model of the wind turbine, obtaining an initial 3D model. Then, in the data fusion module 203, a preset data fusion algorithm is used to correlate and fuse the wind turbine's real-time operating data collected by the acquisition module 202 with the initial 3D model to obtain a target 3D model. This target 3D model provides a clear 3D view of the wind turbine's operating status. Next, the wind turbine monitoring module 204 uses the operating data and the target 3D model to perform data monitoring and fault monitoring of the wind turbine. In this way, by constructing the target 3D model, a more comprehensive 3D monitoring of the operating status and performance of each component of the wind turbine can be achieved. This allows maintenance personnel to gain a timely and comprehensive understanding of the overall condition of the wind turbine, thereby improving the monitoring effectiveness.

[0053] Optionally, modeling module 201 is specifically used for: Obtain the actual dimensions and design drawings of the wind turbine; Using pre-set 3D modeling software, 3D modeling is performed according to the actual dimensions and design drawings to obtain the initial 3D model.

[0054] Optionally, the operational data includes component data of multiple components of the wind turbine during operation; Data fusion module 203 is specifically used for: Using a preset data fusion algorithm, data from multiple components are preprocessed to obtain multiple processed data. The preprocessing includes filtering and timestamp alignment. Construct component anchor points for each part of the wind turbine on the initial 3D model; Multiple processed data points are associated with multiple component anchor points according to component type to form a target 3D model.

[0055] Optionally, the wind turbine monitoring module 204 is specifically used for: The target 3D model, which incorporates operational data, is displayed in 3D to monitor the data of the wind turbine. Using a pre-defined fault diagnosis algorithm, fault diagnosis is performed on the wind turbine based on the operating data to obtain fault parameters; Faults are displayed on the target 3D model based on fault parameters to monitor faults in wind turbines.

[0056] Optionally, the wind turbine monitoring module 204 is specifically used for: Using a preset fault diagnosis algorithm, abnormal data is filtered out from the operating data according to a preset normal data range; The fault parameters corresponding to the abnormal data are found in the preset fault table. The fault parameters include the fault type and the type of the faulty component.

[0057] Optionally, the fault parameters include fault type and faulty component type; the wind turbine monitoring module 204 is specifically used for: Locate the faulty component corresponding to the faulty component type on the target 3D model; Find the warning color corresponding to the fault type in the preset fault severity color table; The faulty components on the target 3D model are rendered and displayed according to the warning colors to monitor the faults of the wind turbine.

[0058] Optionally, a monitoring system 200 for a wind turbine generator further includes an interaction module, which is specifically used for: Obtain user interaction information regarding the target 3D model; Control the target 3D model to respond to interactive information, so as to realize the interaction between the user and the target 3D model.

[0059] In summary, the monitoring system 200 for wind turbines of this application can achieve the following effects: System Integration: Integrate functions such as 3D modeling, data acquisition, data fusion, 3D display, user interaction, and fault diagnosis into a unified system. The system should have good stability and reliability, be able to operate stably for a long time, and adapt to various environmental conditions.

[0060] System Testing: System testing is conducted at the wind farm to verify the system's performance and reliability. Testing includes various operating conditions and fault scenarios to ensure the system can function properly under diverse conditions.

[0061] System Deployment: Deploy the system at the wind farm and provide necessary training and maintenance. The system should be easy to install and use, and a detailed user manual and maintenance guide should be provided.

[0062] System Effects: The 3D display system for wind turbine operation status proposed in this application achieves intuitive display and monitoring of the wind turbine's operation status through 3D modeling and real-time data fusion technology. Users can gain a more comprehensive understanding of the wind turbine's operation status and performance through the 3D display, improving the efficiency of wind turbine monitoring and maintenance.

[0063] It should be noted that the monitoring system for wind turbines provided in the above embodiments and the monitoring method for wind turbines provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the monitoring system for wind turbines provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0064] A computing device according to an embodiment of this application includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements some or all of the steps of the above-described monitoring method for wind turbine generators.

[0065] The computing device can be a computer, and the corresponding program is computer software. The parameters and steps in the computing device described above can be referred to the parameters and steps in the embodiment of the monitoring method for wind turbine generators above, and will not be repeated here.

[0066] This application embodiment provides a computer-readable storage medium storing instructions that, when executed, perform the steps of the aforementioned monitoring method for a wind turbine generator.

[0067] The computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0068] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of this disclosure. The aforementioned computer-readable storage medium can be a non-transitory computer-readable storage medium, including: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, and other media capable of storing program code; it can also be a transient computer-readable storage medium.

[0069] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0070] Those skilled in the art will recognize that this application can be implemented as a system, method, or computer program product. Therefore, this disclosure can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "module" or "system." Furthermore, in some embodiments, this application can also be implemented as a computer program product contained in one or more computer-readable media, which contains computer-readable program code. Computer-readable storage media can be, for example, but not limited to—electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof.

[0071] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. 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. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0072] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A monitoring method for wind turbine generators, characterized in that, include: Based on the three-dimensional modeling of the wind turbine, an initial three-dimensional model is obtained; Real-time acquisition of the wind turbine's operating data; Using a preset data fusion algorithm, the running data is correlated and fused with the initial 3D model to obtain the target 3D model; The wind turbine is monitored based on the operational data and the target 3D model. The monitoring includes data monitoring and fault monitoring.

2. The method according to claim 1, characterized in that, The initial 3D model obtained by performing 3D modeling based on the wind turbine includes: Obtain the actual dimensions and design drawings of the wind turbine; Using pre-set 3D modeling software, a 3D model is created according to the actual dimensions and the design drawings to obtain an initial 3D model.

3. The method according to claim 1, characterized in that, The operational data includes component data of multiple components of the wind turbine during operation; The step of using a preset data fusion algorithm to correlate and fuse the running data with the initial 3D model to obtain the target 3D model includes: Using a preset data fusion algorithm, the data of multiple components are preprocessed to obtain multiple processed data; Construct component anchor points for each component of the wind turbine on the initial three-dimensional model; The multiple processed data and multiple component anchor points are associated with each other according to the component type to form a target three-dimensional model.

4. The method according to claim 1, characterized in that, The monitoring of the wind turbine based on the operational data and the target 3D model includes: The target 3D model, which incorporates the operational data, is displayed in 3D to monitor the data of the wind turbine. Using a preset fault diagnosis algorithm, fault diagnosis is performed on the wind turbine based on the operating data to obtain fault parameters; Based on the fault parameters, the fault is displayed on the target 3D model to monitor the fault of the wind turbine.

5. The method according to claim 4, characterized in that, The method of using a preset fault diagnosis algorithm to diagnose faults in the wind turbine based on the operating data and obtaining fault parameters includes: Using a preset fault diagnosis algorithm, abnormal data is filtered out from the operating data according to a preset normal data range; The fault parameters corresponding to the abnormal data are found in the preset fault table. The fault parameters include the fault type and the fault component type.

6. The method according to claim 4, characterized in that, The fault parameters include fault type and fault component type; the step of displaying the fault on the target 3D model based on the fault parameters to monitor the fault of the wind turbine includes: Locate the faulty component corresponding to the faulty component type on the target 3D model; Find the alert color corresponding to the fault type in the preset fault severity color table; The faulty components on the target 3D model are rendered and displayed according to the warning colors to monitor the faults of the wind turbine.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Obtain user interaction information regarding the target 3D model; The target 3D model is controlled to respond to the interactive information in order to realize the interaction between the user and the target 3D model.

8. A monitoring system for wind turbine generators, characterized in that, include: The modeling module is used to perform 3D modeling based on wind turbines to obtain an initial 3D model. The data acquisition module is used to collect the operating data of the wind turbine in real time. The data fusion module is used to associate and fuse the running data with the initial three-dimensional model using a preset data fusion algorithm to obtain the target three-dimensional model; The wind turbine monitoring module is used to monitor the wind turbine based on the operating data and the target 3D model. The monitoring includes data monitoring and fault monitoring.

9. A computing device, comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of a monitoring method for a wind turbine as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the steps of a monitoring method for a wind turbine as described in any one of claims 1 to 7.

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