Method and system for detecting flying dust on road surface of transportation road in mining area

Abstract

The invention relates to the technical field of environment monitoring, in particular to a mining area transportation road pavement dust detection method and system. The method comprises the steps that real-time point cloud data collected by a laser radar and vehicle information of a mining area transport vehicle are acquired, the point cloud data are analyzed, and dust accumulation area information is determined; the dust accumulation data after the last cleaning is called; according to the dust accumulation data and the dust accumulation area information, the dust accumulation condition at the current moment is determined; according to the vehicle information and the accumulated dust accumulation condition, the dust raising amount is predicted; and determining whether to clean the road surface according to the dust raising amount.

Description

Technical Field

[0001] The present application relates to the field of environmental monitoring technology, and in particular to a method and system for detecting dust on a mining transport road surface. Background Art

[0002] With the large-scale mining of mineral resources in my country, the dust problem on the transportation roads in mining areas is becoming increasingly serious. Dust not only pollutes the environment around the mining area, but also seriously affects road driving safety.

[0003] At present, the research on dust detection on mining transportation roads at home and abroad mainly focuses on the monitoring of particle concentration and the identification of dust sources. The main methods for monitoring particle concentration include weight method, light scattering method, light absorption method, etc. These methods can reflect the degree of dust pollution to a certain extent, but cannot accurately determine the source of dust, so as to accurately suppress dust generation from the root. Summary of the invention

[0004] The present application provides a method and system for detecting dust on a mining transport road surface to solve the above-mentioned problem.

[0005] In a first aspect, the present application provides a method for detecting dust on a mining transport road surface, the method for detecting dust on a mining transport road surface is applied to a dust detection device, the dust detection device includes a server and a laser radar, the method is applied to the server, and the method includes: Acquire the real-time point cloud data collected by the laser radar and the vehicle information of the mining area transport vehicle, analyze the point cloud data, and determine the dust accumulation area information; Retrieving dust accumulation data after the last cleaning; determining the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information; The amount of dust is predicted based on the vehicle information and the dust accumulation situation; and whether to perform road cleaning is determined based on the amount of dust.

[0006] Through the method provided by this embodiment, by acquiring the real-time point cloud data collected by the laser radar and the vehicle information of the mining area transport vehicle, the system can monitor the road dust situation in real time and accurately identify the dust accumulation area. This helps to understand the distribution and changes of dust in a timely manner, so as to take effective control measures. Retrieving the dust accumulation data after the last cleaning, combined with the current dust accumulation area information, can provide data-driven decision support for decision makers. By analyzing these data, the cleaning time and frequency can be scientifically planned to improve the cleaning efficiency. Determining the dust accumulation situation at the current moment helps to take timely measures to reduce the pollution of dust to the surrounding environment of the mining area. By predicting the amount of dust, intervention can be carried out before the dust is generated, thereby reducing the emission of pollutants. Dust not only pollutes the environment, but also reduces visibility and affects road driving safety. By predicting the amount of dust and deciding whether to clean the road surface accordingly, the impact of dust on vision can be effectively reduced and the driving safety of the road can be improved. According to the prediction results of the amount of dust, cleaning resources, such as cleaning vehicles and personnel, can be allocated in a targeted manner to avoid waste of resources and ensure effective cleaning work when necessary.

[0007] Optionally, analyzing the point cloud data to determine dust accumulation area information includes: Obtaining mining area transportation information; analyzing the mining area transportation information to determine the type of dust accumulation; Acquire meteorological data within a first preset time period; analyze the meteorological data to determine the meteorological impact of different meteorological conditions within the preset time period on the dust accumulation type; Determine the type of transport vehicle according to the vehicle information; Determining the dust accumulation form according to the type of transport vehicle; Analyze the dust accumulation morphology and determine the data type mapped to the point cloud; Based on the data type and according to the meteorological influence, the point cloud data is analyzed to determine the dust accumulation area information.

[0008] Through the method provided by this embodiment, by analyzing the point cloud data, the dust accumulation area on the road can be more accurately identified and located, thereby improving the accuracy and reliability of dust detection. Determining the dust accumulation area information helps to optimize the allocation of cleaning resources, concentrate the cleaning force on the areas with the most serious dust accumulation, improve cleaning efficiency, and reduce resource waste. By cleaning the dust accumulation area in a timely manner, the generation and emission of dust can be effectively reduced, the environmental quality around the mining area can be improved, and air pollution can be reduced.

[0009] Optionally, determining the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information includes: Determining the dust accumulation density at the current moment according to the dust accumulation form; Determining a dust accumulation range according to the dust accumulation area information; Determining a current dust accumulation change amount according to the dust accumulation data; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change.

[0010] Through the method provided in this embodiment, by analyzing the dust morphology to determine the dust density, the dust accumulation on the road can be monitored more accurately, providing a basis for formulating targeted cleaning and maintenance plans. Determining the range of dust accumulation helps managers understand the distribution of dust accumulation, so as to allocate cleaning resources in a targeted manner and improve the efficiency of cleaning work. By monitoring the current change in dust accumulation, the trend of increasing or decreasing dust accumulation can be discovered in time, so that timely measures can be taken to respond and prevent the deterioration of dust problems. Accurate analysis of dust accumulation helps to reduce dust emissions, improve the environmental quality around mining areas, and protect public health. Monitoring and timely cleaning of dust accumulation can reduce dust on the road, improve road visibility and driving safety.

[0011] Optionally, determining the dust accumulation condition according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change includes: Acquire road traffic data for a second preset time period; Analyze the road traffic data to determine the type of passing vehicles; Determining the total weight of the vehicle based on the type of vehicle passing through; Predicting a change in dust density based on the vehicle's total load weight; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, the current dust accumulation change and the dust accumulation density change.

[0012] Through the method provided by this embodiment, by analyzing the types of passing vehicles and the total weight of the load, the change in dust density caused by vehicle traffic can be more accurately predicted, thereby improving the prediction accuracy of dust accumulation. Understanding the road traffic conditions and dust changes in different time periods will help optimize the allocation of cleaning resources and ensure that more cleaning forces are invested in periods and areas with more dust. Predicting the change in dust density can help relevant departments take preventive measures in advance, such as increasing the frequency of cleaning, using sprinkler trucks to reduce dust, etc., to reduce the impact of dust on the environment and road safety. Combined with road traffic data, the cleaning and maintenance of mining transportation roads can be managed more effectively and management efficiency can be improved.

[0013] Optionally, the analyzing the point cloud data based on the data type and according to the meteorological influence to determine the dust accumulation area information includes: Analyze the meteorological impact and determine the first point cloud shape after the first meteorological change; Analyze the influence of other different weather conditions on the first point cloud shape to determine the final point cloud shape; Analyzing the point cloud data according to the final point cloud form to determine the dust point cloud features; Determining dust accumulation area information according to the dust accumulation point cloud features; Determining the dust density at the current moment according to the dust accumulation form includes: The dust accumulation density at the current moment is determined according to the final point cloud shape.

[0014] Through the method provided by this embodiment, through point cloud data analysis, a detailed dust distribution map can be generated to show the thickness and density of dust in different areas. Combined with meteorological data, changes in dust areas can be dynamically monitored, such as dust accumulation or removal over time. By identifying the source of dust, targeted measures can be taken to control dust generation from the source. By analyzing point cloud data, the long-term trend of dust can be identified, providing a basis for long-term planning. By analyzing point cloud data, dust areas can be more accurately identified and located, thereby improving the accuracy and efficiency of dust monitoring. Timely identification of dust area information helps to quickly respond to dust problems and reduce the impact on the environment and road safety. Accurate dust area information can guide cleaning and maintenance work, optimize resource allocation, and avoid waste of resources. Determining dust area information helps to assess the impact of dust on the environment, including air quality and ecosystem health. Understanding dust areas helps reduce road driving safety risks, such as reduced visibility and vehicle skidding.

[0015] Optionally, predicting the amount of dust according to the vehicle information and the dust accumulation condition includes: Determine the vehicle type and vehicle load according to the vehicle information; Obtaining historical traffic records, and determining the average speed of each type of vehicle passing through the mining area transportation road according to the historical traffic records; Analyzing the final point cloud morphology to determine the amount of particle dust; Obtain basic information of the mining area transportation road and determine the road width; Determining the dust range according to the road width and the dust accumulation area information; The amount of dust is predicted according to the amount of particulate dust, the range of dust generation, the average speed and the vehicle load.

[0016] Through the method provided by this embodiment, effective dust control measures can be implemented in advance according to the predicted dust volume through the prediction results, and targeted control measures can be implemented in specific areas or time periods, which can significantly reduce the concentration of particulate matter in the air around the mining area. It helps environmental managers better understand the temporal and spatial distribution of dust, thereby optimizing environmental management strategies. Reduce the damage of dust to roads, extend the service life of roads, and reduce road maintenance costs. Reduce the impact of dust on visibility and road friction coefficient, improve driver visibility and vehicle braking effect.

[0017] Optionally, determining whether to perform road cleaning according to the amount of dust includes: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the degree of visual interference according to the dust volume and the dust height; Whether to perform road cleaning is determined according to the degree of visual interference.

[0018] Through the method provided by this embodiment, by real-time monitoring of dust volume, dust problems can be discovered in time, and an early warning can be issued when the dust volume reaches a certain threshold, and cleaning measures can be taken in advance; based on the dust volume data, the timing and scope of road cleaning can be accurately controlled to avoid excessive cleaning and unnecessary waste of resources. By timely cleaning of dust, the risk of slippery roads and reduced visibility can be reduced, thereby improving the driving safety of drivers and reducing traffic accidents. Determining the cleaning frequency based on the dust volume can optimize the allocation of human resources and equipment resources and improve work efficiency. When the degree of visual interference is low, frequent cleaning may not be required, thereby saving costs. When the degree of visual interference is high, timely cleaning can quickly restore road visibility and reduce safety hazards.

[0019] Optionally, determining whether to perform road cleaning according to the amount of dust includes: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the severity of dust emission according to the dust emission volume and the dust emission height; Determine whether to clean the road surface based on the severity of the dust.

[0020] The method provided in this embodiment helps to understand the actual distribution of dust and provide data support for subsequent cleaning work. By calculating the severity of dust, the impact of dust on the environment and traffic can be more intuitively understood. When dust reaches a certain level, timely cleaning can prevent dust from spreading and reduce pollution. When dust does not reach a certain standard, unnecessary cleaning can be avoided to save costs.

[0021] Optionally, the dust accumulation condition is determined according to the dust density, the dust range, the current dust change and the dust density change, and is calculated according to the following formula: ; in, Indicates the accumulation index; Indicates the influence weight of the dust accumulation density on the accumulation condition index; Indicates the dust accumulation density; Indicates the influence weight of the dust accumulation range on the accumulation condition index; Indicates the dust accumulation range; Indicates the influence weight of the dust accumulation density change on the accumulation condition index; is the change in dust density over a long period of time; Indicates the length of the first preset period of time.

[0022] Through the method provided in this embodiment, the formula provides a comprehensive indicator for evaluating the dust accumulation on the transportation roads in the mining area, including the total amount of dust accumulation, distribution range and change trend. By adjusting the coefficient, the influence of dust density, dust accumulation range and dust density change can be weighted according to actual conditions and needs. The introduction of the time factor enables the formula to reflect the changes in dust accumulation over time, which helps to dynamically monitor and manage dust problems.

[0023] In a second aspect, the present application provides a mining area transport road pavement dust detection system, the system comprising: An information acquisition module is used to acquire real-time point cloud data collected by the laser radar and vehicle information of the mining area transport vehicle, analyze the point cloud data, and determine the dust accumulation area information; The accumulation analysis module is used to retrieve the dust accumulation data after the last cleaning; and determine the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information; The prediction module is used to predict the amount of dust according to the vehicle information and the dust accumulation situation; and determine whether to clean the road surface according to the amount of dust.

[0024] Optionally, when the information acquisition module analyzes the point cloud data to determine the dust accumulation area information, it is used to: Obtaining mining area transportation information; analyzing the mining area transportation information to determine the type of dust accumulation; Acquire meteorological data within a first preset time period; analyze the meteorological data to determine the meteorological impact of different meteorological conditions within the preset time period on the dust accumulation type; Determine the type of transport vehicle according to the vehicle information; Determining the dust accumulation form according to the type of transport vehicle; Analyze the dust accumulation morphology and determine the data type mapped to the point cloud; Based on the data type and according to the meteorological influence, the point cloud data is analyzed to determine the dust accumulation area information.

[0025] Optionally, when the accumulation analysis module determines the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information, it is used to: Determining the dust accumulation density at the current moment according to the dust accumulation form; Determining a dust accumulation range according to the dust accumulation area information; Determining a current dust accumulation change amount according to the dust accumulation data; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change.

[0026] Optionally, when the accumulation analysis module determines the dust accumulation condition according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change, it is used to: Acquire road traffic data for a second preset time period; Analyze the road traffic data to determine the type of passing vehicles; Determining the total weight of the vehicle based on the type of vehicle passing through; Predicting a change in dust density based on the vehicle's total load weight; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, the current dust accumulation change and the dust accumulation density change.

[0027] Optionally, when the information acquisition module analyzes the point cloud data based on the data type and according to the meteorological influence to determine the dust accumulation area information, it is used to: Analyze the meteorological impact and determine the first point cloud shape after the first meteorological change; Analyze the influence of other different weather conditions on the first point cloud shape to determine the final point cloud shape; Analyzing the point cloud data according to the final point cloud form to determine the dust point cloud features; Determining dust accumulation area information according to the dust accumulation point cloud features; When determining the dust density at the current moment according to the dust accumulation form, it is used to: The dust accumulation density at the current moment is determined according to the final point cloud shape.

[0028] Optionally, when the prediction module predicts the amount of dust according to the vehicle information and the dust accumulation condition, it is used to: Determine the vehicle type and vehicle load according to the vehicle information; Obtaining historical traffic records, and determining the average speed of each type of vehicle passing through the mining area transportation road according to the historical traffic records; Analyzing the final point cloud morphology to determine the amount of particle dust; Obtain basic information of the mining area transportation road and determine the road width; Determining the dust range according to the road width and the dust accumulation area information; The amount of dust is predicted according to the amount of particulate dust, the range of dust generation, the average speed and the vehicle load.

[0029] Optionally, when the prediction module determines whether to perform road cleaning according to the dust amount, it is used to: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the degree of visual interference according to the dust volume and the dust height; Whether to perform road cleaning is determined according to the degree of visual interference.

[0030] Optionally, when the prediction module determines whether to perform road cleaning according to the dust amount, it is used to: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the severity of dust emission according to the dust emission volume and the dust emission height; Determine whether to clean the road surface based on the severity of the dust.

[0031] Optionally, the accumulation analysis module determines the dust accumulation situation according to the dust accumulation density, the dust accumulation range, the current dust accumulation change and the dust accumulation density change, and calculates according to the following formula: ; in, Indicates the accumulation index; Indicates the influence weight of the dust accumulation density on the accumulation condition index; Indicates the dust accumulation density; Indicates the influence weight of the dust accumulation range on the accumulation condition index; Indicates the dust accumulation range; Indicates the influence weight of the dust accumulation density change on the accumulation condition index; is the change in dust density over a long period of time; Indicates the length of the first preset period of time. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flow chart of a method for detecting dust on a mining transport road provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a dust detection system for mining transport roads provided in one embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0036] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0037] With the large-scale mining of mineral resources in my country, the dust problem on the transportation roads in mining areas is becoming increasingly serious. Dust not only pollutes the environment around the mining area, but also seriously affects road driving safety.

[0038] At present, the research on dust detection on mining transportation roads at home and abroad mainly focuses on the monitoring of particle concentration and the identification of dust sources. The main methods for monitoring particle concentration include weight method, light scattering method, light absorption method, etc. These methods can reflect the degree of dust pollution to a certain extent, but cannot accurately determine the source of dust, so as to accurately suppress dust generation from the root.

[0039] Based on this, the present application provides a method and system for detecting dust on the road surface of a mining area transportation road, obtains the real-time point cloud data collected by the laser radar and the vehicle information of the mining area transportation vehicle, analyzes the point cloud data, and determines the dust accumulation area information; retrieves the dust accumulation data after the last cleaning; determines the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information; predicts the dust amount according to the vehicle information and the dust accumulation situation; and determines whether to clean the road surface according to the dust amount. By obtaining the real-time point cloud data collected by the laser radar and the vehicle information of the mining area transportation vehicle, the system can monitor the road dust situation in real time and accurately identify the dust accumulation area. This helps to understand the distribution and changes of dust in a timely manner, so as to take effective control measures. Retrieving the dust accumulation data after the last cleaning, combined with the current dust accumulation area information, can provide data-driven decision support for decision makers. By analyzing these data, the cleaning time and frequency can be scientifically planned to improve the cleaning efficiency. Determining the dust accumulation situation at the current moment helps to take timely measures to reduce the pollution of dust to the surrounding environment of the mining area. By predicting the amount of dust, intervention can be made before dust is generated, thereby reducing pollutant emissions.

[0040] Figure 1 A schematic diagram of an application scenario provided for this application, when detecting dust on the mine transport road, the method provided by this application is applied, specifically, the method provided by this application is applied to any server, the server interacts with the laser radar, and by obtaining the real-time point cloud data collected by the laser radar and the vehicle information of the mine transport vehicle, the system can monitor the road dust situation in real time and accurately identify the dust accumulation area. This helps to understand the distribution and changes of dust in a timely manner, so as to take effective control measures. Retrieving the dust accumulation data after the last cleaning, combined with the current dust accumulation area information, can provide data-driven decision support for decision makers. By analyzing these data, the cleaning time and frequency can be scientifically planned to improve the cleaning efficiency. Determining the dust accumulation situation at the current moment helps to take timely measures to reduce the pollution of dust to the surrounding environment of the mining area. By predicting the amount of dust, intervention can be made before dust is generated, thereby reducing the emission of pollutants.

[0041] For specific implementation methods, please refer to the following embodiments.

[0042] Figure 2 This is a flow chart of a method for detecting dust on a mining transport road surface provided in an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201, obtaining real-time point cloud data collected by the laser radar and vehicle information of the mining area transport vehicle, analyzing the point cloud data, and determining the dust accumulation area information.

[0043] Point cloud data can be a set of three-dimensional coordinate points on the surface of a mine transportation road captured by lidar at a specific moment, which can reflect the morphology and characteristics of the road surface, including dust accumulation.

[0044] The vehicle information may be various attributes of the mining area transport vehicle, such as vehicle type (such as truck, bus, etc.), license plate number, vehicle size, load, driving speed, etc.

[0045] The dust accumulation area information may be the distribution of dust accumulation on the road obtained by analyzing point cloud data, including the location, range, shape, etc. of the dust accumulation.

[0046] Specifically, in order to monitor the dust situation on the mine transportation roads in real time, it is necessary to install sensor equipment such as lidar at the monitoring stations beside the roads to capture the point cloud data of the mine transportation roads in real time. Point cloud data can provide three-dimensional information of the road surface and provide basic data for the subsequent identification of dust accumulation areas. Through cameras, RFID, license plate recognition and other equipment installed at monitoring stations or transport vehicles, vehicle information of mine transport vehicles, including vehicle type, license plate number, load, etc., is collected. The point cloud data is processed using image processing and machine learning algorithms to identify dust accumulation areas. The algorithm is trained to distinguish between dust accumulation areas and non-dust accumulation areas. Combined with the vehicle's driving trajectory and mine transportation information, the specific location and range of the dust accumulation area are further determined.

[0047] S202, retrieve dust accumulation data after the last cleaning; determine the dust accumulation situation at the current moment according to the dust accumulation data and dust accumulation area information.

[0048] The dust accumulation data may be historical data recording the physical properties (such as thickness, density, particle size, etc.) and distribution of the dust accumulation.

[0049] The last cleaning may be the last cleaning work performed on the mining area transportation roads, including sweeping, flushing and other operations to remove dust accumulated on the road surface.

[0050] The dust accumulation condition may be the accumulation state of dust on the road surface at the current moment, including the thickness, density, distribution range, etc. of the dust.

[0051] Specifically, the dust accumulation data after the last cleaning is extracted from the database, including dust thickness, distribution area, etc. These data are analyzed to compare with the dust accumulation situation at the current moment. The increment of dust accumulation is calculated by comparing the current point cloud data with the data after the last cleaning. The density, range and change of dust accumulation are analyzed to determine the dust accumulation situation at the current moment.

[0052] S203: predicting the amount of raised dust based on vehicle information and dust accumulation; and determining whether to perform road cleaning based on the amount of raised dust.

[0053] Dust emission can be the total amount of dust particles suspended from the road surface into the air due to vehicle movement or other factors such as wind.

[0054] Road cleaning can be the cleaning of the surface of mining transportation roads to reduce the generation and emission of dust, including the use of sweepers, sprinklers and other equipment for cleaning and flushing.

[0055] Specifically, analyze vehicle information, including vehicle type and load, which are directly related to the amount of dust. Combined with the dust accumulation, use a prediction model to estimate the amount of dust. Establish a threshold standard for the amount of dust, and issue a cleaning instruction when the predicted amount of dust exceeds the threshold. For example, the impact of dust on the surrounding environment, such as the degree of visual interference and air quality, can be used to determine the necessity and urgency of cleaning.

[0056] Through the method provided by this embodiment, by acquiring the real-time point cloud data collected by the laser radar and the vehicle information of the mining area transport vehicle, the system can monitor the road dust situation in real time and accurately identify the dust accumulation area. This helps to understand the distribution and changes of dust in a timely manner, so as to take effective control measures. Retrieving the dust accumulation data after the last cleaning, combined with the current dust accumulation area information, can provide data-driven decision support for decision makers. By analyzing these data, the cleaning time and frequency can be scientifically planned to improve the cleaning efficiency. Determining the dust accumulation situation at the current moment helps to take timely measures to reduce the pollution of dust to the surrounding environment of the mining area. By predicting the amount of dust, intervention can be carried out before the dust is generated, thereby reducing the emission of pollutants. Dust not only pollutes the environment, but also reduces visibility and affects road driving safety. By predicting the amount of dust and deciding whether to clean the road surface accordingly, the impact of dust on vision can be effectively reduced and the driving safety of the road can be improved. According to the prediction results of the amount of dust, cleaning resources, such as cleaning vehicles and personnel, can be allocated in a targeted manner to avoid waste of resources and ensure effective cleaning work when necessary.

[0057] In some embodiments, mining area transportation information is obtained; mining area transportation information is analyzed to determine the type of dust accumulation; meteorological data within a first preset time period is obtained; meteorological data is analyzed to determine the meteorological impact of different meteorological conditions on the type of dust accumulation within the first preset time period; based on vehicle information, the type of transport vehicle is determined; based on the type of transport vehicle, the dust morphology is determined; the dust morphology is analyzed to determine the type of data mapped to the point cloud; based on the data type and according to the meteorological impact, the point cloud data is analyzed to determine the dust accumulation area information.

[0058] The mining area transportation information may be various information related to the mining area transportation activities, including but not limited to the type of transportation vehicle, license plate number, load, driving speed, driving track, etc.

[0059] The type of dust deposited can be a variety of road surface deposits, depending on the type of goods transported in the mining area and the characteristics of the vehicles traveling. For example, coal transportation may produce black coal dust, while ore transportation may produce ore dust of different colors and particle sizes.

[0060] The first preset time period may be a time period from the last cleaning to the present, which is preset for analyzing the dust situation and is stored in a preset database.

[0061] Meteorological data can be the measured values ​​of meteorological elements that affect the generation and spread of dust, including wind speed, wind direction, humidity, temperature, precipitation, etc.

[0062] Meteorological influences can be the effects of meteorological conditions on the generation and diffusion of dust. For example, wind speed and direction can determine the direction and distance of dust propagation, humidity can affect the settling speed of dust, and temperature can affect the volatility and stability of dust.

[0063] The type of transport vehicle can be various types of vehicles used for transportation in mining areas, such as heavy trucks, light trucks, dump trucks, trailers, etc. Different types of vehicles have different effects on the generation of dust due to their size, load and driving characteristics.

[0064] Dust morphology can be the physical state and structure of road surface sediments, including particle size, shape, density, distribution, etc. Dust morphology affects the generation and diffusion characteristics of dust.

[0065] Specifically, the sensors, GPS positioning systems and other equipment installed on the transport vehicles in the mining area are used to collect the vehicle's driving trajectory, speed, load and other transportation information. The license plate recognition system or RFID technology is used to automatically identify and record the information of vehicles passing through the mining area's transportation roads. According to the vehicle's load, type and driving frequency, the types and characteristics of dust accumulation generated by different vehicles on the road surface are analyzed. Combined with the type of goods transported in the mining area (such as coal, ore, etc.), the size, shape and density of dust particles that may be generated are determined. Meteorological data such as wind speed, wind direction, humidity and temperature are collected through meteorological stations or mobile meteorological monitoring equipment. Ensure that the collection period of meteorological data matches the peak period of transportation activities in the mining area. Analyze the impact of wind speed and wind direction on dust diffusion and determine which meteorological conditions may lead to an increase in dust, such as the adsorption and sedimentation of dust particles by humidity and the impact of temperature on the volatility of dust particles. Classify the collected vehicle information, distinguish different types of transport vehicles, and infer the dust accumulation form generated by the vehicle on the road surface in combination with the vehicle type and load information. Analyze the dust patterns that may be generated during vehicle driving, such as dust from the rear of the vehicle and dust under the tires. According to the characteristics of the dust accumulation form, select appropriate point cloud data processing methods, such as filtering, segmentation, feature extraction, etc. Determine the data type used to identify the dust accumulation area, such as the height, intensity, number of echoes and other features in the point cloud. Use the selected point cloud data processing method to process the real-time point cloud data and extract the information of the dust accumulation area. Combined with meteorological data, analyze the distribution and changes of dust accumulation areas under different meteorological conditions to determine the specific location and range of the dust accumulation area.

[0066] Through the method provided by this embodiment, by analyzing the point cloud data, the dust accumulation area on the road can be more accurately identified and located, thereby improving the accuracy and reliability of dust detection. Determining the dust accumulation area information helps to optimize the allocation of cleaning resources, concentrate the cleaning force on the areas with the most serious dust accumulation, improve cleaning efficiency, and reduce resource waste. By cleaning the dust accumulation area in a timely manner, the generation and emission of dust can be effectively reduced, the environmental quality around the mining area can be improved, and air pollution can be reduced.

[0067] In some embodiments, the dust density at the current moment is determined based on the dust morphology; the dust range is determined based on the dust area information; the current dust change is determined based on the dust data; the dust accumulation situation is determined based on the dust density, dust range, and current dust change.

[0068] Dust density can be the mass of dust per unit area or volume. It can be an indicator to measure the thickness and concentration of dust and reflect the degree of dust accumulation.

[0069] The dust accumulation range can be the area covered by dust on the road, which can be continuous or scattered.

[0070] The current dust accumulation change may be a change in the dust accumulation within a certain period of time, which may be calculated by comparing the current dust accumulation density with the previous dust accumulation density.

[0071] Specifically, the dust density at the current moment is determined by using real-time point cloud data, analyzing the point cloud density distribution in the dust accumulation area, calculating the number of points per unit area or using a special algorithm to estimate the volume or mass density of the dust. Based on the dust accumulation area information, a geographic information system (GIS) or a computer vision algorithm is used to determine the specific range of the dust accumulation, including identifying the boundary of the dust accumulation area and calculating the area of ​​the dust accumulation area. By comparing the dust accumulation data at the current moment with the dust accumulation data after the last cleaning, the change in dust accumulation is determined by calculating the difference in dust density or the change in the area of ​​the dust accumulation area. The dust density, dust accumulation range and dust accumulation change data obtained in the above steps are integrated together to provide comprehensive information for analyzing the dust accumulation situation. Based on the dust accumulation density and dust accumulation range, the total volume or mass of the dust is calculated. The trend of the change in dust accumulation over time is analyzed to determine whether the dust accumulation continues to increase, decrease or remain stable. Based on the calculated dust volume or mass and dust accumulation change trend, the dust accumulation situation at the current moment is determined. This may include the severity of the accumulation, the accumulation speed and the possible dust risk.

[0072] Through the method provided in this embodiment, by analyzing the dust morphology to determine the dust density, the dust accumulation on the road can be monitored more accurately, providing a basis for formulating targeted cleaning and maintenance plans. Determining the range of dust accumulation helps managers understand the distribution of dust accumulation, so as to allocate cleaning resources in a targeted manner and improve the efficiency of cleaning work. By monitoring the current change in dust accumulation, the trend of increasing or decreasing dust accumulation can be discovered in time, so that timely measures can be taken to respond and prevent the deterioration of dust problems. Accurate analysis of dust accumulation helps to reduce dust emissions, improve the environmental quality around mining areas, and protect public health. Monitoring and timely cleaning of dust accumulation can reduce dust on the road, improve road visibility and driving safety.

[0073] In some embodiments, road traffic data for a second preset time period is obtained; the road traffic data is analyzed to determine the type of passing vehicles; based on the type of passing vehicles, the total weight of the vehicle is determined; based on the total weight of the vehicle, the change in dust density is predicted; and based on the dust density, dust range, current dust change and dust density change, the dust accumulation situation is determined.

[0074] The second preset time period may be the time from the last meteorological change to the present, such as from the last precipitation to the present.

[0075] Road traffic data can be various forms of same-direction data of vehicles passing through the road, including information such as vehicle count, vehicle speed, vehicle type, and travel time.

[0076] The types of vehicles passing through can be different types of vehicles, classified according to the structure, purpose or load capacity of the vehicle, such as trucks, buses, motorcycles, etc.

[0077] The gross vehicle weight can be the total weight of the vehicle when fully loaded, including the weight of the vehicle itself and the weight of the cargo or passengers carried.

[0078] The dust density change may be an increase or decrease in the dust density within a certain time interval.

[0079] Specifically, the traffic data on the road within the second preset period is collected by sensors, cameras and other equipment installed on the road. The collected traffic data is processed, and the types of passing vehicles are identified and classified using image recognition or sensor data analysis technology. According to the identified vehicle type, the total load weight of each vehicle is estimated with reference to the vehicle load standard or actual measurement data. For different types of vehicles, a preset average load value can be used or calculated based on actual data. Combined with the total load weight of the vehicle and the dust generation law of the mining area transportation road, a statistical model or a machine learning algorithm is used to analyze the relationship between load and dust generation, and the change in dust density caused by vehicle traffic is predicted. The specific range covered by dust is determined using laser radar technology. The dust density, dust range, current dust change and predicted dust density change data are integrated together. According to the dust density and dust range, the total volume or mass of the dust is calculated. The increase and decrease trend of dust accumulation is analyzed by comprehensively considering the current dust change and the predicted dust density change. Based on the above data and analysis results, the dust accumulation situation at the current moment is determined, including the dust accumulation speed, accumulation density and possible environmental impact.

[0080] Through the method provided by this embodiment, by analyzing the types of passing vehicles and the total weight of the load, the change in dust density caused by vehicle traffic can be more accurately predicted, thereby improving the prediction accuracy of dust accumulation. Understanding the road traffic conditions and dust changes in different time periods will help optimize the allocation of cleaning resources and ensure that more cleaning forces are invested in periods and areas with more dust. Predicting the change in dust density can help relevant departments take preventive measures in advance, such as increasing the frequency of cleaning, using sprinkler trucks to reduce dust, etc., to reduce the impact of dust on the environment and road safety. Combined with road traffic data, the cleaning and maintenance of mining transportation roads can be managed more effectively and management efficiency can be improved.

[0081] In some embodiments, the meteorological impact is analyzed to determine the first point cloud shape after the first meteorological change; the impact of other different meteorological conditions on the first point cloud shape is analyzed to determine the final point cloud shape; based on the final point cloud shape, the point cloud data is analyzed to determine the dust point cloud characteristics; based on the dust point cloud characteristics, the dust accumulation area information is determined; based on the final point cloud shape, the dust density at the current moment is determined.

[0082] The first meteorological change may be the first significant change in meteorological conditions within a certain period of time. For example, the first meteorological change may be a sudden strong wind or a heavy rain.

[0083] The first point cloud form may be the form of a mining area transportation road represented by point cloud data after the first meteorological change. For example, the first point cloud form may show that accumulated dust is blown away due to strong winds, forming an uneven distribution pattern.

[0084] The final point cloud shape may be the road shape in a stable state reflected by the point cloud data after comprehensively considering the influence of all meteorological factors. For example, the final point cloud shape may show that dust accumulates in low-lying areas of the road to form a thick dust layer.

[0085] Point cloud data can be a collection of a large number of spatial points used to represent the three-dimensional shape of an object. In dust monitoring, point cloud data can be detailed three-dimensional coordinates of the road surface and its surroundings collected using lidar or other scanning equipment.

[0086] The dust accumulation point cloud features may be features related to dust accumulation extracted from the point cloud data, including the density of dust accumulation (number of points / unit area), the height variation of the dust accumulation layer, the distribution pattern of dust accumulation, etc.

[0087] The dust accumulation area information may be specific information about the distribution of dust accumulation, including the location, range, thickness and amount of dust accumulation. For example, in an area of ​​100 square meters at the entrance of a mining area, the average dust accumulation thickness is 2 centimeters.

[0088] The dust accumulation form can be the distribution and appearance of the dust accumulation in the space. For example, the dust accumulation form can be a uniformly distributed thin layer, or it can be an uneven block or stripe distribution.

[0089] Dust density can be the mass of dust per unit area or volume, for example, there are 30 grams of dust per square meter in a specific area.

[0090] Specifically, meteorological data related to dust are usually collected from meteorological stations or automatic meteorological observation equipment, including wind speed, wind direction, temperature, humidity, rainfall, etc. Analyze meteorological data to determine the impact of meteorological factors on dust propagation and deposition. For example, wind speed and wind direction will affect the direction and speed of dust diffusion. Collect point cloud data of mining transportation roads, which can be obtained through laser scanning, drone aerial photography or other 3D scanning technologies. Analyze the point cloud data after the first meteorological change (such as a strong wind event) to determine the morphological changes of the point cloud, which may include the thickness and distribution of the dust layer. Compare point cloud data under different meteorological conditions and analyze the impact of meteorological factors on point cloud morphology, such as the impact of wind speed, wind direction and precipitation on dust deposition. Combine all meteorological conditions and point cloud data to determine the final point cloud morphology and reflect the long-term deposition pattern of dust under normal meteorological conditions. Extract the features of dust point cloud from the point cloud data, such as point cloud density, point cloud distribution, point cloud color, etc., and determine the specific information of the dust accumulation area based on the dust point cloud features, combined with meteorological data and point cloud morphology; use point cloud analysis software to calculate the average thickness of the dust layer based on the final point cloud morphology, thereby estimating the dust density. If available, calculate the dust density directly from the point cloud data at the current moment; combine the above analysis results with other data such as particulate matter concentration monitoring data to verify the accuracy of the dust area information.

[0091] Through the method provided by this embodiment, through point cloud data analysis, a detailed dust distribution map can be generated to show the thickness and density of dust in different areas. Combined with meteorological data, changes in dust areas can be dynamically monitored, such as dust accumulation or removal over time. By identifying the source of dust, targeted measures can be taken to control dust generation from the source. By analyzing point cloud data, the long-term trend of dust can be identified, providing a basis for long-term planning. By analyzing point cloud data, dust areas can be more accurately identified and located, thereby improving the accuracy and efficiency of dust monitoring. Timely identification of dust area information helps to quickly respond to dust problems and reduce the impact on the environment and road safety. Accurate dust area information can guide cleaning and maintenance work, optimize resource allocation, and avoid waste of resources. Determining dust area information helps to assess the impact of dust on the environment, including air quality and ecosystem health. Understanding dust areas helps reduce road driving safety risks, such as reduced visibility and vehicle skidding.

[0092] In some embodiments, the vehicle type and vehicle load are determined based on vehicle information; historical traffic records are obtained, and based on the historical traffic records, the average speed of each type of vehicle passing through the mining transportation road is determined; the final point cloud morphology is analyzed to determine the amount of particulate dust; basic information of the mining transportation road is obtained to determine the road width; the dust range is determined based on the road width and dust accumulation area information; the dust amount is predicted based on the particulate dust amount, dust range, average speed and vehicle load.

[0093] The historical travel record may be data recording the travel history of a vehicle on a specific road.

[0094] The amount of particulate matter can be the number or mass of suspended particles in the air per unit volume or per unit area analyzed from point cloud data, such as the total amount of particulate matter in dust caused by vehicle movement or wind.

[0095] The basic information of mining area transportation roads can be data about the basic attributes and characteristics of the roads.

[0096] The dust range can be the area affected by dust caused by vehicle driving or other factors.

[0097] Specifically, the vehicle type, such as truck, bus, dump truck, etc., is identified based on vehicle information, such as license plate number, vehicle registration information, etc. The rated load and actual load of the vehicle are determined by the vehicle type and vehicle registration information; the historical traffic records of vehicles on the mining area transportation road are obtained from the traffic monitoring system, including the travel time, the number of passes, etc. The historical traffic records are analyzed to calculate the average speed of each type of vehicle on the mining area transportation road. The point cloud data analysis technology is used to analyze the final point cloud shape, determine the amount of particulate dust, and obtain the basic information of the mining area transportation road, including the road width, road material, etc.; according to the road width and dust accumulation area information, GIS technology is used to draw a dust distribution map to determine the dust range. According to the amount of particulate dust, dust range, average speed and vehicle load, the amount of dust is predicted using mathematical models or statistical methods. The amount of dust can also be predicted using mathematical models or statistical methods based on the above factors, considering the influence of meteorological factors such as wind speed, wind direction, and humidity.

[0098] Through the method provided by this embodiment, effective dust control measures can be implemented in advance according to the predicted dust volume through the prediction results, and targeted control measures can be implemented in specific areas or time periods, which can significantly reduce the concentration of particulate matter in the air around the mining area. It helps environmental managers better understand the temporal and spatial distribution of dust, thereby optimizing environmental management strategies. Reduce the damage of dust to roads, extend the service life of roads, and reduce road maintenance costs. Reduce the impact of dust on visibility and road friction coefficient, improve driver visibility and vehicle braking effect.

[0099] In some embodiments, the dust height and dust volume are determined based on the amount of dust and the vehicle load; the degree of visual interference is determined based on the dust volume and dust height; and whether to clean the road surface is determined based on the degree of visual interference.

[0100] Dust height can be the height at which dust particles are suspended in the air, starting from the ground, to the height at which dust particles begin to settle due to gravity, air resistance and meteorological conditions.

[0101] The dust volume can be the size of the three-dimensional space occupied by the dust particles.

[0102] The degree of visual interference can be the impact of dust on the clarity of vision. The suspension of dust particles in the air can reduce the transmission of light, thereby reducing visibility and causing blurred vision.

[0103] Specifically, use environmental monitoring equipment (such as a particle monitor) or point cloud data analysis to collect data on changes in dust emissions over different time periods. Since the dust height and dust volume of different types of vehicles are different, use statistical analysis or establish a mathematical model to analyze the relationship between dust emissions and vehicle load to determine the extent to which vehicle load affects dust emissions. Based on dust emission data, combined with meteorological conditions and vehicle driving conditions, use a fluid mechanics model or empirical formula to estimate dust height and volume. Dust height can be calculated using the following formula (1); (1) in, is the dust height; is the amount of dust raised; is the air density; is the vehicle load; is the reference load (usually a standard value); , , is the weight coefficient constant.

[0104] The dust volume can be calculated by the following formula (2); (2) in, is the dust volume; is the amount of dust raised; is the density of dust particles.

[0105] According to the dust height and volume, the impact of dust on visibility is evaluated. The same dust height and dust volume will cause different interference to different vehicles. The degree of interference of dust on vision is calculated in this way. The degree of interference of vision can be calculated by the following formula (3): (3) in, is the degree of visual interference; is the dust volume; is the dust height; , is the weight coefficient.

[0106] The threshold for road cleaning is set according to the degree of visual interference and safety standards, such as the Ambient Air Quality Standard (GB 3095-2012) and the Highway Engineering Technical Standard (JTG B01-2014). For example, when visibility is lower than a certain standard due to dust, cleaning is required. The amount of dust and the degree of visual interference are monitored in real time. When the amount of dust exceeds the preset threshold or the degree of visual interference reaches the cleaning standard, the road cleaning operation is triggered. According to the decision results, the road cleaning work is carried out, including measures such as sprinkling water to reduce dust, sweeping accumulated dust, and using dust suppressants.

[0107] Through the method provided by this embodiment, by real-time monitoring of dust volume, dust problems can be discovered in time, and an early warning can be issued when the dust volume reaches a certain threshold, and cleaning measures can be taken in advance; based on the dust volume data, the timing and scope of road cleaning can be accurately controlled to avoid excessive cleaning and unnecessary waste of resources. By timely cleaning of dust, the risk of slippery roads and reduced visibility can be reduced, thereby improving the driving safety of drivers and reducing traffic accidents. Determining the cleaning frequency based on the dust volume can optimize the allocation of human resources and equipment resources and improve work efficiency. When the degree of visual interference is low, frequent cleaning may not be required, thereby saving costs. When the degree of visual interference is high, timely cleaning can quickly restore road visibility and reduce safety hazards.

[0108] In some embodiments, the dust height and dust volume are determined based on the amount of dust and the vehicle load; the severity of the dust is determined based on the dust volume and dust height; and whether to clean the road surface is determined based on the severity of the dust.

[0109] The severity of dust emission can be the degree to which dust particles on the road surface are lifted up and suspended in the air due to the action of different forces.

[0110] Specifically, use particulate matter monitoring equipment to collect dust data on the transportation roads in the mining area. Collect the load data of passing vehicles, which may require vehicle traffic records or be obtained through weighing equipment. Use empirical formulas or numerical models to calculate the dust volume based on the dust volume. and vehicle load To estimate dust height: (4) in, is the dust height; is the amount of dust raised; is the vehicle load; , , is the weight coefficient constant.

[0111] According to the amount of dust and the density of dust particles ; Use formula (2) to estimate the dust volume.

[0112] Use dust volume and dust height To assess the severity of dust: (5) in, is the severity of dust; is the weight coefficient; is the dust volume; It is the dust height.

[0113] in It is a weight coefficient used to convert the relationship between dust volume and dust height into a severity index. According to traffic regulations, road safety standards and environmental quality requirements, a threshold for dust severity is set. If the calculated dust severity Exceeding the threshold , then clean the road surface. Not exceeding the threshold , then cleanup may not be necessary or other precautions can be taken.

[0114] The method provided in this embodiment helps to understand the actual distribution of dust and provide data support for subsequent cleaning work. By calculating the severity of dust, the impact of dust on the environment and traffic can be more intuitively understood. When dust reaches a certain level, timely cleaning can prevent dust from spreading and reduce pollution. When dust does not reach a certain standard, unnecessary cleaning can be avoided to save costs.

[0115] In some embodiments, the dust accumulation condition is determined based on the dust density, dust range, current dust change and dust density change, and is calculated according to the following formula (6): (6) in, Indicates the accumulation index; Indicates the weight of the influence of dust density on the accumulation index; Indicates dust accumulation density; Indicates the weight of the influence of dust accumulation range on the accumulation index; Indicates the dust accumulation range; Indicates the weight of the influence of the change in dust density on the accumulation index; is the change in dust density over a long period of time; Indicates the length of the first preset period of time.

[0116] Specifically, dust density It is usually proportional to the total amount of dust. Therefore, the square of the dust density It can be used to represent the total amount of dust accumulation, assuming that the distribution of dust accumulation is uniform. Is a weight that indicates the influence of dust density on the accumulation index. It represents the area covered by dust on the ground. Since the larger the range, the larger the affected area of ​​dust, the natural logarithm can be used. To reflect the influence of dust accumulation range. Indicates the weight of the dust accumulation range on the accumulation index. Adding 1 here is to avoid the logarithmic function Undefined situation when . Change in dust density Indicates that in a period of time In order to take into account the time factor, use To express the rate of change per unit time. Indicates the weight of the impact of this change on the accumulation index. Again, adding 1 is to avoid the situation where the denominator is zero.

[0117] Through the method provided in this embodiment, the formula provides a comprehensive indicator for evaluating the dust accumulation on the transportation roads in the mining area, including the total amount of dust accumulation, distribution range and change trend. By adjusting the coefficient, the influence of dust density, dust accumulation range and dust density change can be weighted according to actual conditions and needs. The introduction of the time factor enables the formula to reflect the changes in dust accumulation over time, which helps to dynamically monitor and manage dust problems.

[0118] Figure 3 A schematic diagram of a dust detection system for a mining area transportation road provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the mining area transportation road pavement dust detection system 300 of this embodiment includes: an information acquisition module 301, a deposition analysis module 302, and a prediction module 303.

[0119] The information acquisition module 301 is used to acquire the real-time point cloud data collected by the laser radar and the vehicle information of the mining area transport vehicle, analyze the point cloud data, and determine the dust accumulation area information; The accumulation analysis module 302 is used to retrieve the dust accumulation data after the last cleaning; and determine the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information; The prediction module 303 is used to predict the amount of dust according to the vehicle information and the dust accumulation situation; and determine whether to perform road cleaning according to the amount of dust.

[0120] Optionally, when the information acquisition module 301 analyzes the point cloud data to determine the dust accumulation area information, it is used to: Obtaining mining area transportation information; analyzing the mining area transportation information to determine the type of dust accumulation; Acquire meteorological data within a first preset time period; analyze the meteorological data to determine the meteorological impact of different meteorological conditions within the preset time period on the dust accumulation type; Determine the type of transport vehicle according to the vehicle information; Determining the dust accumulation form according to the type of transport vehicle; Analyze the dust accumulation morphology and determine the data type mapped to the point cloud; Based on the data type and according to the meteorological influence, the point cloud data is analyzed to determine the dust accumulation area information.

[0121] Optionally, when the accumulation analysis module 302 determines the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information, it is used to: Determining the dust accumulation density at the current moment according to the dust accumulation form; Determining a dust accumulation range according to the dust accumulation area information; Determining a current dust accumulation change amount according to the dust accumulation data; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change.

[0122] Optionally, when the accumulation analysis module 302 determines the dust accumulation condition according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change, it is used to: Acquire road traffic data for a second preset time period; Analyze the road traffic data to determine the type of passing vehicles; Determining the total weight of the vehicle based on the type of vehicle passing through; Predicting a change in dust density based on the vehicle's total load weight; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, the current dust accumulation change and the dust accumulation density change.

[0123] Optionally, when the information acquisition module 301 analyzes the point cloud data based on the data type and the meteorological influence to determine the dust accumulation area information, it is used to: Analyze the meteorological impact and determine the first point cloud shape after the first meteorological change; Analyze the influence of other different weather conditions on the first point cloud shape to determine the final point cloud shape; Analyzing the point cloud data according to the final point cloud form to determine the dust point cloud features; Determining dust accumulation area information according to the dust accumulation point cloud features; When determining the dust density at the current moment according to the dust accumulation form, it is used to: The dust accumulation density at the current moment is determined according to the final point cloud shape.

[0124] Optionally, when predicting the amount of dust according to the vehicle information and the dust accumulation condition, the prediction module 303 is used to: Determine the vehicle type and vehicle load according to the vehicle information; Obtaining historical traffic records, and determining the average speed of each type of vehicle passing through the mining area transportation road according to the historical traffic records; Analyzing the final point cloud morphology to determine the amount of particle dust; Obtain basic information of the mining area transportation road and determine the road width; Determining the dust range according to the road width and the dust accumulation area information; The amount of dust is predicted according to the amount of particulate dust, the range of dust generation, the average speed and the vehicle load.

[0125] Optionally, when the prediction module 303 determines whether to perform road cleaning according to the dust amount, it is used to: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the degree of visual interference according to the dust volume and the dust height; Whether to perform road cleaning is determined according to the degree of visual interference.

[0126] Optionally, when the prediction module determines whether to perform road cleaning according to the dust amount, it is used to: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the severity of dust emission according to the dust emission volume and the dust emission height; Determine whether to clean the road surface based on the severity of the dust.

[0127] Optionally, the accumulation analysis module 302 determines the dust accumulation situation according to the dust accumulation density, the dust accumulation range, the current dust accumulation change and the dust accumulation density change, and calculates according to the following formula: ; in, Indicates the accumulation index; Indicates the influence weight of the dust accumulation density on the accumulation condition index; Indicates the dust accumulation density; Indicates the influence weight of the dust accumulation range on the accumulation condition index; Indicates the dust accumulation range; Indicates the influence weight of the dust accumulation density change on the accumulation condition index; is the change in dust density over a long period of time; Indicates the length of the first preset period of time.

[0128] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A method for detecting dust on a mining area transport road, characterized in that: The method for detecting dust on a mining area transport road is applied to a dust detection device, the dust detection device includes a server and a laser radar, the method is applied to the server, and the method includes: Acquire the real-time point cloud data collected by the laser radar and the vehicle information of the mining area transport vehicle, analyze the point cloud data, and determine the dust accumulation area information; Retrieving dust accumulation data after the last cleaning; determining the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information; The amount of dust is predicted based on the vehicle information and the dust accumulation situation; and whether to perform road cleaning is determined based on the amount of dust.

2. The method according to claim 1, characterized in that The step of analyzing the point cloud data to determine dust accumulation area information includes: Obtaining mining area transportation information; analyzing the mining area transportation information to determine the type of dust accumulation; Acquire meteorological data within a first preset time period; analyze the meteorological data to determine the meteorological impact of different meteorological conditions within the preset time period on the dust accumulation type; Determine the type of transport vehicle according to the vehicle information; Determining the dust accumulation form according to the type of transport vehicle; Analyze the dust accumulation morphology and determine the data type mapped to the point cloud; Based on the data type and according to the meteorological influence, the point cloud data is analyzed to determine the dust accumulation area information.

3. The method according to claim 2, characterized in that The determining of the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information includes: Determining the dust accumulation density at the current moment according to the dust accumulation form; Determining a dust accumulation range according to the dust accumulation area information; Determining a current dust accumulation change amount according to the dust accumulation data; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change.

4. The method according to claim 2, characterized in that: The determining of the dust accumulation condition according to the dust accumulation density, the dust accumulation range, and the current dust accumulation change amount includes: Acquire road traffic data for a second preset time period; Analyze the road traffic data to determine the type of passing vehicles; Determining the total weight of the vehicle based on the type of vehicle passing through; Predicting a change in dust density based on the vehicle's total load weight; The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, the current dust accumulation change and the dust accumulation density change.

5. The method according to claim 2, characterized in that: The step of analyzing the point cloud data based on the data type and according to the meteorological influence to determine the dust accumulation area information includes: Analyze the meteorological impact and determine the first point cloud shape after the first meteorological change; Analyze the influence of other different weather conditions on the first point cloud shape to determine the final point cloud shape; Analyzing the point cloud data according to the final point cloud form to determine the dust point cloud features; Determining dust accumulation area information according to the dust accumulation point cloud features; Determining the dust density at the current moment according to the dust accumulation form includes: The dust accumulation density at the current moment is determined according to the final point cloud shape.

6. The method according to claim 5, characterized in that The predicting of dust amount according to the vehicle information and the dust accumulation condition includes: Determine the vehicle type and vehicle load according to the vehicle information; Obtaining historical traffic records, and determining the average speed of each type of vehicle passing through the mining area transportation road according to the historical traffic records; Analyzing the final point cloud morphology to determine the amount of particle dust; Obtain basic information of the mining area transportation road and determine the road width; Determining the dust range according to the road width and the dust accumulation area information; The amount of dust is predicted according to the amount of particulate dust, the range of dust generation, the average speed and the vehicle load.

7. The method according to claim 6, characterized in that The step of determining whether to perform road cleaning according to the dust amount includes: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the degree of visual interference according to the dust volume and the dust height; Whether to perform road cleaning is determined according to the degree of visual interference.

8. The method according to claim 6, characterized in that The step of determining whether to perform road cleaning according to the dust amount includes: Determining dust height and dust volume according to the dust amount and the vehicle load; Determining the severity of dust emission according to the dust emission volume and the dust emission height; Determine whether to clean the road surface based on the severity of the dust.

9. The method according to claim 5, characterized in that The dust accumulation condition is determined according to the dust accumulation density, the dust accumulation range, the current dust accumulation change and the dust accumulation density change, and is calculated according to the following formula: ； in, Indicates the accumulation index; Indicates the influence weight of the dust accumulation density on the accumulation condition index; Indicates the dust accumulation density; Indicates the influence weight of the dust accumulation range on the accumulation condition index; Indicates the dust accumulation range; Indicates the influence weight of the dust accumulation density change on the accumulation condition index; is the change in dust density over a long period of time; Indicates the length of the first preset period of time.

10. A dust detection system for mining area transportation roads, characterized in that: include: An information acquisition module is used to acquire real-time point cloud data collected by the laser radar and vehicle information of the mining area transport vehicle, analyze the point cloud data, and determine the dust accumulation area information; The accumulation analysis module is used to retrieve the dust accumulation data after the last cleaning; and determine the dust accumulation situation at the current moment according to the dust accumulation data and the dust accumulation area information; A prediction module, used for predicting the amount of dust according to the vehicle information and the dust accumulation condition; And according to the dust amount, it is determined whether to clean the road surface.

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