Dust concentration dynamic warning method and device combined with spray device

Abstract

The present invention discloses a method and device for dynamic early warning of dust concentration in combination with a spray device, and relates to the technical field of dust early warning. The method includes: dividing the dust control area into multiple dust reduction operation sub-areas; configuring multiple water mist spraying operation points; when the integrated control center receives the first dust reduction early warning, edge node identification is performed on the first dust reduction early warning to obtain K concentration over-limit deviations; by performing dust dispersion correlation analysis on the K dust reduction operation sub-areas, edge node interaction permissions are generated; K edge dust reduction control modules receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction permissions. The technical problems in the prior art that the dust early warning response is not timely, the dust reduction operation lacks precision and linkage, resulting in poor dust reduction effect are solved. Through real-time dust concentration monitoring, dispersion correlation analysis and cross-region linkage control, the technical effect of improving the dust early warning response speed and realizing precise dust reduction is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of dust warning, and in particular to a method and a device for dynamic warning of dust concentration combined with a spray device. Background Art

[0002] In working environments such as coal mines, the increase in dust concentration will not only seriously affect the health of workers, but may also cause safety hazards. Therefore, it is crucial to effectively monitor and promptly deal with the dust concentration in the working environment. Existing dust reduction measures usually use fixed spray devices to perform dust reduction treatment through preset parameters. However, this method lacks flexibility and cannot be dynamically adjusted according to the real-time concentration changes of dust. At the same time, dust is easily diffused to other areas under the influence of wind speed and wind direction, causing cross-regional dust diffusion. Existing technologies are difficult to effectively deal with this situation, resulting in unsatisfactory dust reduction effects. In addition, most existing systems are dust reduction control for a single operating point, and cannot achieve cross-regional and multi-point linkage control, which reduces the overall dust reduction efficiency. Summary of the invention

[0003] The present application provides a method and device for dynamic early warning of dust concentration combined with a spray device, which solves the technical problems in the prior art of untimely dust early warning response, lack of precision and linkage in dust reduction operations, and poor dust reduction effects.

[0004] In view of the above problems, the present application provides a method and device for dynamic early warning of dust concentration combined with a spray device.

[0005] In a first aspect of the present application, a method for dynamic early warning of dust concentration in combination with a spray device is provided, the method comprising:

[0006] The dust control area is divided into multiple dust reduction operation sub-areas; multiple water mist spraying operation points are configured for the multiple dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center; when the integrated control center receives a first dust reduction warning, edge node identification is performed on the first dust reduction warning to obtain K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust reduction control modules; the integrated control center generates edge node interaction permissions based on the first dust reduction warning by performing dust dispersion correlation analysis on the K dust reduction operation sub-areas; the K edge dust reduction control modules receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction permissions.

[0007] In a second aspect of the present application, a dust concentration dynamic warning device combined with a spray device is provided, the device comprising:

[0008] An area division component, the area division component is used to divide the dust control area into multiple dust reduction operation sub-areas; a configuration component, the configuration component is used to configure multiple water mist injection operation points for the multiple dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center; an identification component, the identification component is used to perform edge node identification on the first dust reduction warning when the integrated control center receives the first dust reduction warning, and obtain K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust reduction control modules; an analysis component, the analysis component is used for the integrated control center to generate edge node interaction permissions based on the first dust reduction warning by performing dust dispersion correlation analysis on the K dust reduction operation sub-areas; a control component, the control component is used for the K edge dust reduction control modules to receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction permissions.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, the dust control area is divided into multiple dust reduction operation sub-areas. Then, multiple water mist spraying operation points are configured for multiple dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center. When the integrated control center receives the first dust reduction warning, it performs edge node identification on the first dust reduction warning and obtains K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust reduction control modules. Next, the integrated control center generates edge node interaction permissions based on the first dust reduction warning by performing dust dispersion correlation analysis on the K dust reduction operation sub-areas. Finally, the K edge dust reduction control modules receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction permissions. The technical problems in the prior art that the dust warning response is not timely and the dust reduction operation lacks accuracy and linkage, resulting in poor dust reduction effect, are solved. Through real-time dust concentration monitoring, dispersion correlation analysis and cross-region linkage control, the technical effect of improving the dust warning response speed and achieving precise dust reduction is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic diagram of a process flow of a dynamic early warning method for dust concentration in combination with a spray device provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of a dust concentration dynamic warning device combined with a spray device provided in an embodiment of the present application.

[0014] Description of reference numerals: area division component 11 , configuration component 12 , identification component 13 , analysis component 14 , control component 15 . DETAILED DESCRIPTION

[0015] The present application solves the technical problems in the prior art of poor dust reduction effect caused by untimely dust warning response and lack of precision and linkage in dust reduction operations by providing a dust concentration dynamic warning method and device combined with a spray device.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0018] Embodiment 1, as Figure 1 As shown, the present application provides a dust concentration dynamic early warning method combined with a spray device, wherein the method comprises:

[0019] Divide the dust control area into multiple dust reduction operation sub-areas.

[0020] When addressing the challenges of dust pollution, in order to improve the targetedness and efficiency of governance, a larger dust control area can be reasonably divided into multiple dust reduction operation sub-areas based on the geographical characteristics of the mining area or work site, dust concentration distribution, wind speed and direction and other environmental factors.

[0021] Furthermore, the dust control area is divided into a plurality of dust reduction operation sub-areas, and the method includes:

[0022] Interactively obtain regional operating conditions of a dust control area; identify similar areas based on the regional operating conditions to obtain multiple benchmark control parameters for multiple similar control areas; perform weighted calculation of the multiple benchmark control parameters based on multiple dust reduction deviation frequencies of the multiple similar control areas as a dust reduction control baseline for the dust control area; perform dust reduction coverage analysis on the spray device based on the dust reduction control baseline to obtain a spray coverage area; divide the dust control area into the multiple dust reduction operation sub-areas using the spray coverage area as a regional division scale.

[0023] Specifically, the regional operating conditions of the dust control area are obtained through real-time interaction of multimodal sensors, including dust concentration, ambient temperature, humidity, wind speed and direction, and other key factors affecting the dust reduction effect; based on the collected regional operating conditions, multiple control areas with similar operating conditions to the current area are identified through comparison and analysis; corresponding benchmark control parameters are extracted from the identified multiple similar control areas, including the spray intensity, frequency, angle and other operating settings of the spray device, as well as related dust concentration thresholds, etc.; after identifying similar areas, the dust reduction deviation frequency data of these areas are further collected. The dust reduction deviation frequency data reflects the difference between each area and the actual dust reduction process. Deviations between expected control targets; Based on the frequency of dust reduction deviations in similar areas, weighted calculations are performed on multiple benchmark control parameters to determine the dust reduction control baseline that is most suitable for the current dust control area. The dust reduction control baseline reflects the best spray control strategy; Based on the set dust reduction control baseline, the spray coverage capability of the current spray device is analyzed, and the actual coverage area of ​​the spray device under different parameters is calculated; Based on the calculated spray coverage area, the dust control area is divided into multiple dust reduction operation sub-areas. The division of each dust reduction operation sub-area can ensure effective coverage of areas with higher dust concentrations and provide precise target areas for subsequent dust reduction control operations.

[0024] Further, similar regions are identified based on the regional operating conditions to obtain multiple benchmark control parameters of multiple similar control regions, the method includes:

[0025] According to the indicator composition of the regional operating conditions, network data call is performed to obtain multiple sample operating conditions of multiple sample control areas, wherein the regional operating conditions include a baseline dust concentration mean, a baseline dust concentration peak, a baseline particulate matter distribution, a baseline gas concentration mean, a baseline wind speed mean, a baseline relative humidity and a baseline temperature mean; the multiple sample operating conditions and regional operating conditions are introduced into the regional similarity evaluation function for numerical calculation to obtain multiple regional similarity coefficients of the multiple sample control areas; a regional similarity threshold is preset, and the regional similarity threshold is used to traverse the multiple regional similarity coefficients to obtain the multiple similar control areas; dust reduction control information is called for the multiple similar control areas to obtain the multiple benchmark control parameters.

[0026] Specifically, according to the indicator composition of regional operating conditions, such as the mean of baseline dust concentration, the peak of baseline dust concentration, the baseline particle distribution, the mean of baseline gas concentration, the mean of baseline wind speed, the mean of baseline relative humidity and the mean of baseline temperature, etc., network data calls are made to obtain multiple sample operating conditions of multiple sample control areas; the collected multiple sample operating conditions and the operating conditions of the current area are substituted into the preset regional similarity evaluation function for numerical calculation to obtain the regional similarity coefficient of each sample control area; a regional similarity threshold is preset, and the calculated multiple regional similarity coefficients are traversed and screened, and the sample areas whose similarity coefficients meet the threshold are selected to obtain multiple similar control areas with similar operating conditions to the current area; the dust reduction control information of the screened similar control areas is called, and the dust reduction control strategies and their related parameters applied in these similar areas are extracted, and finally multiple benchmark control parameters of the current area are obtained. Further, the regional similarity evaluation function is as follows:

[0027] ;

[0028] ;

[0029] ;

[0030] in, S1 is the one-dimensional similarity coefficient, A1 is the average value of the baseline dust concentration, P1 is the peak value of the baseline dust concentration, PM1 is the benchmark particle distribution, W1 is the mean value of the benchmark gas concentration, A2 is the mean dust concentration of the samples, P2 is the peak value of the sample dust concentration, PM2 is the particle distribution of the sample, W2 is the mean value of sample gas concentration; S2 is the two-dimensional similarity coefficient, V1is the mean base wind speed, H1 is the base relative humidity, Tvag,1 is the mean reference temperature, V2 is the sample wind speed mean, H2 is the sample relative humidity, Tvag,2 is the sample temperature mean; where S is the regional similarity coefficient, ω1 is the one-dimensional weight, ω2 is a two-dimensional weight.

[0031] The regional similarity evaluation function evaluates the similarity between different regions by weighted calculation of one-dimensional and two-dimensional similarity coefficients, taking into account factors such as dust concentration, particle distribution, gas concentration, wind speed, humidity and temperature. Based on the regional similarity evaluation function, it can more accurately identify regions with similar working conditions to the current conditions, thereby providing more accurate reference data for dust control.

[0032] Specifically, the one-dimensional similarity coefficient S1 The three main indicators considered are dust concentration, particle distribution and gas concentration. A1 is the average value of the baseline dust concentration, P1 is the peak value of the baseline dust concentration, PM1 is the benchmark particle distribution, including 1~n particle concentrations, i is one of them, W1 is the mean value of the benchmark gas concentration, A2 is the mean dust concentration of the samples, P2 is the peak value of the sample dust concentration, PM2 is the particle distribution of the sample, W2 is the mean value of sample gas concentration; two-dimensional similarity coefficient S2 The three main indicators considered are wind speed, relative humidity and temperature. V1 is the mean base wind speed, H1 is the base relative humidity, Tvag,1 is the mean reference temperature, V2 is the sample wind speed mean, H2 is the sample relative humidity, Tvag,2 is the mean temperature of the samples.

[0033] A plurality of water mist spraying operation points are configured for the plurality of dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center.

[0034] In each dust reduction operation sub-area, multiple water mist spraying operation points are reasonably arranged according to environmental factors such as dust concentration distribution, particle characteristics, wind speed and direction. These spraying operation points can flexibly adjust the spray intensity and coverage according to the real-time dust concentration to ensure the maximum dust reduction effect. Localized spray devices are deployed at each operation point to enable them to operate independently to ensure accurate water mist spraying control in different sub-areas. These spray devices can work in conjunction with environmental sensors to respond to dust changes in the sub-areas in real time. Each spray device is equipped with an integrated control center to manage the spraying operations of multiple operation points; the integrated control center can collect environmental data such as dust concentration, wind speed and direction from each sub-area, analyze and control the operation of water mist spraying operation points in real time, and ensure that dust reduction operations in the entire area are carried out in a coordinated manner.

[0035] When the integrated control center receives the first dust fall warning, it performs edge node identification on the first dust fall warning to obtain K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust fall control modules.

[0036] The integrated control center receives the first dust fall warning signal of the dust fall operation sub-area. The first dust fall warning signal is usually based on the real-time monitored dust concentration data and is triggered when the data exceeds the preset threshold. After receiving the warning, the warning signal will be analyzed and the edge nodes associated with the warning will be identified. The edge nodes refer to the sub-areas that are greatly affected by the dust concentration or the key positions in the dust diffusion path; through further analysis of the edge nodes, K concentration limit deviation points can be identified. Each deviation point represents the degree to which the dust concentration in the area exceeds the predetermined threshold. These deviations reflect the unbalanced state of dust concentration in the area, which requires adjustment and dust fall intervention. The identified K concentration limit deviation points correspond to K edge dust fall control modules respectively. Each edge dust fall control module is responsible for a specific dust fall operation sub-area or spray device, and can perform independent dust fall control on the sub-area.

[0037] Further, when the integrated control center receives the first dust fall warning, edge node identification is performed on the first dust fall warning to obtain K concentration limit deviations. Before that, the method includes:

[0038] A safe concentration prediction module is pre-constructed, wherein the safe concentration prediction module includes a cascaded safe concentration prediction layer and a concentration extreme value call layer, and the safe concentration prediction layer includes M parallel safe concentration prediction branches; a plurality of sample safety limit value arrays are interactively obtained, wherein each sample safety limit value array includes a sample safe dust concentration, a sample carbon dioxide concentration, a sample ambient temperature and a sample gas concentration; the model parameters of the M safe concentration prediction branches are adjusted using the plurality of sample safety limit value arrays to complete the localization of the safe concentration prediction module, wherein the M safe concentration prediction branches are constructed based on M non-repetitive random operators; a concentration difference calculation unit is interactively obtained, and the construction of a plurality of edge dust reduction control modules is completed by copying the concentration difference calculation unit and the safe concentration prediction module to a plurality of local servers of the plurality of dust reduction operation sub-areas, wherein the integrated control center is communicatively connected with the plurality of local servers; a plurality of dust reduction operation sub-areas are configured with multi-modal sensors according to the dust source to obtain a plurality of multi-modal sensing units, wherein the plurality of multi-modal sensing units are communicatively connected with a plurality of edge dust reduction control modules.

[0039] The safe concentration prediction module consists of a cascaded safe concentration prediction layer and a concentration extreme value call layer, where the safe concentration prediction layer consists of M parallel safe concentration prediction branches, each of which can independently predict the dust concentration threshold under different environments. The safe limit value arrays of multiple samples are obtained interactively, and each safe limit value array includes key parameters such as the safe dust concentration, carbon dioxide concentration, ambient temperature, and gas concentration of the sample; the obtained sample safe limit value arrays are used to adjust the model parameters of the M safe concentration prediction branches to ensure that the safe concentration prediction module can make accurate predictions based on the actual working conditions of different areas. The M safe concentration prediction branches are constructed by M non-repetitive random operators, which ensures the adaptability and flexibility of the model under different working conditions.

[0040] Before building the edge dust control module, it is necessary to obtain a concentration difference calculation unit, which is used to calculate the difference between the real-time monitored dust concentration and the safe dust concentration predicted by the safe concentration prediction module, that is, the concentration over-limit deviation; the concentration difference calculation unit and the safe concentration prediction module are copied to multiple local servers in multiple dust operation sub-areas, so that each dust operation sub-area can have an independent edge dust control module to realize the localization and intelligence of dust control. The integrated control center establishes communication connections with multiple local servers to receive and process the concentration over-limit deviation information from each dust operation sub-area in real time, and issue corresponding dust reduction instructions.

[0041] According to the different sources of dust, multimodal sensors are configured in each dust reduction operation sub-area to form multiple multimodal sensing units. Each sensing unit is connected to the corresponding edge dust reduction control module to collect environmental data such as dust concentration, carbon dioxide concentration, temperature, wind speed, etc., to achieve real-time monitoring and dynamic adjustment.

[0042] Further, when the integrated control center receives the first dust fall warning, edge node identification is performed on the first dust fall warning to obtain K concentration limit deviations, and the method includes:

[0043] The multiple edge dust reduction control modules receive and analyze the multiple multimodal sensing units to perform real-time monitoring on the multiple dust reduction operation sub-areas to obtain multiple real-time environment-related data, and output multiple concentration excess deviations; the K edge dust reduction control modules send the K concentration excess deviations as the first dust reduction warning to the integrated control center, wherein the K concentration excess deviations are positive values.

[0044] Specifically, multiple edge dust reduction control modules receive data from multiple multimodal sensor units, which include real-time monitoring results of multiple dust reduction operation sub-areas, such as dust concentration, carbon dioxide concentration, gas concentration, temperature, humidity, wind speed and other environmental factors; the edge dust reduction control module will use the built-in safety concentration prediction module and concentration difference calculation unit to process the received real-time environment-related data, and calculate the concentration excess deviation by comparing the real-time monitored dust concentration with the safety dust concentration predicted by the safety concentration prediction module based on carbon dioxide concentration, ambient temperature and gas concentration, and generate multiple real-time concentration excess deviations; when the calculated concentration excess deviation is a positive value, it means that the real-time monitored dust concentration exceeds the safety concentration predicted by the safety concentration prediction module, that is, there is a dust reduction demand; once the concentration excess deviation is identified, the edge dust reduction control module will regard it as the trigger condition for the first dust reduction warning; the edge dust reduction control module will send the calculated K concentration excess deviations (all positive values) as the specific content of the first dust reduction warning to the integrated control center through the communication connection.

[0045] The integrated control center generates edge node interaction permissions based on the first dust fall warning by performing dust dispersion correlation analysis on K dust fall operation sub-areas.

[0046] The integrated control center will conduct a correlation analysis of dust dispersion based on real-time multimodal sensor unit data, including environmental parameters such as wind speed and wind direction, combined with the geographical location of each dust reduction operation sub-area and the dust concentration over-limit deviation, in order to predict the flow trend of dust between each sub-area and identify the associated areas that may be affected by dust dispersion. Based on the analysis results of dust dispersion, the integrated control center will determine which edge nodes (i.e., the edge dust reduction control modules of each dust reduction sub-area) need to be coordinated and generate corresponding edge node interaction permissions to allow linkage control between sub-areas affected by dust dispersion. These interaction permissions ensure that each sub-area can coordinate dust reduction based on interrelated data, thereby optimizing dust reduction efficiency and preventing further dust spread. As dust dispersion continues to change, the integrated control center will dynamically adjust the edge node interaction permissions to ensure that the spray devices in each sub-area can adjust the injection parameters according to real-time data to achieve precise dust reduction control.

[0047] Furthermore, the integrated control center generates edge node interaction permissions based on the first dust fall warning by performing dust dispersion correlation analysis on the K dust fall operation sub-areas, and the method includes:

[0048] The integrated control center receives K real-time wind directions of the K dust reduction operation sub-areas; performs dust dispersion association judgment based on the distribution of the K dust reduction operation sub-areas in the dust control area and the K real-time wind directions, and merges the K dust reduction operation sub-areas into N collaborative dust reduction partitions, where N is a positive integer less than K; configures the edge node interaction authority based on the mapping relationship between the N collaborative dust reduction partitions and the K dust reduction operation sub-areas.

[0049] Specifically, the integrated control center receives the real-time wind direction data of K dust reduction operation sub-areas; based on the geographical distribution of the K dust reduction operation sub-areas and their respective real-time wind directions, the dust dispersion trend is judged, the direction in which the dust may spread and the affected areas are predicted, and then the sub-areas with dust dispersion associations are identified; based on the correlation analysis results of dust dispersion, the integrated control center merges the K dust reduction operation sub-areas into N collaborative dust reduction partitions. The merged collaborative partitions share similar dust dispersion paths or are affected by the same wind direction in order to perform coordinated dust reduction control; based on the mapping relationship between the N collaborative dust reduction partitions and the K dust reduction operation sub-areas, the integrated control center configures edge node interaction permissions for these areas. These permissions allow multiple sub-areas to perform collaborative operations to optimize cross-regional dust reduction control strategies and ensure that the dust concentration in each area can be effectively controlled.

[0050] The K edge dust reduction control modules receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction authority.

[0051] Each edge dust reduction control module will receive the corresponding edge node interaction permissions from the integrated control center to clarify its role and responsibilities in the coordinated dust reduction operation. The edge node interaction determines whether the module needs to work with other sub-areas and the intensity and frequency of the dust reduction operation required. According to the interaction permissions assigned by the integrated control center, the K edge dust reduction control modules will adjust the water mist injection parameters of their respective dust reduction operation sub-areas, such as spray intensity, spray direction, spray coverage, etc., to ensure that the dust can be effectively controlled within the sub-area and associated areas. In the dust dispersion associated area, multiple edge dust reduction control modules will synchronously perform dust reduction operations according to the configured permissions to ensure that dust diffusion caused by wind speed or wind direction can be contained in time. Through the linkage operation of multiple sub-areas, a cross-regional dust reduction synergy effect can be achieved.

[0052] Furthermore, the K edge dust reduction control modules receive and perform linkage dust reduction control of the K dust reduction operation sub-areas according to the edge node interaction authority, and the method includes:

[0053] The first edge dust reduction control module traverses K-1 edge dust reduction control modules according to the edge node interaction authority to obtain a first group of edge dust reduction control modules; the first edge dust reduction control module integrates a first group of concentration excess limit deviations of the first group of edge dust reduction control modules; a maximum value call is performed on the first group of concentration excess limit deviations to obtain a first concentration excess limit extreme value; spray control parameters are matched according to the first concentration excess limit extreme value to obtain a first linkage dust reduction parameter; the first linkage dust reduction parameter is used to perform dust reduction control of the first collaborative dust reduction zone.

[0054] Specifically, the first edge dust reduction control module traverses the remaining K-1 edge dust reduction control modules according to the assigned edge node interaction authority, and identifies the first group of edge dust reduction control modules that have a linkage dust reduction relationship with it; the first edge dust reduction control module integrates the first group of concentration excess deviations from the first group of edge dust reduction control modules, and these deviations reflect that the dust concentration in the relevant area exceeds the warning threshold; the integrated first group of concentration excess deviations are maximum called to obtain the first concentration excess extreme value in the group of areas, that is, the highest dust concentration excess situation; according to the first concentration excess extreme value, the spray control parameters are matched to ensure that the spray intensity, frequency and direction can effectively cope with the dust concentration in the extreme area; using the matched first linkage dust reduction parameters, the first edge dust reduction control module works in coordination with other related modules to perform joint dust reduction operations on the first coordinated dust reduction partition to ensure that dust is effectively suppressed in the entire partition and prevent dust from spreading to other areas.

[0055] In summary, the embodiments of the present application have at least the following technical effects:

[0056] First, the dust control area is divided into multiple dust reduction operation sub-areas. Then, multiple water mist spraying operation points are configured for multiple dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center. When the integrated control center receives the first dust reduction warning, it performs edge node identification on the first dust reduction warning and obtains K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust reduction control modules. Next, the integrated control center generates edge node interaction permissions based on the first dust reduction warning by performing dust dispersion correlation analysis on the K dust reduction operation sub-areas. Finally, the K edge dust reduction control modules receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction permissions. The technical problems in the prior art that the dust warning response is not timely and the dust reduction operation lacks accuracy and linkage, resulting in poor dust reduction effect, are solved. Through real-time dust concentration monitoring, dispersion correlation analysis and cross-region linkage control, the technical effect of improving the dust warning response speed and achieving precise dust reduction is achieved.

[0057] Embodiment 2 is based on the same inventive concept as the dust concentration dynamic warning method combined with the spray device in the previous embodiment. Figure 2 As shown, the present application provides a dust concentration dynamic warning device combined with a spray device, wherein the device comprises:

[0058] An area division component 11, the area division component 11 is used to divide the dust control area into multiple dust reduction operation sub-areas; a configuration component 12, the configuration component 12 is used to configure multiple water mist spraying operation points for the multiple dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center; an identification component 13, the identification component 13 is used to identify the edge node of the first dust reduction warning when the integrated control center receives the first dust reduction warning, and obtain K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust reduction control modules; an analysis component 14, the analysis component 14 is used for the integrated control center to generate edge node interaction permissions based on the first dust reduction warning by performing dust dispersion correlation analysis on the K dust reduction operation sub-areas; a control component 15, the control component 15 is used for the K edge dust reduction control modules to receive and perform linkage dust reduction control of the K dust reduction operation sub-areas according to the edge node interaction permissions.

[0059] Furthermore, the region division component 11 is used to perform the following method:

[0060] Interactively obtain regional operating conditions of a dust control area; identify similar areas based on the regional operating conditions to obtain multiple benchmark control parameters for multiple similar control areas; perform weighted calculation of the multiple benchmark control parameters based on multiple dust reduction deviation frequencies of the multiple similar control areas as a dust reduction control baseline for the dust control area; perform dust reduction coverage analysis on the spray device based on the dust reduction control baseline to obtain a spray coverage area; divide the dust control area into the multiple dust reduction operation sub-areas using the spray coverage area as a regional division scale.

[0061] Furthermore, the region division component 11 is used to perform the following method:

[0062] According to the indicator composition of the regional operating conditions, network data call is performed to obtain multiple sample operating conditions of multiple sample control areas, wherein the regional operating conditions include a baseline dust concentration mean, a baseline dust concentration peak, a baseline particulate matter distribution, a baseline gas concentration mean, a baseline wind speed mean, a baseline relative humidity and a baseline temperature mean; the multiple sample operating conditions and regional operating conditions are introduced into the regional similarity evaluation function for numerical calculation to obtain multiple regional similarity coefficients of the multiple sample control areas; a regional similarity threshold is preset, and the regional similarity threshold is used to traverse the multiple regional similarity coefficients to obtain the multiple similar control areas; dust reduction control information is called for the multiple similar control areas to obtain the multiple benchmark control parameters.

[0063] Furthermore, the region division component 11 is used to perform the following method: the region similarity evaluation function is as follows:

[0064] ; ; ;

[0065] in, S1 is the one-dimensional similarity coefficient, A1 is the average value of the baseline dust concentration, P1 is the peak value of the baseline dust concentration, PM1 is the benchmark particle distribution, W1 is the mean value of the benchmark gas concentration, A2 is the mean dust concentration of the samples, P2 is the peak value of the sample dust concentration, PM2 is the particle distribution of the sample, W2 is the mean value of sample gas concentration; S2 is the two-dimensional similarity coefficient, V1 is the mean base wind speed, H1 is the base relative humidity, Tvag,1 is the mean reference temperature, V2 is the sample wind speed mean, H2is the sample relative humidity, Tvag,2 is the sample temperature mean; where S is the regional similarity coefficient, ω1 is the one-dimensional weight, ω2 is a two-dimensional weight.

[0066] Furthermore, the identification component 13 is used to perform the following method:

[0067] A safe concentration prediction module is pre-constructed, wherein the safe concentration prediction module includes a cascaded safe concentration prediction layer and a concentration extreme value call layer, and the safe concentration prediction layer includes M parallel safe concentration prediction branches; a plurality of sample safety limit value arrays are interactively obtained, wherein each sample safety limit value array includes a sample safe dust concentration, a sample carbon dioxide concentration, a sample ambient temperature and a sample gas concentration; the model parameters of the M safe concentration prediction branches are adjusted using the plurality of sample safety limit value arrays to complete the localization of the safe concentration prediction module, wherein the M safe concentration prediction branches are constructed based on M non-repetitive random operators; a concentration difference calculation unit is interactively obtained, and the construction of a plurality of edge dust reduction control modules is completed by copying the concentration difference calculation unit and the safe concentration prediction module to a plurality of local servers of the plurality of dust reduction operation sub-areas, wherein the integrated control center is communicatively connected with the plurality of local servers; a plurality of dust reduction operation sub-areas are configured with multi-modal sensors according to the dust source to obtain a plurality of multi-modal sensing units, wherein the plurality of multi-modal sensing units are communicatively connected with a plurality of edge dust reduction control modules.

[0068] Furthermore, the identification component 13 is used to perform the following method:

[0069] The multiple edge dust reduction control modules receive and analyze the multiple multimodal sensing units to perform real-time monitoring on the multiple dust reduction operation sub-areas to obtain multiple real-time environment-related data, and output multiple concentration excess deviations; the K edge dust reduction control modules send the K concentration excess deviations as the first dust reduction warning to the integrated control center, wherein the K concentration excess deviations are positive values.

[0070] Furthermore, the analysis component 14 is used to perform the following method:

[0071] The integrated control center receives K real-time wind directions of the K dust reduction operation sub-areas; performs dust dispersion association judgment based on the distribution of the K dust reduction operation sub-areas in the dust control area and the K real-time wind directions, and merges the K dust reduction operation sub-areas into N collaborative dust reduction partitions, where N is a positive integer less than K; configures the edge node interaction authority based on the mapping relationship between the N collaborative dust reduction partitions and the K dust reduction operation sub-areas.

[0072] Furthermore, the control component 15 is used to execute the following method:

[0073] The first edge dust reduction control module traverses K-1 edge dust reduction control modules according to the edge node interaction authority to obtain a first group of edge dust reduction control modules; the first edge dust reduction control module integrates a first group of concentration excess limit deviations of the first group of edge dust reduction control modules; a maximum value call is performed on the first group of concentration excess limit deviations to obtain a first concentration excess limit extreme value; spray control parameters are matched according to the first concentration excess limit extreme value to obtain a first linkage dust reduction parameter; the first linkage dust reduction parameter is used to perform dust reduction control of the first collaborative dust reduction zone.

[0074] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0075] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application. This specification and the drawings are merely exemplary illustrations of the present application and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and variations.

Claims

1. A dynamic early warning method for dust concentration in combination with a spray device, characterized in that: The method comprises: Divide the dust control area into multiple dust reduction operation sub-areas; A plurality of water mist spraying operation points are configured for the plurality of dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center; When the integrated control center receives the first dust fall warning, edge node identification is performed on the first dust fall warning to obtain K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust fall control modules; The integrated control center generates edge node interaction permissions based on the first dust fall warning by performing dust dispersion correlation analysis on K dust fall operation sub-areas; The K edge dust reduction control modules receive and perform linkage dust reduction control of the K dust reduction operation sub-areas according to the edge node interaction authority; The dust control area is divided into a plurality of dust reduction operation sub-areas, and the method comprises: Interactively obtain regional operating conditions of dust control areas; Identify similar regions based on the regional operating conditions to obtain multiple benchmark control parameters for multiple similar control regions; Perform weighted calculation of the multiple benchmark control parameters according to the multiple dust reduction deviation frequencies of the multiple similar control areas as the dust reduction control baseline of the dust control area; Perform dust cover analysis on the spray device according to the dust control baseline to obtain a spray coverage area; Taking the spray coverage area as the area division scale, dividing the dust control area into the plurality of dust reduction operation sub-areas; Based on the regional operating conditions, similar regions are identified to obtain multiple benchmark control parameters for multiple similar control regions, the method comprising: Performing online data call according to the index composition of the regional operating conditions to obtain multiple sample operating conditions of multiple sample control areas, wherein the regional operating conditions include a baseline dust concentration mean, a baseline dust concentration peak, a baseline particle matter distribution, a baseline gas concentration mean, a baseline wind speed mean, a baseline relative humidity, and a baseline temperature mean; Introducing the multiple sample operating conditions and regional operating conditions into a regional similarity evaluation function for numerical calculation to obtain multiple regional similarity coefficients of the multiple sample control areas; Presetting a region similarity threshold, and using the region similarity threshold to traverse the multiple region similarity coefficients to obtain the multiple similar control regions; Calling dust reduction control information for the plurality of similar control areas to obtain the plurality of benchmark control parameters; The regional similarity evaluation function is as follows: S=ω1S1+ω2S2; Among them, S1 is the one-dimensional similarity coefficient, A1 is the mean value of the baseline dust concentration, P1 is the peak value of the baseline dust concentration, PM1 is the baseline particle distribution, ω1 is the mean value of the baseline gas concentration, A2 is the mean value of the sample dust concentration, P2 is the peak value of the sample dust concentration, PM2 is the sample particle distribution, and ω2 is the mean value of the sample gas concentration; Among them, S1 is the two-dimensional similarity coefficient, V1 is the reference wind speed mean, H1 is the reference relative humidity, T avg,1 is the reference temperature average, V 21 is the sample wind speed mean, H2 is the sample relative humidity, T avg,2 is the mean temperature of the samples; Among them, S is the regional similarity coefficient, ω1 is the one-dimensional weight, and ω2 is the two-dimensional weight.

2. The method for dynamic early warning of dust concentration combined with a spray device according to claim 1, characterized in that: When the integrated control center receives the first dust fall warning, edge node identification is performed on the first dust fall warning to obtain K concentration limit deviations. Before that, the method includes: Pre-constructing a safety concentration prediction module, wherein the safety concentration prediction module includes a cascaded safety concentration prediction layer and a concentration extreme value call layer, and the safety concentration prediction layer includes M parallel safety concentration prediction branches; Interactively obtain multiple sample safety limit value arrays, wherein each sample safety limit value array includes a sample safety dust concentration, a sample carbon dioxide concentration, a sample ambient temperature, and a sample gas concentration; The plurality of sample safety limit value arrays are used to adjust the model parameters of the M safety concentration prediction branches to complete the localization of the safety concentration prediction module, wherein the M safety concentration prediction branches are constructed based on non-repeating M random operators; Interactively obtain a concentration difference calculation unit, and complete the construction of multiple edge dust reduction control modules by copying the concentration difference calculation unit and the safety concentration prediction module to multiple local servers of the multiple dust reduction operation sub-areas, wherein the integrated control center is communicatively connected with the multiple local servers; According to the dust source, multi-modal sensors are configured for the multiple dust reduction operation sub-areas to obtain multiple multi-modal sensing units, wherein the multiple multi-modal sensing units are communicatively connected with multiple edge dust reduction control modules.

3. The method for dynamic early warning of dust concentration combined with a spray device as claimed in claim 2, characterized in that: When the integrated control center receives a first dust fall warning, edge node identification is performed on the first dust fall warning to obtain K concentration limit deviations, and the method includes: The plurality of edge dust reduction control modules receive and analyze the plurality of multimodal sensing units to perform real-time monitoring on the plurality of dust reduction operation sub-areas to obtain a plurality of real-time environment-related data, and output a plurality of concentration over-limit deviations; The K edge dust reduction control modules send the K concentration limit deviations as the first dust reduction warnings to the integrated control center, wherein the K concentration limit deviations are positive values.

4. The method for dynamic early warning of dust concentration combined with a spray device according to claim 1, characterized in that: The integrated control center generates edge node interaction permissions based on the first dust fall warning by performing dust dispersion correlation analysis on the K dust fall operation sub-areas, and the method includes: The integrated control center receives K real-time wind directions of the K dust reduction operation sub-areas; According to the distribution of the K dust reduction operation sub-areas in the dust control area and the K real-time wind directions, the dust dispersion association judgment is performed, and the K dust reduction operation sub-areas are merged into N coordinated dust reduction partitions, where N is a positive integer less than K; The edge node interaction authority is configured according to the mapping relationship between the N collaborative dust reduction zones and the K dust reduction operation sub-zones.

5. The method for dynamic early warning of dust concentration combined with a spray device as claimed in claim 4, characterized in that: The K edge dust reduction control modules receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction authority, and the method includes: The first edge dust reduction control module traverses K-1 edge dust reduction control modules according to the edge node interaction authority to obtain a first group of edge dust reduction control modules; The first edge dust reduction control module integrates the first group of concentration over-limit deviations of the first group of edge dust reduction control modules; Performing a maximum call on the first group of concentration over-limit deviations to obtain the first concentration over-limit extreme value; Matching spray control parameters according to the first concentration exceeding limit value to obtain first linkage dust reduction parameters; The first linkage dust reduction parameters are used to perform dust reduction control in the first coordinated dust reduction zone.

6. A dust concentration dynamic warning device combined with a spray device, characterized in that: The method for implementing the dynamic early warning method for dust concentration combined with a spray device according to any one of claims 1 to 5 comprises: An area division component, the area division component is used to divide the dust control area into a plurality of dust reduction operation sub-areas; A configuration component, wherein the configuration component is used to configure a plurality of water mist spraying operation points for the plurality of dust reduction operation sub-areas to complete the localization of the spray device, wherein the spray device is configured with an integrated control center; an identification component, wherein when the integrated control center receives a first dust fall warning, the identification component is used to perform edge node identification on the first dust fall warning to obtain K concentration limit deviations, wherein the K concentration limit deviations correspond to K edge dust fall control modules; An analysis component, wherein the analysis component is used by the integrated control center to generate edge node interaction permissions based on the first dust fall warning by performing dust dispersion correlation analysis on K dust fall operation sub-areas; A control component is used for the K edge dust reduction control modules to receive and perform linkage dust reduction control on the K dust reduction operation sub-areas according to the edge node interaction authority.

Images