An automatic control method and system for fan operating conditions

Abstract

This invention provides an automatic control method and system for wind turbine operating conditions, applied in the field of automatic control technology. The method includes: collecting application environment information of the wind turbine; setting preset standard dust removal parameters based on the application environment information; subsequently, collecting parameters of the wind turbine's real-time operating status to obtain a set of real-time operating status parameters; extracting main features from the set of real-time operating status parameters to obtain target operating status parameters, which have a direct correlation with the preset standard dust removal parameters; constructing a dynamic influence relationship between the target operating status parameters and the preset standard dust removal parameters; and using this dynamic influence relationship to control the wind turbine, further ensuring the dust removal effect. This solves the technical problem in the prior art where the dust removal parameters cannot be adjusted according to the actual operating environment, resulting in poor dust removal performance.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology, specifically to an automatic control method and system for wind turbine operating conditions. Background Technology

[0002] Fans are crucial production equipment, involved in various energy conversion processes during operation. They are widely used in power plants, tunnels, automobiles, and other fields, and can be categorized into different types based on function, such as dust collection fans and ventilation fans. Because dust collection fans need to accelerate airflow during operation, in environments with high dust levels, dust adheres to the fan blades, increasing the fan load and affecting dust collection efficiency. Therefore, dust collection parameters need to be adjusted according to different dust collection environments. However, in current technology, dust collection is often performed using fixed parameters without adjustment based on the actual operating environment, resulting in poor dust collection performance.

[0003] Therefore, in the existing technology, the dust removal parameters of the fan cannot be adjusted according to the actual operating environment, resulting in poor dust removal effect of the fan. Summary of the Invention

[0004] This application provides an automatic control method and system for the operating conditions of a fan, which addresses the technical problem in the prior art where the dust removal parameters of a fan cannot be adjusted according to the actual operating environment, resulting in poor dust removal performance.

[0005] In view of the above problems, this application provides an automatic control method and system for wind turbine operating conditions.

[0006] The first aspect of this application provides an automatic control method for wind turbine operating conditions. The method is applied to an automatic control system and includes: collecting application environment information of the wind turbine; obtaining preset standard dust removal parameters by setting standard dust removal parameters based on the application environment information; collecting parameters of the real-time operating status of the wind turbine to obtain a set of real-time operating status parameters; obtaining target operating status parameters by extracting main features from the set of real-time operating status parameters, wherein the target operating status parameters have a direct correlation with the preset standard dust removal parameters; constructing a dynamic influence relationship between the target operating status parameters and the preset standard dust removal parameters; and controlling the wind turbine using the dynamic influence relationship.

[0007] A second aspect of this application provides an automatic control system for wind turbine operating conditions, comprising: a data acquisition module for acquiring application environment information of the wind turbine; a preset standard dust removal parameter acquisition module for obtaining preset standard dust removal parameters by setting standard dust removal parameters based on the application environment information; a state parameter set acquisition module for acquiring parameters of the real-time operating state of the wind turbine to obtain a real-time operating state parameter set; a target operating state parameter acquisition module for obtaining target operating state parameters by extracting main features from the real-time operating state parameter set, wherein the target operating state parameters have a direct correlation with the preset standard dust removal parameters; a dynamic influence relationship construction module for constructing a dynamic influence relationship between the target operating state parameters and the preset standard dust removal parameters; and an intelligent control module for controlling the wind turbine using the dynamic influence relationship.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The method provided in this application embodiment acquires application environment information and sets standard dust removal parameters based on that information to obtain preset standard dust removal parameters. Subsequently, it collects parameters of the fan's real-time operating status to obtain a set of real-time operating status parameters. By extracting the main features of the real-time operating status parameter set, it extracts the operating parameters that have a high correlation with the preset standard dust removal parameters, thus obtaining the target operating status parameters. Then, it constructs a dynamic influence relationship between the target operating status parameters and the preset standard dust removal parameters based on the correlation of the target operating status parameters. Using this dynamic influence relationship, it controls the fan, further ensuring the dust removal effect. This solves the technical problem in the prior art where the dust removal parameters cannot be adjusted according to the actual operating environment, resulting in poor dust removal performance.

[0010] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0011] Figure 1 A schematic flowchart of an automatic control method for wind turbine operating conditions provided in this application;

[0012] Figure 2 A flowchart illustrating the process of obtaining target operating state parameters in an automatic control method for wind turbine operating conditions provided in this application;

[0013] Figure 3A flowchart illustrating the construction of dynamic influence relationships in an automatic control method for wind turbine operating conditions provided in this application;

[0014] Figure 4 This application provides a schematic diagram of the structure of an automatic control system for wind turbine operating conditions.

[0015] Figure labeling: Data acquisition module 11, preset standard dust removal parameter acquisition module 12, status parameter set acquisition module 13, target operating status parameter acquisition module 14, dynamic influence relationship construction module 15, intelligent control module 16. Detailed Implementation

[0016] This application provides an automatic control method and system for the operating conditions of a fan, which addresses the technical problem in the prior art where the dust removal parameters of a fan cannot be adjusted according to the actual operating environment, resulting in poor dust removal performance.

[0017] The technical solutions in this application will now be clearly and completely described with reference to the accompanying drawings. The described embodiments are only a part of what can be achieved by this application, and not all of the contents of this application.

[0018] Example 1

[0019] like Figure 1 As shown, this application provides an automatic control method for wind turbine operating conditions. The method is applied to an automatic control system and includes:

[0020] Step 100: Collect information on the application environment of the wind turbine;

[0021] Step 200: Obtain preset standard dust removal parameters by setting standard dust removal parameters based on the application environment information;

[0022] Specifically, information on the actual application environment of the wind turbines is collected, such as the dust removal scenario in a power plant during power generation. Because wind turbines need to accelerate airflow during operation, when the dust level is high, dust will adhere to the surface of the turbine blades, increasing the turbine's load. Using fixed dust removal parameters would affect the dust removal efficiency. Therefore, standard dust removal parameters need to be set according to the wind turbine's application environment to ensure its operational performance under those conditions. These standard dust removal parameters are environmental parameters under standard wind turbine conditions, such as the amount of dust and the dust removal area. Preset standard dust removal parameters are obtained, which are environmental parameters under different application environment conditions.

[0023] Step 300: Collect parameters of the real-time operating status of the fan to obtain a set of real-time operating status parameters;

[0024] Step 400: By extracting the main features from the set of real-time operating status parameters, the target operating status parameters can be obtained, wherein the target operating status parameters have a direct correlation with the preset standard dust removal parameters;

[0025] Specifically, the real-time operating status of the fan is collected, including various parameters such as fan speed, air volume, dynamic pressure, and power. These operating parameters form a real-time operating status parameter set. Then, the main features of the collected real-time operating status parameter set are extracted, and parameters with high correlation between the fan operating parameters and preset standard dust removal parameters are extracted to form target operating status parameters. These target operating status parameters have a direct correlation with the preset standard dust removal parameters.

[0026] like Figure 2 As shown, the method step 400 provided in this embodiment further includes:

[0027] Step 410: Collect the correlation between each operating status parameter and the preset standard dust removal parameter in the real-time operating status parameter set, and obtain the correlation distribution of each operating status parameter-standard dust removal parameter;

[0028] Step 420: By filtering the correlation distribution of each operating state parameter and standard dust removal parameter using a preset correlation value, the target operating state parameter can be obtained.

[0029] Specifically, the correlation between each operating status parameter and a preset standard dust removal parameter is collected from the real-time operating status parameter set. A correlation distribution of each operating status parameter and the preset standard dust removal parameter is constructed based on the correlation between the operating status parameters and the preset standard dust removal parameter. This distribution reflects the correlation between the operating status parameters and the standard dust removal parameter, i.e., the environmental parameters. Then, parameters in the correlation distribution that do not meet the preset value are filtered out. That is, parameters in the correlation distribution of each operating status parameter and the preset correlation value are selected as the target operating status parameters.

[0030] The method step 400 provided in this application embodiment further includes:

[0031] Step 430: Collect standard dust removal parameters for the fan at historical time points to obtain the distribution of standard dust removal parameters at each historical time point;

[0032] Step 440: Collect the historical operating parameters of the fan for each distribution parameter in the standard dust removal parameter distribution of each historical node to obtain the set of historical operating parameters for each node;

[0033] Step 450: Obtain the intersection parameter feature set by performing intersection processing on the historical operation parameter sets of each node;

[0034] Step 460: Using the intersection parameter feature set, calculate the correlation distribution of each operating state parameter with the standard dust removal parameter.

[0035] Specifically, standard dust removal parameters are collected at historical operating time points of the wind turbine to obtain the distribution of standard dust removal parameters in the wind turbine's operating history, i.e., the distribution of dust removal parameters under different dust removal environments. Then, historical operating parameters of the wind turbine are collected based on the distribution of standard dust removal parameters at historical nodes to obtain a set of historical operating parameters during dust removal. The intersection processing of parameter features from the historical operating parameter sets of each node is performed. This intersection processing involves obtaining the parameters adjusted during dust removal from the historical operating parameter sets of the dust removal nodes, i.e., the dust removal parameters adjusted for different dust removal environments. Since it is necessary to construct the correlation distribution between each operating state parameter and the standard dust removal parameter, it is necessary to obtain the parameters adjusted under different dust removal scenarios to obtain the parameter correlation. For example, if the wind turbine speed and air volume change under different dust removal scenarios in the obtained historical parameters, then it can be concluded that the wind turbine speed, air volume, and standard dust removal parameters have a strong correlation. Finally, through intersection processing, the intersection parameter feature set is obtained, and the correlation distribution between each operating state parameter and the standard dust removal parameter is calculated. When calculating the specific correlation, it can be determined by the ratio of the change in the fan dust removal parameter under different environmental parameter settings to the standard dust removal parameter. For example, if the environmental parameter changes from A to B, the change in the fan dust removal parameter from a to b is c, and the standard dust removal parameter is D. In this case, the correlation is c / D. This completes the construction of the correlation between each operating state parameter and the standard dust removal parameter, providing support for subsequent fan control based on the target operating state parameters.

[0036] like Figure 3 As shown, the method step 400 provided in this embodiment further includes:

[0037] Step 470: Collect and obtain the weight distribution of each operating state parameter in relation to the preset standard dust removal parameter among the target operating state parameters;

[0038] Step 480: Based on the distribution of the weights of each influence, perform weight calculation on the preset standard dust removal parameters to obtain the influence coefficients of each operating state;

[0039] Step 490: Construct the dynamic influence relationship using the influence coefficients of each operating state.

[0040] Specifically, the influence weight distribution of each operating state parameter in the target operating state parameters on the preset standard dust removal parameters is collected. This is achieved by summing the correlation degrees of all parameters in the target operating state parameters to obtain the proportion of each parameter's correlation degree to the total correlation degrees of all parameters. Subsequently, based on this influence weight distribution, weight calculations are performed on the preset standard dust removal parameters to obtain the influence coefficients of each operating state parameter on the preset standard dust removal parameters. In other words, the weight distribution is transformed into specific changes in the preset standard dust removal parameters through weight calculations on the preset standard dust removal parameters. Then, using the influence coefficients of each operating state, a dynamic influence relationship is constructed, which reflects the dynamic relationship between the change in the target operating state parameter and the preset standard dust removal parameter. When the target parameter 'a' changes, the change in the preset standard dust removal parameter can be determined based on the dynamic relationship. By constructing the dynamic influence relationship, a correspondence between operating parameters and dust removal parameters is established, facilitating subsequent direct adjustment of the fan operating parameters.

[0041] The method step 470 provided in this embodiment further includes:

[0042] Step 471: Construct a weight allocation channel, wherein the weight allocation channel includes several sub-channels;

[0043] Step 472: Input each of the operating status parameters into the several sub-channels in sequence for weight allocation;

[0044] Step 473: Obtain the weight allocation result, which includes the distribution of the weight percentage of each influence.

[0045] Specifically, a weight allocation channel is constructed to assign weights to various target operational state parameters. This channel comprises several sub-channels, each with a different function: a correlation degree overlay calculation channel and a weight calculation channel. The correlation degree overlay calculation channel calculates the correlation degree of each operational parameter and overlays it to obtain the correlation degree overlay calculation result. The weight calculation channel allocates weights based on the correlation degree of each operational parameter and the correlation degree overlay calculation result; the higher the correlation degree, the larger the weight proportion allocated. The weight allocation results for each operational parameter are obtained, and these results include the weight distribution of each influencing factor.

[0046] Step 500: Construct the dynamic influence relationship between the target operating state parameters and the preset standard dust removal parameters;

[0047] Step 600: Control the fan using the dynamic influence relationship.

[0048] Specifically, a dynamic influence relationship is constructed between the target operating state parameters and the preset standard dust removal parameters. By constructing this dynamic influence relationship, a correspondence between the operating parameters and the dust removal parameters is established. Finally, the constructed dynamic influence relationship is used to control the dust removal process of the fan, ensuring the dust removal effect of the fan.

[0049] The method step 600 provided in this embodiment further includes:

[0050] Step 610: Collect and obtain the existing operating status parameter distribution of the wind turbine;

[0051] Step 620: Input the existing operating status parameter distribution into the dynamic influence relationship to obtain the existing dust removal influence parameters;

[0052] Step 630: Utilize the parameter differences between the existing dust removal influence parameters and the preset standard dust removal parameters to perform intelligent control of the fan.

[0053] Specifically, the existing operating state parameter distribution of the fan is collected, that is, the operating parameters of the fan under its current state are collected. Then, the existing operating state parameter distribution is input into the dynamic influence relationship, and the existing dust removal influence parameters are obtained according to the dynamic influence relationship. These existing dust removal influence parameters are the dust removal environmental parameters obtained under the current fan operating state parameters. Subsequently, based on the parameter difference between the existing dust removal influence parameters and the preset standard dust removal parameters, the environmental difference between the dust removal environmental parameters obtained under the current fan operating state parameters and the preset standard dust removal parameters is obtained. Intelligent control of the fan dust removal process is then performed based on the environmental difference and the dynamic influence relationship.

[0054] In summary, the method provided in this application collects application environment information of the fan and sets standard dust removal parameters based on this information to obtain preset standard dust removal parameters. Subsequently, the real-time operating status of the fan is collected to obtain a set of real-time operating status parameters. By extracting the main features of the real-time operating status parameter set, the operating parameters with a high correlation to the preset standard dust removal parameters are extracted to obtain the target operating status parameters. Then, a dynamic influence relationship between the target operating status parameters and the preset standard dust removal parameters is constructed based on the correlation of the target operating status parameters. By utilizing environmental differences combined with the dynamic influence relationship, the fan is controlled, further ensuring the dust removal effect of the fan. This solves the technical problem in the prior art where the dust removal parameters of the fan cannot be adjusted according to the actual operating environment, resulting in poor dust removal performance.

[0055] Example 2

[0056] Based on the same inventive concept as the automatic control method for a wind turbine operating condition in the foregoing embodiments, such as Figure 4 As shown, this application provides an automatic control system for wind turbine operating conditions, the system comprising:

[0057] Data acquisition module 11 is used to collect information about the application environment of the wind turbine;

[0058] The preset standard dust removal parameter acquisition module 12 is used to obtain preset standard dust removal parameters by setting standard dust removal parameters based on the application environment information;

[0059] The status parameter set acquisition module 13 is used to collect parameters of the real-time operating status of the fan to obtain a real-time operating status parameter set.

[0060] The target operating status parameter acquisition module 14 is used to obtain the target operating status parameters by extracting the main features of the real-time operating status parameter set, wherein the target operating status parameters have a direct correlation with the preset standard dust removal parameters;

[0061] The dynamic influence relationship construction module 15 is used to construct the dynamic influence relationship between the target operating state parameters and the preset standard dust removal parameters;

[0062] The intelligent control module 16 is used to control the fan by utilizing the dynamic influence relationship.

[0063] Furthermore, the target operating state parameter acquisition module 14 is also used for:

[0064] The correlation between each operating status parameter and the preset standard dust removal parameter is collected from the real-time operating status parameter set to obtain the correlation distribution of each operating status parameter and the standard dust removal parameter.

[0065] The target operating state parameters can be obtained by filtering the correlation distribution of each operating state parameter and the standard dust removal parameter using a preset correlation value.

[0066] Furthermore, the target operating state parameter acquisition module 14 is also used for:

[0067] By collecting standard dust removal parameters at historical time points for the aforementioned fan, the distribution of standard dust removal parameters at each historical time point can be obtained;

[0068] For each historical node standard dust removal parameter distribution, the historical operating parameters of the fan are collected for each distribution parameter to obtain the set of historical operating parameters for each node;

[0069] By performing intersection processing on the historical operating parameter sets of each node, an intersection parameter feature set is obtained;

[0070] Using the intersection parameter feature set, the correlation distribution between each operating state parameter and the standard dust removal parameter is calculated.

[0071] Furthermore, the dynamic influence relationship construction module 15 is also used for:

[0072] The influence weight distribution of each operating state parameter on the preset standard dust removal parameter is collected and obtained respectively among the target operating state parameters;

[0073] Based on the distribution of the weights of each influence, the preset standard dust removal parameters are weighted to obtain the influence coefficients of each operating state.

[0074] The dynamic influence relationship is constructed using the influence coefficients of each operating state.

[0075] Furthermore, the dynamic influence relationship construction module 15 is also used for:

[0076] Construct a weight allocation channel, wherein the weight allocation channel includes several sub-channels;

[0077] The various operating status parameters are sequentially input into the several sub-channels for weight allocation;

[0078] Obtain the weight allocation result, which includes the distribution of the weight percentage of each influence.

[0079] Furthermore, the intelligent control module 16 is also used for:

[0080] The existing operating status parameter distribution of the wind turbine was collected;

[0081] The existing operating status parameters are distributed and input into the dynamic influence relationship to obtain the existing dust removal influence parameters;

[0082] The fan is intelligently controlled by utilizing the parameter differences between the existing dust removal influence parameters and the preset standard dust removal parameters.

[0083] The above-described Embodiment 2 is used to execute the method as described in Embodiment 1. Its execution principle and basis can be obtained from the content described in Embodiment 1, and will not be elaborated further here. Although this application has been described in conjunction with specific features and embodiments, this application is not limited to the exemplary embodiments described herein. Based on the embodiments of this application, those skilled in the art can make various modifications and variations to this application without departing from the scope of this application, and the content obtained in this way also falls within the protection scope of this application.

Claims

1. A method for automatically controlling the operating condition of a fan, characterized in that, The method is applied to an automatic control system, and the method includes: Collect information on the application environment of the fan; By setting standard dust removal parameters based on the application environment information, preset standard dust removal parameters are obtained; The real-time operating status of the fan is collected to obtain a set of real-time operating status parameters; By extracting the main features from the set of real-time operating status parameters, the target operating status parameters can be obtained, wherein the target operating status parameters have a direct correlation with the preset standard dust removal parameters. Construct the dynamic influence relationship between the target operating state parameters and the preset standard dust removal parameters; The fan is controlled using the aforementioned dynamic influence relationship; The main feature extraction is performed on the set of real-time operating status parameters, including: The correlation between each operating status parameter and the preset standard dust removal parameter is collected from the real-time operating status parameter set to obtain the correlation distribution of each operating status parameter and the standard dust removal parameter. The target operating state parameters can be obtained by filtering the correlation distribution of each operating state parameter and the standard dust removal parameter using a preset correlation value. By collecting standard dust removal parameters at historical time points for the aforementioned fan, the distribution of standard dust removal parameters at each historical time point can be obtained; For each historical node standard dust removal parameter distribution, the historical operating parameters of the fan are collected for each distribution parameter to obtain the set of historical operating parameters for each node; By performing intersection processing on the historical operating parameter sets of each node, an intersection parameter feature set is obtained; Using the intersection parameter feature set, the correlation distribution between each operating state parameter and the standard dust removal parameter is calculated; Constructing the dynamic influence relationship between the target operating state parameters and the preset standard dust removal parameters includes: The influence weight distribution of each operating state parameter on the preset standard dust removal parameter is collected and obtained respectively among the target operating state parameters; Based on the distribution of the weights of each influence, the preset standard dust removal parameters are weighted to obtain the influence coefficients of each operating state. The dynamic influence relationship is constructed using the influence coefficients of each operating state.

2. The method of claim 1, wherein, The method includes: Construct a weight allocation channel, wherein the weight allocation channel includes several sub-channels; The various operating status parameters are sequentially input into the several sub-channels for weight allocation; Obtain the weight allocation result, which includes the distribution of the weight percentage of each influence.

3. The method of claim 2, wherein, Controlling the fan includes: The existing operating status parameter distribution of the wind turbine was collected; The existing operating status parameters are distributed and input into the dynamic influence relationship to obtain the existing dust removal influence parameters; The fan is intelligently controlled by utilizing the parameter differences between the existing dust removal influence parameters and the preset standard dust removal parameters.

4. An automatic control system for fan operation, characterized in that, The system is used to execute an automatic control method for a wind turbine operating condition as described in any one of claims 1-3, the system comprising: The data acquisition module is used to collect information about the application environment of the wind turbine. The preset standard dust removal parameter acquisition module is used to obtain preset standard dust removal parameters by setting standard dust removal parameters based on the application environment information; The status parameter set acquisition module is used to collect parameters of the real-time operating status of the fan to obtain a real-time operating status parameter set. The target operating status parameter acquisition module is used to obtain the target operating status parameters by extracting the main features of the real-time operating status parameter set, wherein the target operating status parameters have a direct correlation with the preset standard dust removal parameters; The dynamic influence relationship construction module is used to construct the dynamic influence relationship between the target operating state parameters and the preset standard dust removal parameters; The intelligent control module is used to control the fan by utilizing the dynamic influence relationship.

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