Flying dust treatment system with automatic monitoring and real-time early warning functions

Abstract

The invention relates to the technical field of raising dust treatment monitoring and early warning, and discloses a raising dust treatment system with automatic monitoring and real-time early warning functions. The raising dust treatment system comprises a raising dust data acquisition module, a raising dust data analysis and early warning module, a raising dust point position data acquisition module and a target tracking module, the dust raising data acquisition module comprises a dust raising condition acquisition unit and a dust falling equipment data acquisition unit, the dust raising data analysis and early warning module comprises a dust raising early warning unit and an equipment maintenance unit, and the dust raising point location data acquisition module is used for carrying out image recognition on point locations where dust raising conditions occur. The system analyzes the current flying dust condition to judge whether the flying dust is artificially caused or not, if the flying dust is artificially caused, the type of flying dust caused by a vehicle, tire residual dust, cargo capacity exceeding the height limit and vehicle leakage are recognized, and after the determination is completed, license plate data are uploaded to a manager, so that the management of the vehicle is completed. And the license plate data of the vehicle is identified at each detection point, and image data is fed back to a manager for early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of dust control monitoring and early warning, and in particular to a dust control system with automatic monitoring and real-time early warning. Background Art

[0002] With the acceleration of urbanization, dust pollution caused by construction sites, road cleaning and other operations is becoming increasingly serious. Traditional dust control methods rely on manual inspections and supervision, which have problems such as low efficiency, high cost and slow response.

[0003] Prior art CN 117218558 A discloses a method for fine-grained accounting and supervision of construction site dust using multimodal data fusion, which is used to solve the problem that existing construction site dust supervision is not fine enough. The multimodal data fusion construction site dust fine accounting supervision method of the present invention comprises the following steps: S100: identifying the scope of the construction site through satellites to obtain the total area Ac of the construction site; S200: determining the dust removal efficiency η of the pollution control technology on a certain day; S300: obtaining the construction time T of the construction site on a certain day; S400: calculating the emission Wc of particulate matter i in the construction dust of the construction site on a certain day, obtaining the construction site area through remote sensing monitoring, intelligently identifying the type of dust control measures through the construction site video monitoring, obtaining the number of mobile phone messengers through the construction site electronic fence to calculate the construction time, and realizing accurate and timely acquisition of multiple types of parameters of the construction site through the fusion of multimodal data, making the construction site emission accounting comprehensive and refined, realizing the quantitative accounting of the emission pollution degree of a single construction site in the daily dimension, supporting the excavation of potential high-risk construction sites for normalized dust, supporting the excavation of clues of illegal construction at night and failure to implement emergency emission reduction and suspension measures, supporting the accurate tracing of high values ​​of coarse particulate matter, and providing accurate guidance down to the construction site level for supervision and management;

[0004] At the current stage, only the overall dust situation of the construction site is calculated, while the violations caused by vehicles transporting waste soil at excessive heights, exceeding limits, and spilling are ignored. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In view of the deficiencies in the prior art, the present invention provides a dust control system with automatic monitoring and real-time early warning, which has the advantages of monitoring dust problems occurring during the transportation of slag, and solves the above-mentioned technical problems.

[0007] (II) Technical solution

[0008] To achieve the above object, the present invention provides the following technical solutions: a dust control system with automatic monitoring and real-time early warning, comprising a dust data collection module, a dust data analysis and early warning module, a dust point location data collection module and a target tracking module;

[0009] The dust data collection module includes a dust situation collection unit and a dust suppression equipment data collection unit. The dust situation collection unit is used to collect the dust situation in the current environment and send the dust data to the dust data analysis and early warning module for early warning. The dust suppression equipment data collection unit is used to collect the humidity of each dust suppression equipment and send the humidity data to the dust data analysis and early warning module;

[0010] The dust data analysis and warning module includes a dust warning unit and an equipment maintenance unit. The dust warning unit is used to analyze and warn the dust situation in the current environment. When dust occurs, the equipment maintenance unit is called to determine whether the dust suppression equipment is operating normally and whether it needs maintenance. If maintenance is not required, the data collection module at the dust point is started;

[0011] The data acquisition module at the dust point is used to perform image recognition on the point where dust occurs, and record the license plate of the currently recognized vehicle, and collect the vehicle data at the same time, the vehicle data includes the vehicle tire color, vehicle cargo height and vehicle weight, and send the vehicle data and license plate to the target tracking module for tracking;

[0012] The target tracking module includes a target dust type identification unit and a target tracking unit. The target dust type identification unit is used to identify the dust type of the target vehicle, and send the vehicle data and license plate of the determined dust type to the target tracking unit, and track and identify the vehicle through the target tracking unit, and notify the management personnel to handle it.

[0013] As a preferred technical solution of the present invention, the dust situation collection unit collects the dust situation in the current environment using the following expression:

[0014] YC t =[yc t,1 ,…,yc t,i ,…,yc t,n ]

[0015] Among them, yc t,1 ,…,yc t,i ,…,yc t,n They represent the dust situation at the first detection point, ..., the dust situation at the i-th detection point, ..., the dust situation at the n-th detection point, respectively. YC t Represents the dust dataset at time t.

[0016] As a preferred technical solution of the present invention, the dust reduction equipment data collection unit collects the humidity at each dust reduction equipment using the following expression:

[0017] RH t =[RH t,1 ,…,RH t,i ,…,RH t,n ]

[0018] Among them, RH t Represents the humidity data set at the dust suppression equipment at time t, RH t,1 ,…,RH t,i ,…,RH t,n The humidity value at the 1st detection point, ..., the humidity value at the i-th detection point, ..., the humidity value at the n-th detection point.

[0019] As a preferred technical solution of the present invention, the steps of analyzing the dust situation by the dust data analysis and warning module are as follows:

[0020] A1. Dust situation yc for the i-th detection point t,i To judge, if the dust situation yc of the i-th detection point t,i If it is judged that the dust threshold is exceeded, the equipment maintenance unit is called;

[0021] A2. Humidity value RH at the i-th detection point t,i To judge, if the humidity value RH at the i-th detection point t,i When it is lower than the set humidity threshold RH0, the humidity value adjacent to the i-th detection point is detected. If the humidity value adjacent to the i-th detection point is normal, the judgment result is that the dust reduction equipment is damaged and needs maintenance. If the comprehensive humidity value adjacent to the i-th detection point is also lower than the set humidity threshold RH0, it is judged that the local airflow is too large and the judgment is terminated. If the humidity value adjacent to the i-th detection point is not lower than the set humidity threshold RH0, the judgment result is that no maintenance is required, and the data collection module at the dust point is started.

[0022] As a preferred technical solution of the present invention, the expression of the comprehensive humidity value adjacent to the i-th detection point in step A2 is as follows:

[0023]

[0024] Among them, ZHRH t,i It represents the comprehensive humidity value of the vicinity of the i-th detection point at time t. It represents the sum of the humidity values ​​at the two detection points after the i-th detection point. It represents the sum of the humidity values ​​at the first detection point and the two detection points after the i-th detection point. It represents the sum of the humidity values ​​at the two detection points before and after the i-th detection point. Represents the sum of the humidity values ​​at the two detection points before the i-th detection point.

[0025] As a preferred technical solution of the present invention, the target dust type identification unit in the target tracking module identifies dust types including residual dust from tires, cargo load exceeding the height limit and vehicle spillage. After the current vehicle identifies one or more types, the identified one or more types are sent to the target tracking unit for tracking and identification.

[0026] As a preferred technical solution of the present invention, the calculation expression for the target dust type identification unit to identify the residual dust on the tire is as follows:

[0027]

[0028] Where, μ represents the residual amount of dust left in the tire, CHL cl Indicates the total number of pixels selected by the cl-th wheel in the image, GRAY cl It indicates the total number of non-black pixels of the cl-th wheel selected in the image. CL indicates the total number of wheels of the current vehicle. When μ≥0.5, it indicates that there is too much residual dust on the tire. In this case, the output dust type is residual dust on the tire.

[0029] As a preferred technical solution of the present invention, the target dust type identification unit identifies that the cargo load exceeds the height limit by the following calculation expression:

[0030] ΔH=H0-H max

[0031] Among them, H0 represents the current vehicle cargo height, H max Indicates the current vehicle cargo height limit, ΔH indicates the height difference. When ΔH>0, it indicates that the current vehicle cargo height is too high. At this time, the output dust type is cargo load exceeds height limit.

[0032] As a preferred technical solution of the present invention, the target dust type identification unit identifies the vehicle leakage calculation expression as follows:

[0033]

[0034] Among them, M0 represents the current initial load of the vehicle, M i It indicates the load of the current vehicle at the i-th detection point, ΔM indicates the load deviation, and when ΔM>0.05, it means that the vehicle leaks dust, and the output dust type is vehicle leaks dust.

[0035] As a preferred technical solution of the present invention, the target tracking unit uploads the license plate data to the management personnel, identifies the license plate data of the vehicle at each detection point, and feeds back the image data to the management personnel.

[0036] Compared with the prior art, the present invention provides a dust control system with automatic monitoring and real-time early warning, which has the following beneficial effects:

[0037] 1. The present invention analyzes the current dust situation to determine whether the dust is caused by humans. If it is caused by humans, the dust type caused by the vehicle is identified, such as residual dust on tires, cargo volume exceeding the height limit, and vehicle spillage. After the determination is completed, the license plate data is uploaded to the management personnel, and the license plate data of the vehicle is identified at each detection point, and the image data is fed back to the management personnel for early warning.

[0038] 2. The present invention avoids dust interference caused by strong winds and airflows during the monitoring process by constructing a comprehensive humidity value adjacent to the detection point, calculating the comprehensive humidity value adjacent to the detection point, and comparing it with the set humidity threshold RH0. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] See also Figure 1 , a dust control system with automatic monitoring and real-time early warning, including a dust data collection module, a dust data analysis and early warning module, a dust point data collection module and a target tracking module;

[0042] The dust data collection module includes a dust situation collection unit and a dust suppression equipment data collection unit. The dust situation collection unit is used to collect the dust situation in the current environment and send the dust data to the dust data analysis and early warning module for early warning. The dust suppression equipment data collection unit is used to collect the humidity of each dust suppression equipment and send the humidity data to the dust data analysis and early warning module.

[0043] The dust data analysis and warning module includes a dust warning unit and an equipment maintenance unit. The dust warning unit is used to analyze and warn the dust situation in the current environment. When dust occurs, the equipment maintenance unit is called to determine whether the dust suppression equipment is operating normally and whether it needs maintenance. If maintenance is not required, the data collection module at the dust point is started;

[0044] The data collection module at the dust point is used to perform image recognition on the dust point, record the license plate of the currently recognized vehicle, and collect the vehicle data, including the vehicle tire color, vehicle cargo height and vehicle weight, and send the vehicle data and license plate to the target tracking module for tracking;

[0045] The target tracking module includes a target dust type identification unit and a target tracking unit. The target dust type identification unit is used to identify the dust type of the target vehicle, and send the vehicle data and license plate of the determined dust type to the target tracking unit. The target tracking unit tracks and identifies the vehicle, and notifies the management personnel for processing.

[0046] Furthermore, the dust collection unit collects dust in the current environment using the following expression:

[0047] YC t =[yc t,1 ,…,yc t,i ,…,yc t,n ]

[0048] Among them, yc t,1 ,…,yc t,i ,…,yc t,n They represent the dust situation at the first detection point, ..., the dust situation at the i-th detection point, ..., the dust situation at the n-th detection point, respectively. YC t Represents the dust data set at time t. The dust situation here refers to the situation of inhalable particulate matter near the detection point, or whether dust is diffused by means of image recognition. The image recognition method here can increase the credibility through multiple sampling angles.

[0049] Furthermore, the dust reduction equipment data collection unit collects the humidity at each dust reduction equipment using the following expression:

[0050] RH t =[RH t,1 ,…,RH t,i ,…,RH t,n ]

[0051] Among them, RH t Represents the humidity data set at the dust suppression equipment at time t, RH t,1 ,…,RH t,i ,…,RH t,nThe humidity values ​​at the first detection point, ..., the humidity values ​​at the i-th detection point, ..., the humidity values ​​at the n-th detection point can be used to determine whether the dust suppression spray is damaged, resulting in the inability of dust in this area to settle on the ground. If dust still occurs when the dust suppression equipment at that location is not damaged, it indicates that dust is caused by human factors.

[0052] Furthermore, the dust data analysis and early warning module analyzes the dust situation in the following steps:

[0053] A1. Dust situation yc for the i-th detection point t,i To judge, if the dust situation yc of the i-th detection point t,i If it is judged that the dust threshold is exceeded, the equipment maintenance unit is called;

[0054] A2. Humidity value RH at the i-th detection point t,i To judge, if the humidity value RH at the i-th detection point t,i When it is lower than the set humidity threshold RH0, the humidity value adjacent to the i-th detection point is detected. If the humidity value adjacent to the i-th detection point is normal, the judgment result is that the dust reduction equipment is damaged and needs maintenance. If the comprehensive humidity value adjacent to the i-th detection point is also lower than the set humidity threshold RH0, it is judged that the local airflow is too large and the judgment is terminated. If the humidity value adjacent to the i-th detection point is not lower than the set humidity threshold RH0, the judgment result is that no maintenance is required, and the data collection module at the dust point is started.

[0055] Furthermore, the expression of the comprehensive humidity value adjacent to the i-th detection point in step A2 is as follows:

[0056]

[0057] Among them, ZHRH t,i It represents the comprehensive humidity value of the vicinity of the i-th detection point at time t. It represents the sum of the humidity values ​​at the two detection points after the i-th detection point. It represents the sum of the humidity values ​​at the first detection point and the two detection points after the i-th detection point. It represents the sum of the humidity values ​​at the two detection points before and after the i-th detection point. Represents the sum of the humidity values ​​at the two detection points before the i-th detection point.

[0058] The target dust type identification unit in the target tracking module identifies dust types including residual dust from tires, cargo load exceeding the height limit and vehicle spillage. After the current vehicle identifies one or more types, the identified one or more types are sent to the target tracking unit for tracking and identification.

[0059] Furthermore, the calculation expression for the target dust type identification unit to identify the residual dust on the tire is as follows:

[0060]

[0061] Where, μ represents the residual amount of dust left in the tire, CHL cl Indicates the total number of pixels selected by the cl-th wheel in the image, GRAY cl It indicates the total number of non-black pixels of the cl-th wheel selected in the image. CL indicates the total number of wheels of the current vehicle. When μ≥0.5, it indicates that there is too much residual dust on the tire. In this case, the output dust type is residual dust on the tire.

[0062] Furthermore, the target dust type identification unit identifies that the cargo load exceeds the height limit by the following calculation expression:

[0063] ΔH=H0-H max

[0064] Among them, H0 represents the current vehicle cargo height, H max It indicates the current vehicle loading height limit, ΔH indicates the height difference. When ΔH>0, it indicates that the current vehicle loading height is too high. At this time, the output dust type is that the loading height exceeds the height limit. When the loading height of the vehicle transporting slag exceeds the height limit, the slope angle of the slag pile will exceed the repose angle during transportation, and the slag will be scattered from the gaps in the cover.

[0065] Furthermore, the target dust type identification unit identifies the vehicle leakage calculation expression as follows:

[0066]

[0067] Among them, M0 represents the current initial load of the vehicle, M i It indicates the load of the current vehicle at the i-th detection point, ΔM indicates the load deviation, and when ΔM>0.05, it means that the vehicle leaks dust, and the output dust type is vehicle leaks dust.

[0068] Furthermore, the target tracking unit uploads the license plate data to the management personnel, identifies the license plate data of the vehicle at each detection point, and feeds back the image data to the management personnel for early warning. The identification here includes but is not limited to the identification of vehicle models. PP-HGNet can also be used here for GPU devices. The current GPU-friendly networks are analyzed and summarized, and 3x3 standard convolutions (with the highest computational density) are used as much as possible. The main improvements that are conducive to GPU reasoning are integrated to obtain a backbone network that is conducive to GPU reasoning. At the same speed, the accuracy greatly exceeds that of other CNN or VisionTransformer models. And the number of standard convolutions increases with the depth of the layers, so as to obtain a backbone network that is conducive to GPU reasoning. At the same speed, the accuracy also exceeds that of other CNNs, and the cost-effectiveness is better than the ViT-base model, and recognition and detection are performed in this way.

[0069] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dust control system with automatic monitoring and real-time early warning, characterized by: It includes dust data collection module, dust data analysis and early warning module, dust point data collection module and target tracking module; The dust data collection module includes a dust situation collection unit and a dust suppression equipment data collection unit. The dust situation collection unit is used to collect the dust situation in the current environment and send the dust data to the dust data analysis and early warning module for early warning. The dust suppression equipment data collection unit is used to collect the humidity of each dust suppression equipment and send the humidity data to the dust data analysis and early warning module; The dust data analysis and warning module includes a dust warning unit and an equipment maintenance unit. The dust warning unit is used to analyze and warn the dust situation in the current environment. When dust occurs, the equipment maintenance unit is called to determine whether the dust suppression equipment is operating normally and whether it needs maintenance. If maintenance is not required, the data collection module at the dust point is started; The data acquisition module at the dust point is used to perform image recognition on the point where dust occurs, and record the license plate of the currently recognized vehicle, and collect the vehicle data at the same time, the vehicle data includes the vehicle tire color, vehicle cargo height and vehicle weight, and send the vehicle data and license plate to the target tracking module for tracking; The target tracking module includes a target dust type identification unit and a target tracking unit. The target dust type identification unit is used to identify the dust type of the target vehicle, and send the vehicle data and license plate of the determined dust type to the target tracking unit, and track and identify the vehicle through the target tracking unit, and notify the management personnel to handle it.

2. The dust control system with automatic monitoring and real-time early warning according to claim 1 is characterized by: The dust collection unit collects dust in the current environment using the following expression: YC t =[yc t,1 ,…,yc t,i ,…,yc t,n ] Among them, yc t,1 ,…,yc t,i ,…,yc t,n They represent the dust situation at the first detection point, ..., the dust situation at the i-th detection point, ..., the dust situation at the n-th detection point, respectively. YC t Represents the dust dataset at time t.

3. The dust control system with automatic monitoring and real-time early warning according to claim 2 is characterized by: The dust reduction equipment data collection unit collects the humidity at each dust reduction equipment using the following expression: RH t =[RH t,1 ,…,RH t,i ,…,RH t,n ] Among them, RH t Represents the humidity data set at the dust suppression equipment at time t, RH t,1 ,…,RH t,i ,…,RH t,n The humidity value at the 1st detection point, ..., the humidity value at the i-th detection point, ..., the humidity value at the n-th detection point.

4. The dust control system with automatic monitoring and real-time early warning according to claim 3 is characterized by: The steps of analyzing the dust situation by the dust data analysis and early warning module are as follows: A1. Dust situation yc for the i-th detection point t,i To judge, if the dust situation yc of the i-th detection point t,i If it is judged that the dust threshold is exceeded, the equipment maintenance unit is called; A2. Humidity value RH at the i-th detection point t,i To judge, if the humidity value RH at the i-th detection point t,i When it is lower than the set humidity threshold RH0, the humidity value adjacent to the i-th detection point is detected. If the humidity value adjacent to the i-th detection point is normal, the judgment result is that the dust reduction equipment is damaged and needs maintenance. If the comprehensive humidity value adjacent to the i-th detection point is also lower than the set humidity threshold RH0, it is judged that the local airflow is too large and the judgment is terminated. If the humidity value adjacent to the i-th detection point is not lower than the set humidity threshold RH0, the judgment result is that no maintenance is required, and the data collection module at the dust point is started.

5. The dust control system with automatic monitoring and real-time early warning according to claim 4 is characterized by: The expression of the comprehensive humidity value of the i-th detection point adjacent to the i-th detection point in step A2 is as follows: Among them, ZHRH t,i It represents the comprehensive humidity value of the vicinity of the i-th detection point at time t. It represents the sum of the humidity values ​​at the two detection points after the i-th detection point. It represents the sum of the humidity values ​​at the first detection point and the two detection points after the i-th detection point. It represents the sum of the humidity values ​​at the two detection points before and after the i-th detection point. Represents the sum of the humidity values ​​at the two detection points before the i-th detection point.

6. The dust control system with automatic monitoring and real-time early warning according to claim 1 is characterized by: The target dust type identification unit in the target tracking module identifies dust types including residual dust from tires, cargo load exceeding the height limit and vehicle spillage. After the current vehicle identifies one or more types, the identified one or more types are sent to the target tracking unit for tracking and identification.

7. The dust control system with automatic monitoring and real-time early warning according to claim 6 is characterized by: The target dust type identification unit identifies the residual dust on the tire using the following calculation expression: Where, μ represents the residual amount of dust left in the tire, CHL cl Indicates the total number of pixels selected by the cl-th wheel in the image, GRAY cl It indicates the total number of non-black pixels of the cl-th wheel selected in the image. CL indicates the total number of wheels of the current vehicle. When μ≥0.5, it indicates that there is too much residual dust on the tire. In this case, the output dust type is residual dust on the tire.

8. The dust control system with automatic monitoring and real-time early warning according to claim 6 is characterized by: The calculation expression for the target dust type identification unit to identify the cargo load exceeding the height limit is as follows: ΔH=H0-H max Among them, H0 represents the current vehicle cargo height, H max Indicates the current vehicle cargo height limit, ΔH indicates the height difference. When ΔH>0, it indicates that the current vehicle cargo height is too high. At this time, the output dust type is cargo load exceeds height limit.

9. The dust control system with automatic monitoring and real-time early warning according to claim 6 is characterized by: The target dust type identification unit identifies the vehicle's leakage calculation expression as follows: Among them, M0 represents the current initial load of the vehicle, M i It indicates the load of the current vehicle at the i-th detection point, ΔM indicates the load deviation, and when ΔM>0.05, it means that the vehicle leaks dust, and the output dust type is vehicle leaks dust.

10. The dust control system with automatic monitoring and real-time early warning according to claim 1 is characterized by: The target tracking unit uploads the license plate data to the management personnel, identifies the license plate data of the vehicle at each detection point, and feeds back the image data to the management personnel.

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