Spraying dust fall control method and system

Abstract

The invention relates to the technical field of spraying dust fall, in particular to a spraying dust fall control method and system. The spray dust fall control method comprises the following steps: S1, acquiring first external data before spray dust fall; the first external data comprises first air flow velocity data, first dust concentration data, first dust density data, first dust particle size data and first dust distribution data; s2, on the basis of the first external data, calculating the matching relationship between water pressure and particle size required by spray dust fall and spray flow, generating basic regulation and control parameters, and performing spray dust fall; s3, acquiring second external data after spraying and dust falling; the second external data comprises second air flow velocity data, second dust concentration data, second dust density data, second dust particle size data and second dust distribution data, and S4, evaluating the spraying dust reduction effect on the basis of the second external data, so that control over the spraying dust reduction effect can be effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of spray dust suppression, in particular to a spray dust suppression control method and system. BACKGROUND

[0002] In the construction process of underground engineering (such as tunnels, underground mine tunnels, subways, etc.), drilling, blasting, slag transportation and shotcrete operations will all produce a large amount of high-concentration dust, especially in underground coal mining, which has a high concentration of coal dust and is extremely prone to dust explosions, posing a great threat to safety production. In addition to this, high-concentration dust not only affects the service life and construction efficiency of underground construction equipment, but also seriously pollutes the construction environment and threatens the safety of construction workers.

[0003] Traditional mechanical ventilation can dilute dust, but has problems such as high energy consumption, large ventilation resistance and difficulty in achieving rapid dust suppression, and cannot effectively control the dust dispersion range, leading to deterioration of air quality in underground space. Spray dust suppression technology, as a simple, efficient and green dust suppression technology, is mainly applied to underground coal mines, tunnel engineering, etc. The core of spray dust suppression technology is to disperse water into 1-100 micron droplets through atomization, so that the droplets capture or agglomerate dust particles and accelerate dust settling.

[0004] At present, spray dust suppression technology has developed from fixed spraying to intelligent, multi-dimensional control spraying methods, including rotary spray devices, ejector dust suppression systems, etc. However, in the process of spray dust suppression, the existing technology is not very precise, and the amount of water used is reduced when the dust concentration is low, and the amount of water used is increased when the dust concentration is high. Specifically, for equipment with not very high intelligence level, the control relies on the experience of personnel; for equipment with high intelligence level, it adjusts itself according to the feedback of dust concentration sensors, water pressure / flow sensors, etc. However, no matter how, the dimension of spray dust suppression control is still too single, leading to difficulty in controlling the effect of spray dust suppression. SUMMARY

[0005] The present application aims to provide a spray dust suppression control method and system that can effectively improve the control of spray dust suppression effect.

[0006] In order to solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a spray dust suppression control method, comprising the following steps: S1: obtaining first external data before spray dust suppression; the first external data includes first air flow velocity data, first dust concentration data, first dust density data, first dust particle size data and first dust distribution data; S2: based on the first external data, calculating the matching relationship between the water pressure and particle size required for spray dust suppression and the spray flow, generating basic control parameters and performing spray dust suppression; S3: obtaining second external data after spraying dust reduction; the second external data includes second air flow velocity data, second dust concentration data, second dust density data, second dust particle size data, and second dust distribution data; S4: evaluating the spraying dust reduction effect based on the second external data; S5: constructing a spraying dust reduction decision model, training and learning based on the first external data, the second external data, and spraying dust reduction control parameters, and optimizing the spraying dust reduction control parameters; S6: controlling the spraying dust reduction process based on the optimized spraying dust reduction decision model to achieve the optimal spraying dust reduction effect.

[0007] Optionally, the matching relationship between the water pressure required for spraying dust reduction and the particle size includes: The calculation formula of the mist particle size and the settleable dust particle size is: (1) wherein, represents the dust particle size; represents the air dynamic viscosity coefficient; represents the mist particle size; represents the inertial collision coefficient; represents the dust density; represents the air flow velocity; When spraying, the particle size of the spray is determined by the nozzle diameter and the spray pressure, and the calculation formula is: (2) wherein, represents the proportionality coefficient; represents the nozzle diameter; represents the water pressure; According to formulas (1) and (2), the calculation formula of the dust particle size and the water pressure is: (3).

[0008] Optionally, the calculation formula of the spraying flow is: (4) wherein, represents the spraying flow; represents the average dust concentration; represents the air volume; represents the optimal average mist particle size of the water mist; represents the average air dynamic diameter of the dust; represents the spraying flow coefficient; If the optimal average mist particle size of the water mist is equal to the average air dynamic diameter of the dust, formula (4) is simplified as: (5) The calculation formula of water flow is: (6) Wherein, The water flow rate represents.

[0009] According to formula (5), (6), the calculation formula of water flow rate is obtained: (7).

[0010] Optionally, the spray dust falling control method further comprises: acquiring air temperature data and air humidity data during the spray dust falling process.

[0011] Optionally, the spray dust falling control method further comprises: the visualization module of the intelligent control terminal visually displays the first external data, the second external data, the spray dust falling control parameters, the spray state, the valve state and the spray dust falling decision model, etc.

[0012] In a second aspect, the present application provides a spray dust falling control system for realizing the spray dust falling control method of the first aspect, comprising: a spray control device, an automatic gate valve system and an intelligent control terminal; the spray control device is connected with the automatic gate valve system through a water supply pipe; and the intelligent control terminal is wirelessly connected with the spray control device and the automatic gate valve system respectively.

[0013] Optionally, the spray control device comprises a first communication management module and a multi-sensor integrated module connected electrically; the first communication management module is connected with the intelligent control terminal; and the multi-sensor integrated module comprises a dust sensor, a particle size distribution sensor, a wind speed sensor, a temperature sensor and a humidity sensor connected with the first communication management module electrically respectively.

[0014] Optionally, the automatic gate valve system comprises a pressure control valve and a flow control valve installed on the water supply pipe; and the pressure control valve and the flow control valve are wirelessly connected with the intelligent control terminal respectively.

[0015] Optionally, the intelligent control terminal comprises a processor, a second communication management module, a storage module and a visualization module connected with the processor electrically respectively; and the second communication management module is wirelessly connected with the pressure control valve, the flow control valve and the first communication management module respectively.

[0016] In summary, the present application has at least the following beneficial technical effects: 1.The spray dust control method and system provided by the present application utilizes various sensors to monitor data such as dust concentration, dust density, dust particle size, and dust distribution air environment in real time, and the monitoring data is fed back to the intelligent control terminal in real time, and the dust and environmental monitoring data are automatically processed and analyzed. At the same time, the monitoring data is trained and learned to establish a dust reduction parameter model, and based on the dust information and environmental information, intelligent sensing adjustment and analysis are carried out to automatically adjust the water pressure and water flow (water speed), which greatly improves the dust reduction effect and improves the underground working environment.

[0017] 2.The spray dust control method and system utilize sensors, artificial intelligence, data analysis, and other technologies to achieve precise control of dust concentration, temperature, humidity, water pressure, nozzle diameter, and spray dust reduction effect, and build a "monitoring-evaluation-optimization-adjustment" dust reduction control mechanism to realize self-adaptive optimization and full-process intelligent decision-making of spray dust reduction, and provide a safe, efficient, and green dust reduction solution for underground engineering dust reduction. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The figure is a flowchart of a spray dust control method in an embodiment of the present application. Figure 2 The figure is a flowchart of another spray dust control method in an embodiment of the present application. Figure 3 The figure is a schematic diagram of a spray dust control system in an embodiment of the present application.

[0019] Reference signs: 1, spray control device; 2, automatic gate valve system; 3, water supply pipe; 4, intelligent control terminal. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0021] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to be limiting of the present application. As used in the specification and the appended claims of the present application, the singular forms "a," "an" and "the" are intended to include plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or," as used in the present application, refers to and encompasses any and all possible combinations of one or more of the associated listed items. The terms "first," "second," and the like in the description do not denote any order, quantity, or importance, but rather are used to distinguish one element from another, and are more particularly delineated to address the quantity and / or the order where no other criteria is more appropriate. As such, features defined with "first," "second" can explicitly or implicitly include one or more of the features, and in the description of embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0022] The present application provides a spray dust control method.

[0023] Reference Figure 1 , the spray dust control method comprises the following steps: S1: obtaining first external data before spraying dust.

[0024] The multi-sensor integrated module of the spray control device 1 obtains the first external data before spraying dust, and the first external data includes first air flow speed data, first dust concentration data, first dust density data, first dust particle size data, and first dust distribution data.

[0025] The multi-sensor integrated module includes a dust sensor, a particle size distribution sensor, and a wind speed sensor. The dust sensor obtains the first dust concentration data, the first dust density data, and the first dust particle size data, the particle size distribution sensor obtains the first dust distribution data, and the wind speed sensor obtains the first air flow speed data.

[0026] It should be understood that whether the system starts work or not can be determined by setting a dust concentration work threshold in the processor, and starting work after the dust sensor detects that the dust concentration reaches the threshold. Alternatively, the time to start work can be manually set. After obtaining the first external data, the first external data can be preprocessed, which is a prior art and will not be described in detail.

[0027] S2: Based on the first external data, the matching relationship between the water pressure and the particle size required for spraying dust and the spray flow are calculated, the basic control parameters are generated, and the spraying dust is performed.

[0028] The first communication management module of the spray control device 1 sends the first external data to the second communication management module of the intelligent control terminal 4, and the sending adopts a real-time transmission mode, which can be various wired or wireless transmissions and is not limited here. The processor of the intelligent control terminal 4 processes the first external data, and the storage module of the intelligent control terminal 4 stores the first external data.

[0029] In the process of processor calculation, the calculation formula of the mist particle size and the dust particle size thereof is: (1) wherein, represents the dust particle size (unit: um); represents the air dynamic viscosity coefficient (unit: Pa·s), which is 1.8×10 -5 Pa·s; represents the mist particle size (unit: mm); represents the inertial collision coefficient, which ranges from 1 to 200; represents the dust density (unit: g / m 3 ); represents the air flow velocity (unit: m / s).

[0030] When spraying, the particle size of the spray is determined by the nozzle diameter and the spray pressure, and the calculation formula is: (2) wherein, represents the proportional coefficient, which is =34530; represents the nozzle diameter (unit: mm); represents the water pressure (unit: Pa).

[0031] According to formulas (1) and (2), the calculation formula of the dust particle size and the water pressure is obtained as: (3) The calculation formula of the spray flow is: (4) wherein, represents the spray flow (unit: L / min); represents the average dust concentration (unit: mg / m 3 ); represents the air volume (unit: m 3 / min); represents the optimal average mist particle size of the water mist (unit: um); represents the average air dynamic diameter of the dust (unit: um); represents the spray flow coefficient.

[0032] Assuming that the optimum average mist particle size of water mist is equal to the average aerodynamic diameter of dust, (4) is simplified as: (5) The calculation formula of water flow is: (6) Wherein, represents the water flow rate.

[0033] According to (5) and (6), the calculation formula of water flow rate is: (7) The processor generates real-time basic control parameters according to the first external data, the second communication management module sends control signals carrying the basic control parameters to the pressure control valve and the flow control valve of the automatic gate valve system 2, and sends control signals carrying the basic control parameters to the first communication management module.

[0034] The pressure control valve and the flow control valve of the automatic gate valve system 2 control water pressure and water flow (spray flow) respectively, and the spray control module controls particle size, so as to realize self-adaptive control of spray dust removal operation and ensure the spray dust removal effect.

[0035] Wherein, the basic control parameters include water pressure, particle size and spray flow required for spray dust removal. When the basic control parameters change with the change of the first external data, the pressure control valve, the flow control valve and the spray control module are controlled by the processor to adaptively adjust, and the water pressure, the particle size and the spray flow are correspondingly changed.

[0036] S3: Obtain the second external data after spray dust removal.

[0037] The multi-sensor integrated module obtains the second external data after spray dust removal, and the second external data includes second air flow speed data, second dust concentration data, second dust density data, second dust particle size data and second dust distribution data.

[0038] Wherein, the dust sensor obtains the second dust concentration data, the second dust density data and the second dust particle size data, the particle size distribution sensor obtains the second dust distribution data, and the wind speed sensor obtains the second air flow speed data.

[0039] S4: Evaluate the spray dust removal effect based on the second external data.

[0040] After the spray dust removal is completed, the spray dust removal effect can be determined by obtaining the second external data.

[0041] ReferenceFigure 2 In an optional embodiment of the present application, the spray dust-settling control method further comprises, after S4: S5: constructing a spray dust-settling decision model, training and learning based on the first external data, the second external data and the spray dust-settling control parameters, and optimizing the spray dust-settling control parameters.

[0042] The intelligent control terminal 4 constructs the spray dust-settling decision model, trains and learns based on the first external data, the second external data and the spray dust-settling control parameters, and optimizes the spray dust-settling control parameters.

[0043] Specifically, in each spray dust-settling process, a group of data is generated, which includes the first external data, the second external data and the spray dust-settling control parameters. After obtaining multiple groups of data, the multiple groups of data are randomly divided into a training set, a validation set and a test set. Then the data is cleaned and corrected to convert it into a feature set that can be learned by the spray dust-settling decision model. The spray dust-settling decision model is then trained by the training set, the optimized spray dust-settling decision model is verified by the validation set, and the optimized spray dust-settling decision model is tested by the test set. Finally, the optimized spray dust-settling control parameters are obtained.

[0044] The specific selection of the model can be gradient boosting, neural network, integration strategy, etc. The loss function can be mean square error, mean absolute error, etc. The hyperparameter optimization can be grid search, Bayesian optimization, etc. The specific selection can be determined according to the actual situation, and will not be described here. It should be understood that the air temperature data and the air humidity data can also be added to the construction and optimization process of the model.

[0045] S6: based on the optimized spray dust-settling decision model, the spray dust-settling process is regulated to achieve the optimal spray dust-settling effect.

[0046] In an optional embodiment of the present application, the spray dust-settling control method further comprises: the temperature sensor and the humidity sensor of the multi-sensor integration module respectively acquiring air temperature data and air humidity data.

[0047] The spray dust-settling control method further comprises: in the process of spray dust-settling, the visualization module of the intelligent control terminal 4 visually displays the first external data, the second external data, the spray dust-settling control parameters, the spray state, the valve state and the spray dust-settling decision model.

[0048] The spray dust-settling control method further comprises: the storage module of the intelligent control terminal 4 storing the first external data, the second external data, the spray dust-settling control parameters and other data.

[0049] The present application also provides a spray dust-settling control system.

[0050] Reference Figure 3 , spray dust control system, comprising: spray control device 1, automatic gate valve system 2, intelligent control terminal 4. Spray control device 1 can be one or more, spray control device 1 is connected with automatic gate valve system 2 through water supply pipe 3, intelligent control terminal 4 is connected with spray control device 1, automatic gate valve system 2 wireless communication respectively.

[0051] Specifically, the spray control device 1 comprises a first communication management module and a multi-sensor integrated module electrically connected, the first communication management module is connected with the intelligent control terminal 4. The multi-sensor integrated module comprises a dust sensor, a particle size distribution sensor, a wind speed sensor, a temperature sensor and a humidity sensor electrically connected with the first communication management module respectively.

[0052] The automatic gate valve system 2 comprises a pressure control valve and a flow control valve installed on the water supply pipe 3, and the pressure control valve and the flow control valve are wirelessly connected with the intelligent control terminal 4 respectively.

[0053] The intelligent control terminal 4 comprises a processor, and a second communication management module, a storage module and a visualization module electrically connected with the processor respectively. The second communication management module is wirelessly connected with the pressure control valve, the flow control valve and the first communication management module respectively.

[0054] The various changes and specific examples in the method provided by the above embodiment are also applicable to the spray dust control system of the present embodiment. Through the foregoing detailed description of the spray dust control method, those skilled in the art can clearly understand the implementation method of the spray dust control system in the present embodiment. For the sake of brevity of the description, it will not be described in detail here.

[0055] The above-described embodiments are only used to describe the technical solutions of the present application in detail, but the description of the above embodiments is only used to help understand the method of the present application and its core idea, and should not be understood as a limitation of the present application. Those skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for controlling dust suppression by spraying, characterized in that, Includes the following steps: S1: Obtain the first external data before the dust suppression spray; the first external data includes the first airflow velocity data, the first dust concentration data, the first dust density data, the first dust particle size data, and the first dust distribution data; S2: Based on the first external data, calculate the matching relationship between the water pressure and particle size required for spray dust suppression and the spray flow rate, generate basic control parameters and carry out spray dust suppression; S3: Obtain the second external data after the dust suppression spray; the second external data includes the second airflow velocity data, the second dust concentration data, the second dust density data, the second dust particle size data, and the second dust distribution data; S4: Evaluate the dust suppression effect of the spray based on secondary external data; S5: Construct a spray dust suppression decision model, train and learn based on the first external data, the second external data, and the spray dust suppression control parameters, and optimize the spray dust suppression control parameters. S6: Based on the optimized spray dust suppression decision model, regulate the spray dust suppression process to achieve the best spray dust suppression effect.

2. The spray dust suppression control method as described in claim 1, characterized in that, The calculation of the matching relationship between water pressure and particle size required for spray dust suppression includes: The formula for calculating the particle size of mist particles and the particle size of settling dust is as follows: (1) in, Represents the particle size of dust; Represents the aerodynamic viscosity coefficient; Represents the particle size of the fog; Represents the inertial collision coefficient; Represents dust density; Represents the speed of airflow; During spraying, the particle size is determined by the nozzle diameter and the spray pressure, and the calculation formula is as follows: (2) in, Represents the proportionality coefficient; Represents the nozzle diameter; Represents water pressure; Based on equations (1) and (2), the formulas for calculating dust particle size and water pressure are as follows: (3)。 3. The spray dust suppression control method as described in claim 2, characterized in that, The formula for calculating the spray flow rate is: (4) in, Represents spray flow rate; Represents the average dust concentration; Represents air volume; The optimal average droplet size representing water mist; The average aerodynamic diameter of the dust particles; Represents the spray flow rate coefficient; Assuming that the optimal average mist particle size is equal to the average aerodynamic diameter of dust, equation (4) simplifies to: (5) The formula for calculating water flow rate is: (6) in, Represents the water flow velocity; Based on equations (5) and (6), the formula for calculating the water flow velocity is: (7)。 4. The spray dust suppression control method as described in claim 1, characterized in that, Also includes: During the dust suppression spraying process, air temperature and humidity data are acquired.

5. The spray dust suppression control method as described in claim 1 or 4, characterized in that, Also includes: During the dust suppression spraying process, the primary external data, secondary external data, dust suppression spraying control parameters, spraying status, valve status, and dust suppression spraying decision-making model are visualized.

6. A spray dust suppression control system, characterized in that, The method for implementing the spray dust suppression control method as described in any one of claims 1-5 includes: a spray control device (1), an automatic gate valve system (2), and an intelligent control terminal (4); the spray control device (1) is connected to the automatic gate valve system (2) through a water supply pipe (3), and the intelligent control terminal (4) is wirelessly connected to the spray control device (1) and the automatic gate valve system (2) respectively.

7. The spray dust suppression control system as described in claim 6, characterized in that, The spray control device (1) includes a first communication management module and a multi-sensor integration module that are electrically connected. The first communication management module is connected to the intelligent control terminal (4). The multi-sensor integration module includes a dust sensor, a particle size distribution sensor, a wind speed sensor, a temperature sensor, and a humidity sensor that are electrically connected to the first communication management module.

8. The spray dust suppression control system as described in claim 7, characterized in that, The automatic gate valve system (2) includes a pressure control valve and a flow control valve installed on the water supply pipe (3), and the pressure control valve and the flow control valve are wirelessly connected to the intelligent control terminal (4).

9. The spray dust suppression control system as described in claim 8, characterized in that, The intelligent control terminal (4) includes a processor, and a second communication management module, a storage module, and a visualization module that are electrically connected to the processor. The second communication management module is wirelessly connected to the pressure control valve, the flow control valve, and the first communication management module.

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