Method and device for controlling air pressure of material grinding machine and electronic equipment

Abstract

The invention discloses a material grinding machine air pressure control method and device and electronic equipment. Relates to the big data field. The method comprises the steps that characteristic values of M target characteristics of the material grinding machine and a preset value of the opening degree of a capacity air door baffle of the material grinding machine are obtained; inputting the characteristic values of the M target characteristics and a preset value of the opening degree of the capacity air door baffle into a target prediction model to obtain a target prediction result; and determining a primary air mother pipe pressure value of the material grinding machine according to the target prediction result, and controlling the mother pipe pressure value of the material grinding machine according to the primary air mother pipe pressure value. By means of the method, the problem that the adjustment range of the coal output amount automatically adjusted by adjusting the opening degree of the capacity air door baffle is small in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the field of big data, and more specifically, to a method, device and electronic device for controlling the wind pressure of a material grinder. Background Art

[0002] In the existing coal processing technology field, adjusting the coal output of the coal mill has become a key operation. Its efficiency and accuracy are directly related to the amount of coal entering the boiler, which in turn affects the boiler output load. In order to ensure that the coal mill can accurately adjust the output coal according to the boiler output load and reduce labor costs, the industry widely adopts the method of automatically controlling the opening of the capacity damper to achieve automatic adjustment of the coal output. This technological innovation not only significantly reduces the frequency and intensity of manual intervention, but also ensures the stability of the coal output by accurately controlling the damper opening.

[0003] However, although the method of automatically controlling the capacity damper opening works well in most cases, it also faces limitations that cannot be ignored. Specifically, when the damper opening reaches its physical or design limit, the system loses the ability to make further adjustments and cannot respond immediately to sudden changes in coal output or special needs. This situation undoubtedly limits the flexibility and response speed of the system, making it difficult to quickly and accurately adjust the coal output under emergency or special conditions, which may have an adverse impact on production efficiency and product quality.

[0004] With regard to the problem that the adjustment range of automatically adjusting the coal output by adjusting the opening of the capacity damper in the related art is small, no effective solution has been proposed yet. Summary of the invention

[0005] The present application provides a method, device and electronic device for controlling the wind pressure of a material grinder, so as to solve the problem in the related art that the adjustment range of the coal output amount is small by automatically adjusting the opening of the capacity damper.

[0006] According to one aspect of the present application, a method for controlling the air pressure of a material grinder is provided. The method comprises: obtaining characteristic values ​​of M target characteristics of the material grinder and a preset value of the opening of a capacity damper of the material grinder, wherein M is a positive integer; inputting the characteristic values ​​of the M target characteristics and the preset value of the opening of the capacity damper into a target prediction model to obtain a target prediction result; determining a primary air main pipe pressure value of the material grinder according to the target prediction result, and controlling the main pipe pressure value of the material grinder according to the primary air main pipe pressure value.

[0007] Optionally, before obtaining the characteristic values ​​of the M target characteristics, the method further includes: when the material grinder is in operation, obtaining a plurality of initial characteristics with operating parameters in the material grinder; and determining the target characteristics from the plurality of initial characteristics to obtain the M target characteristics.

[0008] Optionally, determining the target feature from multiple initial features to obtain M target features includes: when the material grinder is running, obtaining the initial feature value of each initial feature of the material grinder to obtain Q groups of initial feature values, wherein each group of feature values ​​corresponds to an acquisition period, and Q is a positive integer; preprocessing the Q groups of initial feature values ​​to obtain Q groups of processed initial feature values; performing principal component analysis on the Q groups of processed initial feature values ​​according to the steam flow rate of the boiler, obtaining M target feature values ​​from the multiple initial features according to the analysis results, and determining the initial features corresponding to the M target feature values ​​as the target features.

[0009] Optionally, the target prediction model is trained in the following manner: obtaining historical characteristic values ​​of the target characteristics of the material grinder in each sampling period to obtain N groups of historical characteristic values, wherein the target characteristics include at least one of the following: the primary air main pressure value of the material grinder, the number of material grinders, and the steam flow rate of the boiler; obtaining the capacity damper opening of the material grinder in each sampling period to obtain N historical damper openings, where N is a positive integer; associating a group of historical characteristic values ​​and historical input quantities in the same sampling period to obtain N groups of sample data; using the N groups of sample data to train the initial prediction model, and adjusting the parameters of the initial prediction model until the prediction accuracy of the initial prediction model is greater than the preset accuracy to obtain the target prediction model.

[0010] Optionally, determining the primary air main pressure value of the material grinder according to the target prediction result includes: determining the current pressure value of the primary air main of the material grinder; calculating the difference between the current pressure value and the target prediction result; determining the configuration method of the primary air main pressure value of the material grinder according to the difference, and configuring the primary air main pressure value of the material grinder according to the configuration method.

[0011] Optionally, the configuration method for determining the primary air main pressure value of the material grinder according to the difference degree includes: judging whether the difference degree between the current pressure value and the target prediction result is greater than or equal to the preset difference degree; when the difference degree is less than the preset difference degree, determining the configuration method as the first configuration method, wherein the first configuration method refers to changing the primary air main pressure value from the current pressure value to the predicted pressure value in the target prediction result; when the difference degree is greater than or equal to the preset difference degree, determining the configuration method as the second configuration method, wherein the second configuration method refers to generating a pressure value change curve according to the current pressure value and the predicted pressure value, and changing the primary air main pressure value from the current pressure value to the predicted pressure value in the target prediction result according to the pressure value change curve.

[0012] Optionally, the method also includes: obtaining the capacity damper damper opening of the material grinder, and determining whether the capacity damper damper opening is within a preset opening range; when the capacity damper damper opening is not within the preset opening range, executing the step of obtaining characteristic values ​​of M target characteristics of the material grinder and a preset value of the capacity damper damper opening of the material grinder; when the capacity damper damper opening is within the preset opening range, maintaining the primary air main pipe pressure value of the material grinder unchanged.

[0013] According to another aspect of the present application, a control device for the air pressure of a material grinder is provided. The device comprises: a first acquisition unit, used to acquire the characteristic values ​​of M target characteristics of the material grinder and the preset value of the capacity damper damper opening of the material grinder, wherein M is a positive integer; a prediction unit, used to input the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening into a target prediction model to obtain a target prediction result; a first determination unit, used to determine the primary air main pipe pressure value of the material grinder according to the target prediction result, and control the main pipe pressure value of the material grinder according to the primary air main pipe pressure value.

[0014] According to another aspect of the present invention, a computer program product is also provided, including a computer program, which, when executed by a processor, implements a method for controlling the wind pressure of a material grinder provided in the aforementioned embodiment of the present application.

[0015] According to another aspect of the present invention, there is also provided an electronic device comprising one or more processors and a memory; the memory stores computer-readable instructions, and the processor is used to execute the computer-readable instructions, wherein when the computer-readable instructions are executed, a method for controlling the wind pressure of a material grinder provided in the aforementioned embodiment is executed.

[0016] Through this application, the following steps are adopted: obtaining the characteristic values ​​of M target features of the material grinder and the preset value of the capacity damper damper opening of the material grinder, wherein M is a positive integer; inputting the characteristic values ​​of the M target features and the preset value of the capacity damper damper opening into the target prediction model to obtain the target prediction result; determining the primary air main pipe pressure value of the material grinder according to the target prediction result, and controlling the main pipe pressure value of the material grinder according to the primary air main pipe pressure value. The problem of the small adjustment range of the automatic adjustment of the coal output by adjusting the capacity damper damper opening in the related art is solved. By judging the primary air main pipe pressure value that the coal mill currently needs to set according to the preset value of the capacity damper damper opening and the target feature of the material grinder, the capacity damper damper opening is maintained near the preset value according to the adjustment of the primary air main pipe pressure value, thereby ensuring that in the case of a sudden change in the coal output, the capacity damper damper opening can be quickly adjusted to follow the coal output demand, and the capacity damper damper opening is stabilized at the preset value by adjusting the primary air main pipe pressure value. This achieves the effect of ensuring the accuracy and stability of the coal output while ensuring that the opening of the capacity air door damper is stable at a preset value. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 is a flow chart of a method for controlling wind pressure of a material grinder provided in an embodiment of the present application;

[0019] Figure 2 is a flowchart of an optional process for selecting a principal component feature according to an embodiment of the present application;

[0020] Figure 3 is a schematic diagram of a control device for wind pressure of a material grinder provided in an embodiment of the present application;

[0021] Figure 4 It is a schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] It should be noted that the material grinder wind pressure control method, device and electronic equipment determined in the present disclosure can be used in the field of big data, and can also be used in any field except the field of big data. The application field of the material grinder wind pressure control method, device and electronic equipment determined in the present disclosure is not limited.

[0026] It should be noted that the collected information, user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) used in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with the relevant laws, regulations and standards of the relevant regions, necessary confidentiality measures are taken, and public order and good customs are not violated. Corresponding operation portals are provided for users to choose to authorize or refuse to use. For example, an interface is set up between this system and relevant users or organizations. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0027] The embodiments or examples of the present disclosure are not exhaustive, but are only illustrative of some embodiments or examples, and are not intended to be specific limitations on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment or example can be implemented as an independent example, and the steps can be combined arbitrarily. For example, the scheme after removing some steps in a certain embodiment or example can also be implemented as an independent example, and the order of the steps in a certain embodiment or example can be arbitrarily exchanged. In addition, the optional methods or optional examples in a certain embodiment or example can be combined arbitrarily; in addition, the various embodiments or examples can be combined arbitrarily, for example, some or all steps of different embodiments or examples can be combined arbitrarily, and a certain embodiment or example can be combined arbitrarily with the optional methods or optional examples of other embodiments or examples.

[0028] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0029] Principal Component Analysis: Principal Component Analysis (PCA) is a widely used statistical method, mainly used for data dimensionality reduction, feature extraction and data compression.

[0030] Capacity damper opening: The capacity damper opening refers to the degree of opening of the damper used to regulate the flow of media (such as air, flue gas, etc.) in boilers or related industrial equipment. This opening is usually expressed as a percentage, ranging from 0% (fully closed) to 100% (fully open).

[0031] Coal mill: Coal mill is a mechanical equipment that crushes coal blocks and grinds them into coal powder. It is an important auxiliary equipment for pulverized coal furnaces.

[0032] Primary air main pipe pressure value: The primary air main pipe pressure value of the coal mill refers to the gas pressure in the primary air main pipe of the coal mill system. This pressure value is an important parameter in the operation of the coal mill, which directly affects the performance of the coal mill, the transportation and combustion of coal powder.

[0033] According to an embodiment of the present application, a method for controlling the wind pressure of a material grinder is provided.

[0034] Figure 1 1 is a flow chart of a method for controlling the wind pressure of a material grinding machine according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0035] Step S101, acquiring characteristic values ​​of M target characteristics of a material grinder and a preset value of a capacity damper baffle opening of the material grinder, wherein M is a positive integer.

[0036] Specifically, the material grinding machine may be a coal mill, such as a double-inlet and double-outlet ball mill, and the coal output from the coal mill is input into the boiler, thereby ensuring that the boiler can operate normally and ensure normal steam output. The target feature may include feature information related to the coal mill, such as the steam flow rate of the boiler, the number of coal mills, etc.

[0037] Furthermore, when the output load of the boiler changes, in order to ensure that the capacity damper opening of the material grinder is maintained at a preset value, the primary air main pipe pressure value needs to be adjusted, thereby ensuring that the capacity damper opening of the material grinder can be maintained at a preset value when the output load of the boiler meets user requirements.

[0038] It should be noted that, when the capacity damper opening is maintained at a preset value, when the boiler output load changes, the capacity damper damper opening of the material grinder is adjusted first. However, when the capacity damper damper opening of the material grinder is too large, the capacity damper damper of the material grinder may be unable to be adjusted. Therefore, in order to avoid the above situation, it is necessary to obtain the characteristic values ​​of the M target characteristics of the material grinder and the preset value of the capacity damper damper opening of the material grinder, and then calculate the primary air main pressure value based on the characteristic values ​​of the M target characteristics of the material grinder and the preset value of the capacity damper damper opening of the material grinder, and then ensure that the capacity damper damper opening is maintained at the preset value by adjusting the primary air main pressure value.

[0039] Step S102, inputting the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening into the target prediction model to obtain the target prediction result.

[0040] Specifically, after obtaining the characteristic value and the preset value, since the target prediction model contains a fitting equation for calculating the primary air main pipe pressure value, the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening can be input into the target prediction model, and then the characteristic value and the preset value are calculated by the target prediction model to obtain the prediction result, wherein the prediction result is also the set value of the primary air main pipe pressure value calculated by the model according to the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening.

[0041] It should be noted that the model formula in the target prediction model can be shown as Formula 1:

[0042] P s =a0+a1D+a2N+a3O+a4D 2 +a5N 2 +a6O 2 (1)

[0043] Among them, P sis the set value of primary air main pipe pressure, D is the steam flow rate, N is the number of coal mills in operation, and O is the average opening value of the capacity damper.

[0044] Step S103, determining the primary air main pipe pressure value of the material grinder according to the target prediction result, and controlling the main pipe pressure value of the material grinder according to the primary air main pipe pressure value.

[0045] Specifically, after obtaining the target prediction result through the target prediction model, the pressure value contained in the target prediction result can be determined as the primary air main pipe pressure value of the material grinder at the current moment, and the main pipe pressure value of the material grinder can be set according to the pressure value, thereby ensuring that under the pressure setting value, the coal mill can ensure that the output load of the boiler can meet the user's set requirements when the average opening value of the capacity damper is a preset value, thereby ensuring the normal operation of the boiler when the average opening value of the capacity damper of the coal mill is a preset value. At the same time, when the boiler needs to increase or reduce the output load, the average opening value of the capacity damper can be immediately modified to ensure that the boiler output load can be changed in time.

[0046] The control method of the wind pressure of a material grinder provided in the embodiment of the present application obtains the characteristic values ​​of M target features of the material grinder and the preset value of the capacity damper damper opening of the material grinder, wherein M is a positive integer; the characteristic values ​​of the M target features and the preset value of the capacity damper damper opening are input into the target prediction model to obtain the target prediction result; the primary air main pipe pressure value of the material grinder is determined according to the target prediction result, and the main pipe pressure value of the material grinder is controlled according to the primary air main pipe pressure value. The problem of the small adjustment range of the automatic adjustment of the coal output by adjusting the capacity damper damper opening in the related art is solved. The primary air main pipe pressure value that the coal mill currently needs to set is determined according to the preset value of the capacity damper damper opening and the target feature of the material grinder, so that the capacity damper damper opening is maintained near the preset value according to the adjustment of the primary air main pipe pressure value, thereby ensuring that in the case of a sudden change in the coal output, the capacity damper damper opening can be quickly adjusted according to the coal output demand, and the capacity damper damper opening is stabilized at the preset value by adjusting the primary air main pipe pressure value. This achieves the effect of ensuring the accuracy and stability of the coal output while ensuring that the opening of the capacity air door damper is stable at a preset value.

[0047] In order to reduce the number of features that need to be analyzed, optionally, in the material grinder wind pressure control method provided in the embodiment of the present application, before obtaining the characteristic values ​​of M target features, the method also includes: when the material grinder is in an operating state, obtaining multiple initial features with operating parameters in the material grinder; determining the target feature from the multiple initial features to obtain M target features.

[0048] Specifically, during the continuous operation of the material grinder, a series of operating parameters and configuration parameters will be involved, which directly reflect the operating status, performance and configuration information of the equipment. In order to obtain the operating characteristics that are highly correlated with the boiler load, it is first necessary to obtain the initial data of these parameter information. These initial characteristics include but are not limited to the current and speed of the motor, the temperature and pressure of the grinding chamber, the distribution and movement state of the grinding medium, as well as the flow rate and particle size changes of the material, the number of coal mills, and the running time of the coal mills. Through high-precision sensors and real-time data acquisition systems, these initial characteristics can be accurately captured, providing a solid foundation for subsequent data analysis, feature extraction and optimization control.

[0049] Furthermore, after determining the initial characteristics of the coal mill, the characteristic values ​​corresponding to each initial characteristic can be obtained by querying from the configuration information table and measuring the operating parameters, and then the characteristic values ​​of each characteristic at different operating times can be used to determine the characteristic that has the greatest impact on the boiler output power, thereby determining the target characteristic from multiple initial characteristics, and then determining the output load of the boiler based on the characteristic value of the target characteristic.

[0050] In order to ensure the accuracy of the selected target features, optionally, Figure 2 is a flowchart of an optional process for selecting a principal component feature according to an embodiment of the present application, such as Figure 2 As shown, in the method for controlling the wind pressure of a material grinder provided in an embodiment of the present application, a target feature is determined from a plurality of initial features, and the obtained M target features include:

[0051] Step S201, when the material grinder is running, the initial characteristic value of each initial characteristic of the material grinder is obtained to obtain Q groups of initial characteristic values, wherein each group of characteristic values ​​corresponds to a collection period, and Q is a positive integer.

[0052] Step S202, preprocessing the Q groups of initial eigenvalues ​​to obtain the Q groups of processed initial eigenvalues.

[0053] Step S203, performing principal component analysis on the processed initial eigenvalues ​​of group Q according to the steam flow of the boiler, obtaining M target eigenvalues ​​from the multiple initial features according to the analysis results, and determining the initial features corresponding to the M target eigenvalues ​​as the target features.

[0054] It should be noted that in industrial production, the output load of the boiler is affected by multiple initial features, among which the most important feature is the coal output of the coal mill, and the coal output of the coal mill is also affected by multiple initial features (such as raw material type, raw material humidity, grinding time, grinder temperature, motor current, etc.). Therefore, in order to ensure the accuracy of the output load of the boiler, it is necessary to screen out the target features that have a significant impact on the output from the numerous initial features. This embodiment will explain in detail how to determine the target features from the multiple initial features when the coal mill is running.

[0055] Specifically, first, when the coal mill is running, it is necessary to set up sensors, instruments and other equipment in the coal mill, or to obtain the initial characteristic value of each initial characteristic in real time in the control device of the coal mill, and divide the collected data into Q collection time periods in chronological order, each time period corresponds to a group of initial characteristic values, and a total of Q groups of initial characteristic values ​​are obtained.

[0056] Furthermore, it is necessary to clean the initial eigenvalues ​​of group Q, remove missing values, outliers and other data that do not meet the requirements, encode non-numerical features, and standardize or normalize numerical features to eliminate the influence of different feature dimensions, so as to obtain the initial eigenvalues ​​of group Q after processing.

[0057] Furthermore, after obtaining the initial eigenvalues ​​after the Q groups are processed, it is necessary to perform principal component analysis on the initial eigenvalues ​​after the Q groups are processed, so as to map the high-dimensional data to a low-dimensional space while retaining the main information of the data. In the principal component analysis process, it is necessary to calculate the covariance matrix of the initial eigenvalues ​​after the Q groups are processed, and solve the eigenvalues ​​and eigenvectors of the matrix, and select the first M most important eigenvectors (i.e., principal components) according to the size of the eigenvalues. The initial features corresponding to these eigenvectors are the target features, wherein the size of the eigenvalues ​​in the principal component analysis process reflects the importance of the eigenvectors in the data.

[0058] Finally, according to the results of principal component analysis, the initial features corresponding to the M target eigenvalues ​​are determined as target features, thereby obtaining the key features that affect the output load of the boiler.

[0059] It should be noted that in the present technical solution, after obtaining the target feature, the feature with the largest adjustable range can be selected, such as the primary air main pressure value of the material grinder, as the final predicted value, so as to adjust the feature to ensure that after the user sets the output load of the boiler, the actual output load of the boiler can be adjusted to the user's set value by adjusting the characteristic value of the feature.

[0060] This embodiment uses principal component analysis to effectively determine the target feature from multiple initial features of the material grinder during operation, providing strong support for subsequent prediction and evaluation work.

[0061] Optionally, in the material grinder wind pressure control method provided in the embodiment of the present application, the target prediction model is trained in the following manner: obtaining historical characteristic values ​​of the target characteristics of the material grinder in each sampling period to obtain N groups of historical characteristic values, wherein the target characteristics include at least one of the following: the primary air main pipe pressure value of the material grinder, the number of material grinders, and the steam flow rate of the boiler; obtaining the capacity damper opening of the material grinder in each sampling period to obtain N historical damper openings, where N is a positive integer; associating a group of historical characteristic values ​​and historical input quantities in the same sampling period to obtain N groups of sample data; using the N groups of sample data to train the initial prediction model, and adjusting the parameters of the initial prediction model until the prediction accuracy of the initial prediction model is greater than the preset accuracy to obtain the target prediction model.

[0062] It should be noted that the sampling period can be any period when the coal mill is in operation. In this sampling period, the characteristic value corresponding to the target feature (including the capacity damper damper opening) and the steam flow of the boiler in each sampling period are obtained, so that the primary air main pipe pressure value of the material grinder, the number of material grinders, the steam flow of the boiler and the capacity damper damper opening are used as variables for model training, so as to obtain the target prediction model that predicts the primary air main pipe pressure value of the material grinder from the number of material grinders, the steam flow of the boiler and the capacity damper damper opening.

[0063] Specifically, when training the target prediction model, the operation data of the coal mill can be obtained from the historical database, including various characteristic values ​​during each operation (such as the primary air main pipe pressure value of the coal mill, the number of coal mills, the steam flow of the boiler, and the opening of the capacity damper), to obtain multiple groups of historical data, and remove missing values, outliers and other data that do not meet the requirements from the historical data to ensure data quality, and encode non-numerical features according to business needs and model characteristics to ensure that the model can read historical data, thereby obtaining multiple groups of sample data.

[0064] It should be noted that although some data are not missing, they are erroneous values ​​and may not be identified, resulting in errors in the model prediction values. In this case, after obtaining the eigenvalues ​​of each feature, the erroneous values ​​in the eigenvalues ​​can be determined based on the change dimensions and change rules between the eigenvalues, thereby ensuring the accuracy of the eigenvalues.

[0065] Furthermore, after obtaining multiple groups of sample data, the multiple groups of sample data can be divided into training sets, validation sets and test sets, usually in a ratio of 7:2:1 or adjusted according to specific circumstances, and a suitable prediction model is selected according to the nature of the problem and the characteristics of the data, such as linear regression, decision tree, random forest, gradient boosting tree, neural network, etc., so as to train the selected model using the training set data, optimize the model performance by adjusting the model parameters (such as learning rate, number of trees, depth of trees, etc.), and further evaluate the trained model using the validation set, and evaluate the model performance by calculating the prediction error (such as mean square error, mean absolute error, etc.). If the model performance does not meet the requirements, return to the model training step for adjustment, so as to obtain a model with more accurate prediction values, and obtain the target prediction model.

[0066] This embodiment achieves the technical effect of improving the prediction accuracy of the model by acquiring the operating data in the historical operating period and then training the model based on the sample data obtained from the operating data.

[0067] In order to ensure the normal operation of the coal mill. Optionally, in the material grinder air pressure control method provided in the embodiment of the present application, determining the primary air main pipe pressure value of the material grinder according to the target prediction result includes: determining the current pressure value of the primary air main pipe of the material grinder; calculating the difference between the current pressure value and the target prediction result; determining the configuration method of the primary air main pipe pressure value of the material grinder according to the difference, and configuring the primary air main pipe pressure value of the material grinder according to the configuration method.

[0068] Specifically, after obtaining the target prediction result, since the target prediction result includes the primary air main pressure value required to keep the capacity damper damper opening at a preset value, the primary air main pressure value may have a difference with the currently set primary air main pressure value. When adjusting the primary air main pressure value, it is necessary to determine the configuration method of the pressure value based on the difference between the current pressure value and the target prediction result, so as to avoid abnormalities in the coal mill equipment due to excessive changes in the primary air main pressure value.

[0069] In order to accurately determine the configuration mode of the primary air main pressure value, optionally, in the material grinder air pressure control method provided in the embodiment of the present application, the configuration mode of determining the primary air main pressure value of the material grinder according to the difference degree includes: judging whether the difference degree between the current pressure value and the target prediction result is greater than or equal to the preset difference degree; when the difference degree is less than the preset difference degree, determining the configuration mode as the first configuration mode, wherein the first configuration mode refers to changing the primary air main pressure value from the current pressure value to the predicted pressure value in the target prediction result; when the difference degree is greater than or equal to the preset difference degree, determining the configuration mode as the second configuration mode, wherein the second configuration mode refers to generating a pressure value change curve according to the current pressure value and the predicted pressure value, and changing the primary air main pressure value from the current pressure value to the predicted pressure value in the target prediction result according to the pressure value change curve.

[0070] It should be noted that in this technical solution, it is first necessary to calculate the difference between the current pressure value and the target prediction result, wherein the difference can be calculated by the following steps: First, obtain the real-time current pressure value of the primary air main pipe, which reflects the actual operating status of the current system. Then, obtain the predicted pressure value in the target prediction result from the prediction model or algorithm, and then use the preset calculation method (such as absolute value difference, square difference, percentage difference, etc.) to calculate the difference between the current pressure value and the predicted pressure value.

[0071] Furthermore, after calculating the difference, it is necessary to determine whether the difference between the current pressure value and the target prediction result is greater than or equal to the preset difference, so as to determine the configuration method of the pressure value according to the difference, so as to ensure the normal operation of the coal mill.

[0072] When the calculated difference is less than the preset difference threshold, it indicates that the current pressure value is close to the target prediction result, and the pressure value is within a relatively stable or acceptable fluctuation range. At this time, select the first configuration method for operation: that is, directly change the pressure value of the primary air main pipe from the current pressure value to the predicted pressure value in the target prediction result. This configuration method is simple and direct, and can respond quickly to the prediction results. By directly setting the predicted pressure value, the system can maintain stable operation for a period of time in the future, reducing unnecessary fluctuations and adjustment costs.

[0073] When the calculated difference is greater than or equal to the preset difference threshold, it means that there is a large gap between the current pressure value and the target prediction result, and a more sophisticated and gradual adjustment strategy may be required to ensure a smooth transition of the system. At this time, select the second configuration method for operation: First, generate a pressure value change curve based on the current pressure value and the predicted pressure value. This curve should transition smoothly to avoid the impact of sudden changes in pressure values ​​on the system. Then, according to the change curve, gradually adjust the pressure value of the primary air main pipe from the current value to the predicted value. This method allows the system to maintain a certain stability and controllability during the adjustment process, reducing the risks that may be caused by sudden changes. By precisely controlling the rate and path of change of the pressure value, it can better adapt to the needs of dynamic changes in the system and ensure the stability and efficiency of the system throughout the adjustment process.

[0074] This embodiment determines the configuration mode of the pressure value according to the pressure difference, thereby ensuring the normal operation of the coal mill.

[0075] Optionally, in the material grinder wind pressure control method provided in the embodiment of the present application, the method also includes: obtaining the capacity damper damper opening of the material grinder, and determining whether the capacity damper damper opening is within a preset opening range; when the capacity damper damper opening is not within the preset opening range, executing the step of obtaining characteristic values ​​of M target characteristics of the material grinder and a preset value of the capacity damper damper opening of the material grinder; when the capacity damper damper opening is within the preset opening range, maintaining the primary air main pipe pressure value of the material grinder unchanged.

[0076] Specifically, before changing the primary air main pipe pressure value, it is necessary to determine whether the primary air main pipe pressure value needs to be changed. Therefore, it is necessary to obtain the capacity damper damper opening of the material grinder, and determine whether the capacity damper damper opening of the material grinder is within the preset opening range. When the capacity damper damper opening is within the preset opening range, it indicates that the capacity damper damper opening is at a suitable position. At this time, there is no need to adjust the primary air main pipe pressure value of the material grinder, and the primary air main pipe pressure value of the material grinder can be kept unchanged.

[0077] Furthermore, when the capacity damper opening is not within the preset opening range, it is necessary to change the capacity damper damper opening to the preset opening range by changing the primary air main pipe pressure value of the material grinder, thereby ensuring that the capacity damper damper can perform corresponding change operations when the output load of the boiler changes, thereby ensuring the accuracy of the output load of the boiler.

[0078] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0079] The embodiment of the present application also provides a material grinder wind pressure control device. It should be noted that the material grinder wind pressure control device of the embodiment of the present application can be used to execute the material grinder wind pressure control method provided in the embodiment of the present application. The material grinder wind pressure control device provided in the embodiment of the present application is introduced below.

[0080] Figure 3 Schematic diagram of a device for controlling the wind pressure of a material grinding machine according to an embodiment of the present application. Figure 3 As shown, the device includes: a first acquisition unit 31, a prediction unit 32, and a first determination unit 33.

[0081] The first acquisition unit 31 is used to acquire characteristic values ​​of M target characteristics of the material grinder and a preset value of the opening of the capacity damper of the material grinder, wherein M is a positive integer.

[0082] The prediction unit 32 is used to input the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening into the target prediction model to obtain the target prediction result.

[0083] The first determination unit 33 is used to determine the primary air main pipe pressure value of the material grinder according to the target prediction result, and control the main pipe pressure value of the material grinder according to the primary air main pipe pressure value.

[0084] The control device for the wind pressure of a material grinder provided in the embodiment of the present application obtains the characteristic values ​​of M target characteristics of the material grinder and the preset value of the capacity damper damper opening of the material grinder through the first acquisition unit 31, wherein M is a positive integer; the prediction unit 32 inputs the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening into the target prediction model to obtain the target prediction result; the first determination unit 33 determines the primary air main pipe pressure value of the material grinder according to the target prediction result, and controls the main pipe pressure value of the material grinder according to the primary air main pipe pressure value. The problem of a small adjustment range of the coal output automatically adjusted by adjusting the opening of the capacity damper in the related art is solved. The primary air main pipe pressure value that needs to be set for the coal mill is determined according to the preset value of the capacity damper opening and the target characteristics of the material grinder, so that the capacity damper opening is maintained near the preset value according to the adjustment of the primary air main pipe pressure value, thereby ensuring that in the case of a sudden change in the coal output, the capacity damper opening can be quickly adjusted to follow the coal output demand, and the capacity damper opening is stabilized at the preset value by adjusting the primary air main pipe pressure value. Thus, the accuracy and stability of the coal output are ensured while ensuring that the capacity damper opening is stabilized at the preset value.

[0085] Optionally, in the control device for the wind pressure of a material grinder provided in an embodiment of the present application, before obtaining the characteristic values ​​of M target characteristics, the device also includes: a second acquisition unit, used to obtain multiple initial characteristics with operating parameters in the material grinder when the material grinder is in an operating state; a second determination unit, used to determine the target characteristic from the multiple initial characteristics to obtain M target characteristics.

[0086] Optionally, in the control device for the wind pressure of a material grinder provided in an embodiment of the present application, the second determination unit includes: an acquisition module, used to acquire the initial characteristic value of each initial characteristic of the material grinder when the material grinder is running, and obtain Q groups of initial characteristic values, wherein each group of characteristic values ​​corresponds to an acquisition period, and Q is a positive integer; a processing module, used to preprocess the Q groups of initial characteristic values, and obtain the Q groups of processed initial characteristic values; an analysis module, used to perform principal component analysis on the Q groups of processed initial characteristic values ​​according to the steam flow rate of the boiler, obtain M target characteristic values ​​from multiple initial characteristics according to the analysis results, and determine the initial characteristics corresponding to the M target characteristic values ​​as the target characteristics.

[0087] Optionally, in the control device for the wind pressure of a material grinder provided in an embodiment of the present application, the target prediction model is trained in the following manner: a third acquisition unit is used to obtain the historical characteristic values ​​of the target characteristics of the material grinder in each sampling period, and obtain N groups of historical characteristic values, wherein the target characteristics include at least one of the following: the primary air main pipe pressure value of the material grinder, the number of material grinders, and the steam flow rate of the boiler; a fourth acquisition unit is used to obtain the capacity damper opening of the material grinder in each sampling period, and obtain N historical damper openings, where N is a positive integer; an association unit is used to associate a group of historical characteristic values ​​and historical input quantities in the same sampling period to obtain N groups of sample data; a training unit is used to train the initial prediction model using N groups of sample data, and adjust the parameters of the initial prediction model until the prediction accuracy of the initial prediction model is greater than the preset accuracy, and the target prediction model is obtained.

[0088] Optionally, in the control device for the wind pressure of a material grinder provided in an embodiment of the present application, the first determination unit 33 includes: a determination module, used to determine the current pressure value of the primary air main pipe of the material grinder; a calculation module, used to calculate the difference between the current pressure value and the target prediction result; a configuration module, used to determine the configuration method of the primary air main pipe pressure value of the material grinder according to the difference, and configure the primary air main pipe pressure value of the material grinder according to the configuration method.

[0089] Optionally, in the material grinder wind pressure control device provided in the embodiment of the present application, the configuration module includes: a judgment submodule, used to judge whether the difference between the current pressure value and the target prediction result is greater than or equal to a preset difference; a first determination submodule, used to determine that the configuration mode is the first configuration mode when the difference is less than the preset difference, wherein the first configuration mode refers to changing the primary air main pipe pressure value from the current pressure value to the predicted pressure value in the target prediction result; a second determination submodule, used to determine that the configuration mode is the second configuration mode when the difference is greater than or equal to the preset difference, wherein the second configuration mode refers to generating a pressure value change curve according to the current pressure value and the predicted pressure value, and changing the primary air main pipe pressure value from the current pressure value to the predicted pressure value in the target prediction result according to the pressure value change curve.

[0090] Optionally, in the material grinder wind pressure control device provided in the embodiment of the present application, the device also includes: a judgment unit, used to obtain the capacity damper damper opening of the material grinder, and judge whether the capacity damper damper opening is within a preset opening range; an execution unit, used to execute the step of obtaining the characteristic values ​​of M target characteristics of the material grinder and the preset value of the capacity damper damper opening of the material grinder when the capacity damper damper opening is not within the preset opening range; a maintaining unit, used to keep the primary air main pipe pressure value of the material grinder unchanged when the capacity damper damper opening is within the preset opening range.

[0091] The above-mentioned material grinder wind pressure control device includes a processor and a memory. The above-mentioned first acquisition unit 31, prediction unit 32, first determination unit 33, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0092] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and the problem of a small adjustment range of automatically adjusting the coal output by adjusting the opening of the capacity damper damper in the related art is solved by adjusting the kernel parameters.

[0093] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0094] An embodiment of the present invention provides a computer-readable storage medium on which a program is stored. When the program is executed by a processor, the method for controlling the wind pressure of the material grinder is implemented.

[0095] An embodiment of the present invention provides a processor, which is used to run a program, wherein the method for controlling the wind pressure of the material grinder is executed when the program is run.

[0096] Figure 4 is a schematic diagram of an electronic device provided according to an embodiment of the present application, such as Figure 4 As shown, an embodiment of the present invention provides an electronic device, the electronic device 40 includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor executes the program to implement the steps of the above-mentioned material grinding machine wind pressure control method. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0097] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the steps of the above-mentioned material grinder wind pressure control method.

[0098] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0099] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0100] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0102] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0103] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0104] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0105] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0106] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for controlling the wind pressure of a material grinding machine, characterized in that: include: Acquire characteristic values ​​of M target characteristics of a material grinder and a preset value of a capacity damper baffle opening of the material grinder, wherein M is a positive integer; Inputting the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening into the target prediction model to obtain a target prediction result; The primary air main pipe pressure value of the material grinder is determined according to the target prediction result, and the main pipe pressure value of the material grinder is controlled according to the primary air main pipe pressure value.

2. The method according to claim 1, characterized in that Before obtaining the characteristic values ​​of the M target characteristics of the material grinding machine, the method further includes: When the material grinder is in operation, obtaining a plurality of initial features having operation parameters of the material grinder; Determine the target feature from the multiple initial features to obtain the M target features.

3. The method according to claim 2, characterized in that Determining a target feature from the multiple initial features to obtain the M target features includes: When the material grinder is running, an initial characteristic value of each initial characteristic of the material grinder is obtained to obtain Q groups of initial characteristic values, wherein each group of characteristic values ​​corresponds to a collection period, and Q is a positive integer; Preprocessing the Q groups of initial eigenvalues ​​to obtain Q groups of processed initial eigenvalues; The principal component analysis is performed on the Q group of processed initial characteristic values ​​according to the steam flow of the boiler, M target characteristic values ​​are obtained from the multiple initial characteristics according to the analysis results, and the initial characteristics corresponding to the M target characteristic values ​​are determined as the target characteristics.

4. The method according to claim 1, characterized in that The target prediction model is trained in the following way: Obtain historical characteristic values ​​of the target characteristics of the material grinder in each sampling period to obtain N groups of historical characteristic values, wherein the target characteristics include at least one of the following: a primary air main pipe pressure value of the material grinder, the number of the material grinders, and a steam flow rate of a boiler; Obtaining the capacity damper opening of the material grinder in each sampling period, and obtaining N historical damper openings, where N is a positive integer; A set of historical feature values ​​and historical input quantities in the same sampling period are associated to obtain N sets of sample data; The initial prediction model is trained using the N groups of sample data, and the parameters of the initial prediction model are adjusted until the prediction accuracy of the initial prediction model is greater than a preset accuracy, thereby obtaining the target prediction model.

5. The method according to claim 1, characterized in that Determining the primary air main pipe pressure value of the material grinder according to the target prediction result includes: Determine the current pressure value of the primary air main pipe of the material grinder; Calculating the difference between the current pressure value and the target prediction result; The configuration method of the primary air main pipe pressure value of the material grinder is determined according to the difference, and the primary air main pipe pressure value of the material grinder is configured according to the configuration method.

6. The method according to claim 5, characterized in that The configuration method for determining the primary air main pipe pressure value of the material grinder according to the difference degree includes: Determine whether the difference between the current pressure value and the target prediction result is greater than or equal to a preset difference; When the difference is less than the preset difference, determining that the configuration mode is the first configuration mode, wherein the first configuration mode refers to changing the primary air main pipe pressure value from the current pressure value to the predicted pressure value in the target prediction result; When the difference is greater than or equal to the preset difference, the configuration mode is determined to be the second configuration mode, wherein the second configuration mode refers to generating a pressure value change curve according to the current pressure value and the predicted pressure value, and changing the primary air main pipe pressure value from the current pressure value to the predicted pressure value in the target prediction result according to the pressure value change curve.

7. The method according to claim 1, characterized in that The method further comprises: Obtaining the capacity damper opening of the material grinder, and determining whether the capacity damper opening is within a preset opening range; When the capacity damper opening is not within the preset opening range, performing the step of acquiring the characteristic values ​​of the M target characteristics of the material grinder and the preset value of the capacity damper opening of the material grinder; When the opening of the capacity damper is within the preset opening range, the pressure value of the primary air main pipe of the material grinder is kept unchanged.

8. A device for controlling the wind pressure of a material grinding machine, characterized in that: include: A first acquisition unit is used to acquire characteristic values ​​of M target characteristics of the material grinder and a preset value of the opening of the capacity damper of the material grinder, wherein M is a positive integer; A prediction unit, used for inputting the characteristic values ​​of the M target characteristics and the preset value of the capacity damper damper opening into a target prediction model to obtain a target prediction result; The first determination unit is used to determine the primary air main pipe pressure value of the material grinder according to the target prediction result, and control the main pipe pressure value of the material grinder according to the primary air main pipe pressure value.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for controlling the wind pressure of a material grinder according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the material grinder wind pressure control method described in any one of claims 1 to 7.

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