Spraying arm unfolding method and system of intelligent dust suppression robot shared by rails

Abstract

The invention relates to the technical field of robot arm control, and discloses a spraying arm unfolding method and system of an intelligent dust suppression robot shared by a track. The method comprises the following steps: analyzing the basic information of a stack to obtain the characteristic value of the basic information of the stack, analyzing the state of the stack, judging whether a dust suppression robot corresponding to the stack needs to start running or not, analyzing the environment where the dust suppression robot needing to start running is located, and judging whether the dust suppression robot can start running or not. According to the method, the rail position state of the dust suppression robot capable of starting to operate is analyzed, a dust suppression robot advancing scheme is obtained through comparison, a dust suppression robot spraying arm unfolding scheme is obtained through comparison, the problems that a traditional dust suppression mode is serious in resource waste and insufficient in scene dynamic adaptive capacity are solved, the operation efficiency is improved, and the method is suitable for popularization and application. And the optimal spraying arm unfolding scheme is obtained through comparison, so that the uniformity and effective coverage of water spraying can be ensured, the flying dust is further reduced, and the waste of water resources is reduced.

Description

Technical Field

[0001] The present invention relates to the field of program-controlled manipulators, and in particular to a method and system for deploying a spraying arm of a track-sharing intelligent dust suppression robot. Background Art

[0002] The prevention and control of dust in bulk cargo yards at terminals is the key task of environmental governance in the areas around terminals. Dust is a typical manifestation of air pollution. The main reason for its formation is that wind, human and other factors drive the dust on the ground into the atmosphere. It is a total suspended particulate matter pollution caused by an open pollution source. The regional dust phenomenon is serious. Dust in open-air yards not only causes serious pollution to the environment, but also threatens the health of employees and residents working nearby. With the improvement of people's environmental awareness and the concept of energy conservation and consumption reduction, dust control has increasingly attracted the attention of business managers and has become a problem that must be solved. Timely spraying, effective coverage, water saving and emission reduction are the main problems that dust suppression in yards currently solves. The existing commonly used prevention and control measures have their own advantages and disadvantages in terms of economy, environmental protection and applicability. With the rapid development of science and technology, technologies such as the Internet of Things and artificial intelligence have been widely used, providing new solutions for more effective and scientific solutions to the dust problem in bulk cargo yards. The intelligent and automated design of dust suppression equipment can improve work efficiency, reduce labor costs and improve operational safety.

[0003] For example, the invention patent with announcement number CN115816467B discloses a robot control method, device, system, storage medium and robot, the robot control method includes: obtaining the target posture position information of the robot, and using the current posture position information of the robot to determine the required movement distance of each arm section; obtaining the required movement speed according to the required running distance and the required movement time; determining the control current of the proportional valve action according to the required movement speed and the cylinder speed current relationship matrix corresponding to each execution cylinder; and controlling the corresponding proportional valve execution action according to the control current. The present invention generates the control current by using the cylinder speed current relationship matrix, discretizes the continuous current signal that originally controls the operation of the proportional valve, and realizes the control of the execution cylinder movement with a fixed control current, which can minimize the hysteresis effect of the electromagnetic coil of the proportional valve, effectively maintain the accuracy of the robot control, and does not need to rely on imported high-performance digital signal control multi-way valves.

[0004] At present, there are still some shortcomings in the research on the deployment method of the spray arm of the intelligent dust suppression robot. Specifically, when using traditional dust suppression methods, uneven watering often occurs, the coverage area is small, the labor cost is high, and there is serious waste of resources. The maintenance workload of the spray gun station is large in the later stage, and the dynamic adaptability of the scene is insufficient, which makes it impossible to effectively suppress the dust in some areas, and then the dust problem continues to exist or worsen. Uneven watering may cause mud or slippery ground to form in places with too much water, while dust in places with insufficient water is still suspended in the air, causing dust accumulation and secondary dusting. Manual continuous monitoring and adjustment of the dust suppression effect are required, and true intelligent control cannot be achieved, resulting in insufficient automation and reducing the overall efficiency of the system. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a track-shared intelligent dust suppression robot spray arm deployment method and system, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] A first aspect of the present invention provides a method for deploying the spray arm of an intelligent dust suppression robot that shares a track, comprising the following steps: analyzing basic information of a stack to obtain characteristic values ​​of the basic information of the stack; analyzing the state of the stack to determine whether the dust suppression robot corresponding to the stack needs to start running; analyzing the environment in which the dust suppression robot that needs to start running is located to determine whether the dust suppression robot can start running; analyzing the track position state of the dust suppression robot that can start running to obtain a travel plan for the dust suppression robot by comparison; and obtaining a deployment plan for the spray arm of the dust suppression robot by comparison based on the characteristic values ​​of the basic information of the stack and the travel plan of the dust suppression robot.

[0008] Optionally, the basic information of the stack is analyzed, and the specific analysis process is: obtaining a basic information data set of the stack, the basic information data set of the stack specifically includes the maximum height of the stack, the area occupied by the stack, and the total volume of the stack; based on the obtained basic information data set of the stack, a comprehensive analysis is performed to obtain a basic information characteristic value of the stack, and the basic information characteristic value of the stack is used as an analysis basis for comparing to obtain a deployment plan of the spray arm of the dust suppression robot.

[0009] Optionally, it is determined whether the dust suppression robot corresponding to the stack needs to start running. The specific analysis process is: obtain a stacking status data set, and based on the obtained stacking status data set, comprehensively analyze to obtain a stacking status evaluation value, and use the stacking status evaluation value as an analysis basis for determining whether the dust suppression robot corresponding to the stack needs to start running; compare the stacking status evaluation value with the stacking status reference evaluation value stored in the database; if the stacking status evaluation value is higher than or equal to the stacking status reference evaluation value, the dust suppression robot corresponding to the stacking status evaluation value needs to start running; if the stacking status evaluation value is lower than the stacking status reference evaluation value, the dust suppression robot corresponding to the stacking status evaluation value does not need to start running.

[0010] Optionally, the stacking status data set specifically includes stacking humidity, dust concentration in the stacking area, and dust diffusion speed in the stacking area.

[0011] Optionally, to determine whether the dust suppression robot can start running, the specific analysis process is: obtain the dust suppression robot's environment data set, the dust suppression robot's environment data set specifically includes the dust suppression robot's environment wind speed, the dust suppression robot's environment precipitation, and the absolute value of the difference between the dust suppression robot's environment temperature and the reference temperature; based on the obtained dust suppression robot environment data set, a comprehensive analysis is performed to obtain an evaluation value of the dust suppression robot's environment, and the evaluation value of the dust suppression robot's environment is used as an analysis basis for determining whether the dust suppression robot can start running; the dust suppression robot's environment evaluation value is compared with the dust suppression robot's environment reference evaluation value stored in the database; if the dust suppression robot's environment evaluation value is higher than or equal to the dust suppression robot's environment reference evaluation value, then the dust suppression robot corresponding to the dust suppression robot's environment evaluation value can start running; if the dust suppression robot's environment evaluation value is lower than the dust suppression robot's environment reference evaluation value, then the dust suppression robot corresponding to the dust suppression robot's environment evaluation value cannot start running.

[0012] Optionally, the dust suppression robot's environment assessment value, the specific analysis process is:

[0013]

[0014] Wherein, ω is the environmental assessment value of the dust suppression robot, fs is the wind speed of the dust suppression robot, js is the precipitation of the dust suppression robot, wc is the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature, σ1 is the compensation factor of the set wind speed of the dust suppression robot, σ2 is the compensation factor of the set precipitation of the dust suppression robot, σ3 is the compensation factor of the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature, and e is a natural constant.

[0015] Optionally, a travel plan of the dust suppression robot is obtained by comparison, and the specific analysis process is: obtain the dust suppression robot track position state data set, the dust suppression robot track position state data set specifically includes the dust suppression robot track running speed, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stack; based on the obtained dust suppression robot track position state data set, a comprehensive analysis is performed to obtain the dust suppression robot track position state characteristic value, and the dust suppression robot track position state characteristic value is used as the analysis basis for comparing the dust suppression robot travel plan; compare the dust suppression robot track position state characteristic value with the dust suppression robot travel plan corresponding to each dust suppression robot track position state characteristic value stored in the database, and obtain the dust suppression robot travel plan corresponding to the dust suppression robot track position state characteristic value.

[0016] Optionally, the track position state characteristic value of the dust suppression robot, the specific analysis process is:

[0017]

[0018] Wherein, δ is the characteristic value of the track position state of the dust suppression robot, ys is the track running speed of the dust suppression robot, za is the distance between the dust suppression robot and the nearest obstacle in front of the track, mb is the distance between the dust suppression robot and the target stacking, τ1 is the compensation factor of the set track running speed of the dust suppression robot, τ2 is the compensation factor of the set distance between the dust suppression robot and the nearest obstacle in front of the track, and τ3 is the compensation factor of the set distance between the dust suppression robot and the target stacking.

[0019] Optionally, the dust suppression robot spray arm deployment plan is obtained by comparison, and the specific analysis process is: store the basic information characteristic value of the stacking and the dust suppression robot travel plan as a designated label, compare the designated label with the dust suppression robot spray arm deployment plan corresponding to each designated label stored in the database, and obtain the dust suppression robot spray arm deployment plan corresponding to the designated label.

[0020] The second aspect of the present invention provides a track-sharing intelligent dust suppression robot spray arm deployment system, including a basic information characteristic value acquisition module, a need to start operation judgment module, an ability to start operation judgment module, a travel plan comparison module and a spray arm deployment plan comparison module, wherein: the basic information characteristic value acquisition module is used to analyze the basic information of the stack to obtain the basic information characteristic value of the stack; the need to start operation judgment module is used to analyze the stacking state to determine whether the dust suppression robot corresponding to the stack needs to start operation; the ability to start operation judgment module is used to analyze the environment in which the dust suppression robot that needs to start operation is located, and determine whether the dust suppression robot can start operation; the travel plan comparison module is used to analyze the track position state of the dust suppression robot that can start operation, and compare to obtain the travel plan of the dust suppression robot; the spray arm deployment plan comparison module is used to compare and obtain the spray arm deployment plan of the dust suppression robot based on the basic information characteristic value of the stack and the travel plan of the dust suppression robot.

[0021] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0022] (1) The present invention provides a track-sharing intelligent dust suppression robot spray arm deployment method and system, which conducts a detailed analysis of the stacking information, helps to accurately assess the dust risk and the required dust suppression intensity, thereby optimizing the use of dust suppression resources and judging whether the dust suppression robot needs to be started. This can avoid starting the robot unnecessarily, thereby saving energy and extending the service life of the equipment. By analyzing the humidity, wind speed and other parameters of the environment in which the robot is located, it can ensure that the robot operates under appropriate conditions, avoid inefficient or even ineffective operations, and further improve the operating efficiency. Based on the characteristic values ​​of the basic information of the stack and the robot's travel plan, the optimal spray arm deployment plan is compared to ensure the uniformity and effective coverage of watering, further reduce dust and reduce the waste of water resources.

[0023] (2) The present invention analyzes the track position status of the dust suppression robot that can start running, compares it to obtain the travel plan of the dust suppression robot, and analyzes the track position status to determine the robot's optimal travel route, avoid repeated coverage or unnecessary detours, thereby reducing operation time and improving overall efficiency. In the travel plan, the robot's spraying intensity and frequency in different areas can be reasonably arranged to ensure that the dust suppression effect is maximized, especially in areas with high dust concentration. Through real-time monitoring of the track position status, the route can be adjusted in time when encountering obstacles or emergencies to avoid collisions or operation interruptions, thereby improving safety.

[0024] (3) The present invention obtains a deployment plan for the spray arm of the dust suppression robot by comparing the characteristic values ​​of the basic information of the stack and the travel plan of the dust suppression robot. The deployment angle and range of the spray arm can be accurately adjusted to make the dust suppression operation more precise and effectively cover the surface and surrounding areas of the stack, ensuring that dust is effectively controlled. The deployment range of the spray arm can be accurately controlled to spray only the areas that require dust suppression, avoiding watering unnecessary areas, thereby reducing the waste of water resources. The deployment of the spray arm can be accurately matched with the travel path of the robot, ensuring that the spray arm is always in the best position during the movement of the robot, avoiding frequent adjustments and re-deployment, and further reducing the operation time. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0026] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.

[0027] Figure 2 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] like Figure 1 As shown, the first aspect of the present invention provides a method for deploying a spraying arm of a track-sharing intelligent dust suppression robot, comprising: analyzing basic information of the stack to obtain characteristic values ​​of the basic information of the stack.

[0030] Specifically, the basic information of the stack is analyzed, and the specific analysis process is: obtaining a basic information data set of the stack, the basic information data set of the stack specifically includes the maximum height of the stack, the area occupied by the stack, and the total volume of the stack; based on the obtained basic information data set of the stack, a comprehensive analysis is performed to obtain the basic information characteristic values ​​of the stack, and the basic information characteristic values ​​of the stack are used as the analysis basis for comparing to obtain the deployment plan of the spray arm of the dust suppression robot.

[0031] In a specific embodiment, the maximum height of the stack refers to the vertical distance from the base of the stack to its top, usually in meters or centimeters, and is used to evaluate the vertical space occupancy of the stack. The distance from the bottom to the top of the stack is measured by a laser beam, which is highly accurate and suitable for use in industrial environments. The stack footprint refers to the projected area of ​​the stack on the ground, usually in square meters (m2), reflecting the space occupied by the stack on the horizontal plane. By scanning the bottom contour of the stack, a two-dimensional projection map of its footprint is generated to obtain the stack footprint. The total volume of the stack refers to the volume of the space occupied by the stack, usually in cubic meters (m3). The volume is the result of a combination of geometric parameters such as the maximum height of the stack and the footprint. By generating a three-dimensional model of the stack by a three-dimensional laser scanner, the total volume of the stack can be directly calculated. The total volume of a regular stack is equal to the maximum height multiplied by the footprint. The maximum height and footprint of the stack are fully utilized to improve storage efficiency. In the case of limited height, reasonable adjustment of the footprint and stacking manpower can improve the overall storage and processing capabilities.

[0032] It should be explained that the above analysis of the maximum height, floor area and total volume of the stack can accurately calculate the specific area that needs to be sprayed. The dust suppression robot can accurately adjust the deployment range of the spray arm according to these characteristic values ​​to ensure that the dust suppression operation can cover the entire stacking area without omissions or excessive coverage. The stacking volume can help determine the total demand for dust suppression, thereby optimizing the spraying volume and frequency. For larger stacks, a larger range and higher intensity spraying can be selected; for smaller stacks, a lighter spraying strategy can be selected to improve the overall dust suppression efficiency and reduce resource waste. The analysis of the stacking area and total volume helps to accurately calculate the amount of water required for dust suppression. According to these characteristic values, the dust suppression robot can reduce unnecessary water resource use and reduce operating costs without affecting the dust suppression effect. Different stacks may have great differences in height, area and volume. By comprehensively analyzing these characteristic values, the dust suppression robot can dynamically adjust the deployment strategy of the spray arm to adapt to various stacking conditions and improve the flexibility and adaptability of dust suppression operations.

[0033] It should be explained that the specific analysis process of the above stacking basic information characteristic value is as follows:

[0034]

[0035] Where α is the basic information characteristic value of the stacking, gd is the maximum height of the stacking, zd is the area occupied by the stacking, tj is the total volume of the stacking, ε1 is the compensation factor of the set maximum height of the stacking, ε2 is the compensation factor of the set area occupied by the stacking, ε3 is the compensation factor of the set total volume of the stacking, and e is a natural constant.

[0036] It should be explained that the above-mentioned characteristic values ​​of basic information of the stack are calculated through the maximum height of the stack, the area occupied by the stack and the total volume of the stack. The maximum height of the stack, the area occupied by the stack and the total volume of the stack are normalized. The maximum height of the stack, the area occupied and the total volume are the three core parameters that describe the physical characteristics of the stack. The characteristic values ​​can fully reflect the actual situation of the stack, such as the ductility in height, the occupied space on the plane and the total volume in three-dimensional space, which helps the dust suppression robot to understand the overall shape and scale of the stack. Through the calculated characteristic values ​​of the stack, the dust suppression robot can select the most appropriate way to deploy the spray arm and the spraying intensity. For high and narrow stacks, the robot can adjust the angle of the spray arm The degree and spraying range can ensure that the water mist can cover the entire stacking surface. For wide and low stacks, the spray arm may need to be deployed horizontally more widely. By pre-calculating the basic information eigenvalues ​​of the stack, the dust suppression robot can make decisions faster and reduce the time of real-time calculation during the operation. It can accelerate the start of dust suppression operations and improve overall operation efficiency. Different stacks may have great differences in height, area and volume. The eigenvalues ​​of the basic information of the stack are obtained by calculating the eigenvalues. The basic information eigenvalues ​​of the stack are used as the analysis basis for comparing the deployment plan of the dust suppression robot's spray arm, so that the dust suppression robot can better adapt to various types of stacks and provide flexible and efficient dust suppression solutions.

[0037] ε1, ε2, ε3 are the compensation factors corresponding to the maximum stacking height, the stacking area, and the total stacking volume preset in the database, which represent the numerical values ​​of the influence of the maximum stacking height, the stacking area, and the total stacking volume on the characteristic values ​​of the basic information of the stacking. When used, the compensation factors corresponding to the maximum stacking height, the stacking area, and the total stacking volume can be directly obtained from the database. The corresponding relationship can be a preset mapping relationship, in which the mapping relationship can be one-to-one or many-to-one. For example, the maximum stacking height and the compensation factor of the maximum stacking height are in the form of For example, the stacking area and the compensation factor of the stacking area form a mapping set, and the real-time stacking area is input into the mapping set to obtain the compensation factor of the stacking area. In this example, the value range is between 0 and 1; for example, the total volume of the stacking and the compensation factor of the total volume of the stacking form a mapping set, and the real-time total volume of the stacking is input into the mapping set to obtain the compensation factor of the total volume of the stacking. In this example, the value range is between 0 and 1.

[0038] Analyze the stacking status to determine whether the dust suppression robot corresponding to the stacking needs to start running.

[0039] Specifically, it is determined whether the dust suppression robot corresponding to the stack needs to start running. The specific analysis process is: obtain a stacking state data set, and based on the obtained stacking state data set, comprehensively analyze to obtain a stacking state evaluation value, and use the stacking state evaluation value as an analysis basis for determining whether the dust suppression robot corresponding to the stack needs to start running; compare the stacking state evaluation value with the stacking state reference evaluation value stored in the database; if the stacking state evaluation value is higher than or equal to the stacking state reference evaluation value, the dust suppression robot corresponding to the stacking state evaluation value needs to start running; if the stacking state evaluation value is lower than the stacking state reference evaluation value, the dust suppression robot corresponding to the stacking state evaluation value does not need to start running.

[0040] It needs to be explained that the above-mentioned comprehensive assessment of the stacking status only starts the dust suppression robot when needed, avoiding unnecessary operation, thereby saving energy and water resources. Accurate judgment makes resource use more efficient, reduces waste, and reduces the number of unnecessary starts. The energy consumption of the dust suppression robot is reduced, thereby reducing the overall operating cost. The dust suppression robot only runs when necessary, reducing the wear and maintenance requirements of mechanical equipment, thereby extending the service life of the equipment and reducing maintenance costs. The analysis process relies on automated status assessment and data comparison, which can reduce human intervention and improve work efficiency. Intelligent judgment can make decisions faster and more accurately, ensuring that dust suppression operations are started at the right time. The data-driven decision-making process reduces the errors that may be caused by human judgment and ensures that dust suppression operations are carried out at the most appropriate time. The stacking status evaluation value can reflect the dynamic changes of the stack in real time, allowing the dust suppression robot to quickly adapt to different environmental conditions and work requirements, enhancing the flexibility of the system.

[0041] Furthermore, the stacking status data set specifically includes stacking humidity, dust concentration in the stacking area, and dust diffusion speed in the stacking area.

[0042] In a specific embodiment, stacking humidity refers to the relative amount of moisture contained in the stacked items, usually expressed in relative humidity (%) or absolute humidity (g / m3), reflecting the moisture level of the stacked materials. When the humidity is high, dust is more likely to condense and the risk of dust is lower; when the humidity is low, the dust in the stack is more likely to be dissipated into the air. Based on the humidity sensor, the dust concentration in the stacking area refers to the mass of dust particles suspended in a unit volume of air, usually expressed in micrograms per cubic meter (g / m3) or milligrams per cubic meter (mg / m3). The higher the dust concentration, the greater the dust content in the air and the more serious the dust pollution. Based on the dust detector, the dust diffusion rate in the stacking area refers to the speed at which dust in the stacking area diffuses in the air, usually expressed in meters per second (m / s), reflecting the speed at which dust particles propagate in the air. It is affected by air flow, the properties of the stacked dust and environmental conditions. Based on the particle tracking velocimeter, the movement speed of dust particles in the air is measured by laser and high-speed photography technology.

[0043] In a specific embodiment, when the humidity of the stack is high, the dust particles on the surface of the stack easily absorb moisture, increasing the cohesion between the particles, making the dust particles heavier and less likely to float in the air, thereby reducing the dust concentration. When the humidity is high, the dust particles are more likely to gather together to form larger particles. These larger particles are not easy to diffuse with the air flow due to gravity, so the diffusion rate is slower. When the dust diffusion rate is faster, the dust particles quickly spread from the stacking area to the surrounding air, which may cause the dust concentration in the local area to temporarily drop, but spread to a wider range of air, which may cause more widespread pollution.

[0044] It should be explained that the above stacking status evaluation value has the following specific analysis process:

[0045]

[0046] Wherein, β is the stacking state evaluation value, ds is the stacking humidity, nd is the dust concentration in the stacking area, ks is the dust diffusion speed in the stacking area, μ1 is the compensation factor for the set stacking humidity, μ2 is the compensation factor for the set dust concentration in the stacking area, and μ3 is the compensation factor for the set dust diffusion speed in the stacking area.

[0047] It needs to be explained that the above-mentioned stacking status assessment value is calculated through stacking humidity, dust concentration in the stacking area and dust diffusion rate in the stacking area. The stacking humidity, dust concentration and dust diffusion rate are normalized. Stacking humidity, dust concentration and dust diffusion rate are important factors affecting stacking dust. The stacking status assessment value can accurately reflect the current dust risk of the stack and avoid the misjudgment that may be caused by relying on a single indicator. These parameters can dynamically reflect changes in the stack and its surrounding environment, such as increased humidity or a sudden increase in dust concentration. The assessment value can therefore be adjusted in time to ensure a quick response when the dust risk increases. The dust suppression robot can avoid unnecessary startup when the dust risk is low, thereby saving energy and resources and reducing unnecessary equipment wear. The stacking status assessment value can predict possible dust risks and start dust suppression operations in advance, thereby preventing potential dust hazards and ensuring a safe working environment.

[0048] μ1, μ2, and μ3 are compensation factors corresponding to the stacking humidity, dust concentration in the stacking area, and dust diffusion speed in the stacking area preset in the database, which represent the numerical values ​​of the influence of the stacking humidity, dust concentration in the stacking area, and dust diffusion speed in the stacking area on the stacking state evaluation value. When used, the compensation factors corresponding to the stacking humidity, dust concentration in the stacking area, and dust diffusion speed in the stacking area can be directly obtained from the database. The corresponding relationship can be a preset mapping relationship, in which the mapping relationship can be one-to-one or many-to-one. For example, the stacking humidity and the compensation factor of the stacking humidity form a mapping set, which will be real-time The stacking humidity is input into a mapping set to obtain a compensation factor for the stacking humidity, and its value range in this example is between 0 and 1; for example, the dust concentration in the stacking area and the compensation factor of the dust concentration in the stacking area form a mapping set, and the real-time dust concentration in the stacking area is input into the mapping set to obtain the compensation factor for the dust concentration in the stacking area, and its value range in this example is between 0 and 1; for example, the dust diffusion speed in the stacking area and the compensation factor of the dust diffusion speed in the stacking area form a mapping set, and the real-time dust diffusion speed in the stacking area is input into the mapping set to obtain the compensation factor for the dust diffusion speed in the stacking area, and its value range in this example is between 0 and 1.

[0049] The environment in which the dust suppression robot that needs to start running is located is analyzed to determine whether the dust suppression robot can start running.

[0050] Specifically, to determine whether the dust suppression robot can start running, the specific analysis process is: obtain the dust suppression robot's environmental data set, the dust suppression robot's environmental data set specifically includes the dust suppression robot's environmental wind speed, the dust suppression robot's environmental precipitation, and the absolute value of the difference between the dust suppression robot's environmental temperature and the reference temperature; based on the obtained dust suppression robot's environmental data set, a comprehensive analysis is performed to obtain an evaluation value of the dust suppression robot's environment, and the evaluation value of the dust suppression robot's environment is used as an analysis basis for determining whether the dust suppression robot can start running; the dust suppression robot's environmental evaluation value is compared with the dust suppression robot's environmental reference evaluation value stored in the database; if the dust suppression robot's environmental evaluation value is higher than or equal to the dust suppression robot's environmental reference evaluation value, then the dust suppression robot corresponding to the dust suppression robot's environmental evaluation value can start running; if the dust suppression robot's environmental evaluation value is lower than the dust suppression robot's environmental reference evaluation value, then the dust suppression robot corresponding to the dust suppression robot's environmental evaluation value cannot start running.

[0051] It needs to be explained that the above-mentioned wind speed refers to the speed of air flow in the environment where the dust suppression robot is located, usually in meters per second (m / s) or kilometers per hour (km / h). The wind speed directly affects the effect of dust suppression operations: excessive wind speed may cause the sprayed water mist to be blown away, reducing the dust suppression effect, based on the anemometer. The precipitation refers to the total amount of precipitation in the environment where the dust suppression robot is located within a certain period of time, usually in millimeters (mm). The precipitation affects the necessity of dust suppression operations: when the precipitation is large, natural precipitation already has a certain dust suppression effect, and additional dust suppression operations may not be required. Based on the rain gauge, the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature refers to the absolute value of the difference between the actual temperature of the environment where the dust suppression robot is located and a preset reference temperature. The temperature difference may affect the dust suppression effect and the efficiency of the robot operation: for example, too high or too low temperature may affect the evaporation rate and diffusion effect of water mist. The temperature is obtained based on the temperature sensor and combined with the reference temperature to calculate the dust suppression robot. The absolute value of the difference between the ambient temperature and the reference temperature. When the wind speed is high, even if the precipitation is high, the distribution of precipitation may be uneven, and the water droplets may be blown away by the wind, resulting in insufficient precipitation in some areas of the ground. Additional dust suppression operations may be required to make up for the lack of natural precipitation. The wind speed will affect the temperature distribution in the environment. A larger wind speed can accelerate the transfer of heat, making the impact of the temperature difference more significant. If the wind speed is high, the evaporation rate of the water mist may be faster, resulting in a decrease in the dust suppression effect. A large amount of precipitation can partially offset the negative impact of the wind speed. Although the wind speed is high, enough precipitation can still effectively suppress dust, which may reduce the necessity of the dust suppression robot to operate. When the temperature difference is small, the impact of wind speed on the dust suppression effect may be small, because the evaporation of water mist is relatively stable, and the effect of dust suppression operation is more ideal. Precipitation can adjust the ambient temperature, especially when the temperature is high. Precipitation will bring a cooling effect and reduce the temperature difference. This cooling effect can improve the efficiency of dust suppression operations because the evaporation rate of water mist is reduced.

[0052] It needs to be explained that the above analysis of environmental conditions will only start the dust suppression robot in a suitable environment and avoid operation under unfavorable conditions to ensure the maximum dust suppression effect. If the environmental assessment value is lower than the reference value, the dust suppression robot will not start, avoiding inefficient or ineffective dust suppression operations when the wind speed is too high, the temperature difference is too large or the precipitation is too high. Running the dust suppression robot under unsuitable environmental conditions may lead to waste of water resources, electricity, etc. These wastes can be avoided through accurate judgment, thereby reducing operating costs. Factors such as environmental wind speed, precipitation and temperature difference have a significant impact on the dust suppression effect. In an unfavorable environment (such as excessive wind speed or excessive precipitation), the dust suppression effect may be greatly reduced. By comprehensively analyzing the environmental conditions, ensure that the robot is started under the most favorable conditions to ensure the optimization of the dust suppression effect, allow the dust suppression robot to make dynamic adjustments based on real-time environmental data, adapt to changing environmental conditions, and ensure that it always operates under optimal conditions.

[0053] Furthermore, the environmental assessment value of the dust suppression robot is analyzed in the following specific process:

[0054]

[0055] Wherein, ω is the environmental assessment value of the dust suppression robot, fs is the wind speed of the dust suppression robot, js is the precipitation of the dust suppression robot, wc is the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature, σ1 is the compensation factor of the set wind speed of the dust suppression robot, σ2 is the compensation factor of the set precipitation of the dust suppression robot, σ3 is the compensation factor of the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature, and e is a natural constant.

[0056] It should be explained that the environmental assessment value of the above-mentioned dust suppression robot is calculated by the absolute value of the difference between the wind speed of the environment in which the dust suppression robot is located, the precipitation of the environment in which the dust suppression robot is located, and the temperature of the environment in which the dust suppression robot is located and the reference temperature. The wind speed of the environment in which the dust suppression robot is located, the precipitation of the environment in which the dust suppression robot is located, and the absolute value of the difference between the temperature of the environment in which the dust suppression robot is located and the reference temperature are normalized to calculate the environmental assessment value. The dust suppression robot can avoid starting when the environmental conditions are not conducive to effective dust suppression, save resources, and reduce unnecessary equipment wear. In the case of excessive wind speed or excessive precipitation Under these adverse conditions, dust suppression operations may result in a waste of water resources and energy. Dust suppression operations can be avoided to maximize resource utilization efficiency. Environmental conditions such as wind speed, precipitation and temperature difference may change at any time. By calculating and updating the environmental assessment values, the dust suppression robot can quickly adapt to environmental changes and adjust its operating strategy to ensure that the dust suppression effect and operating efficiency are not negatively affected by environmental changes. The impact of wind speed, precipitation and temperature difference on dust suppression operations is evaluated. The dust suppression robot can avoid operating under extreme or dangerous environmental conditions and reduce the risk of equipment failure and operational accidents.

[0057] σ1, σ2, and σ3 are compensation factors corresponding to the absolute value of the difference between the wind speed of the environment in which the dust suppression robot is located, the precipitation of the environment in which the dust suppression robot is located, and the temperature of the environment in which the dust suppression robot is located and the reference temperature, which are preset in the database. They represent the numerical value of the influence of the wind speed of the environment in which the dust suppression robot is located, the precipitation of the environment in which the dust suppression robot is located, and the absolute value of the difference between the temperature of the environment in which the dust suppression robot is located and the reference temperature on the environmental assessment value of the dust suppression robot. When used, the compensation factors corresponding to the absolute value of the difference between the wind speed of the environment in which the dust suppression robot is located, the precipitation of the environment in which the dust suppression robot is located, and the temperature of the environment in which the dust suppression robot is located and the reference temperature can be directly obtained from the database. The corresponding relationship can be a preset mapping relationship, in which the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. For example, the wind speed of the environment in which the dust suppression robot is located and the compensation factor of the wind speed of the environment in which the dust suppression robot is located form a mapping Set, the real-time wind speed of the dust suppression robot's environment is input into the mapping set to obtain the compensation factor of the wind speed of the dust suppression robot's environment, and its value range in this example is between 0 and 1; for example, the precipitation of the dust suppression robot's environment and the compensation factor of the precipitation of the dust suppression robot's environment form a mapping set, and the real-time precipitation of the dust suppression robot's environment is input into the mapping set to obtain the compensation factor of the precipitation of the dust suppression robot's environment, and its value range in this example is between 0 and 1; for example, the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature and the compensation factor of the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature form a mapping set, and the absolute value of the difference between the ambient temperature of the real-time dust suppression robot and the reference temperature is input into the mapping set to obtain the compensation factor of the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature, and its value range in this example is between 0 and 1.

[0058] The track position status of the dust suppression robot that can start running is analyzed and compared to obtain the travel plan of the dust suppression robot.

[0059] Specifically, the traveling plan of the dust suppression robot is obtained by comparison, and the specific analysis process is: obtain the dust suppression robot track position state data set, the dust suppression robot track position state data set specifically includes the dust suppression robot track running speed, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stack; based on the obtained dust suppression robot track position state data set, a comprehensive analysis is performed to obtain the track position state characteristic value of the dust suppression robot, and the track position state characteristic value of the dust suppression robot is used as the analysis basis for comparing the traveling plan of the dust suppression robot; compare the track position state characteristic value of the dust suppression robot with the dust suppression robot traveling plan corresponding to each dust suppression robot track position state characteristic value stored in the database, and obtain the dust suppression robot traveling plan corresponding to the track position state characteristic value of the dust suppression robot.

[0060] It should be explained that the above-mentioned dust suppression robot track running speed refers to the speed of the robot on the track, usually measured in meters per second (m / s) or kilometers per hour (km / h). The speed directly affects the robot's operating efficiency and dust suppression effect: too fast speed may lead to uneven spraying, while too slow speed will prolong the operation time. Dust suppression robots are usually equipped with built-in speed sensors, which measure the movement of the robot on the track to obtain its operating speed in real time. The distance between the dust suppression robot and the nearest obstacle in front of the track refers to the distance between the dust suppression robot and the nearest obstacle in front of it when it is traveling on the track, usually measured in meters (m) or centimeters (cm). It determines whether the robot needs to slow down, stop or detour to avoid collision. LiDAR can scan the environment in front of the robot in real time and accurately measure the distance to the obstacle. It is a commonly used detection technology at present. The distance between the dust suppression robot and the target stack refers to the distance between the current position of the dust suppression robot and its target stack, usually measured in meters (m) or centimeters (cm). cm) is used for navigation and positioning to ensure that the robot can accurately reach the designated stacking position for dust suppression operations. When the robot approaches the target stack, a laser rangefinder can be used to measure the precise distance between the robot and the stack to ensure that the robot accurately stops at the target position. When the robot runs at a faster speed, the safe distance from the obstacle in front needs to be increased accordingly to ensure that the robot has enough time and distance to slow down or stop to avoid collision. As the running speed increases, the distance to the nearest obstacle in front needs to increase. When the robot approaches the target stack, in order to ensure that it accurately reaches the target position and performs effective dust suppression operations, it is usually necessary to slow down. A slower speed can improve positioning accuracy and avoid deviation or inaccurate stopping caused by approaching too quickly. There may be multiple dust suppression robots on a track. The dust suppression robot may encounter obstacles in the process of moving towards the target stack. When the distance to the obstacle in front is short, the robot may need to adjust its route or even change the way it approaches the target stack to avoid collision.

[0061] It needs to be explained that the above-mentioned monitoring of the distance between the dust suppression robot and the nearest obstacle in front of the track allows the system to adjust the travel route or speed in time to avoid collisions and shutdowns, ensuring that the robot can perform dust suppression tasks smoothly and continuously. By monitoring the distance between the dust suppression robot and the obstacle in front and incorporating it into the comparison and analysis of the travel plan, the collision between the robot and the obstacle can be effectively avoided, thereby protecting the safety of the equipment and the working environment. By monitoring and analyzing the distance between the robot and the target stack, it can be ensured that the robot arrives at the specified position accurately, avoiding unsatisfactory dust suppression effects due to position deviations. By analyzing and comparing the characteristic values ​​of the track position state, the system can automatically generate the best travel plan, reduce the need for manual intervention, and improve the intelligence and automation level of operations. The track environment may change at any time, such as new obstacles or emergencies. By monitoring and analyzing the track position state, the system can dynamically adjust the travel plan to ensure the robot's flexible response capabilities in complex environments.

[0062] It needs to be explained that the above-mentioned analysis of the track position status of the dust suppression robot that can start operation is carried out, and the travel plan of the dust suppression robot is obtained by comparison. By analyzing the track position status, the optimal travel route of the robot can be determined to avoid repeated coverage or unnecessary detours, thereby reducing operation time and improving overall efficiency. In the travel plan, the spraying intensity and frequency of the robot in different areas can be reasonably arranged to ensure the maximum dust suppression effect, especially in areas with high dust concentration. Through real-time monitoring of the track position status, the route can be adjusted in time when encountering obstacles or emergencies, avoiding collisions or operation interruptions, and improving safety.

[0063] Furthermore, the specific analysis process of the track position state characteristic value of the dust suppression robot is as follows:

[0064]

[0065] Wherein, δ is the characteristic value of the track position state of the dust suppression robot, ys is the track running speed of the dust suppression robot, za is the distance between the dust suppression robot and the nearest obstacle in front of the track, mb is the distance between the dust suppression robot and the target stacking, τ1 is the compensation factor of the set track running speed of the dust suppression robot, τ2 is the compensation factor of the set distance between the dust suppression robot and the nearest obstacle in front of the track, and τ3 is the compensation factor of the set distance between the dust suppression robot and the target stacking.

[0066] It needs to be explained that the above-mentioned dust suppression robot track position state characteristic value is calculated through the track running speed of the dust suppression robot, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stack. The track running speed of the dust suppression robot, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stack are normalized to calculate the track position state characteristic value. The dust suppression robot can select the optimal travel path according to the real-time status to avoid unnecessary detours and pauses, thereby improving operation efficiency. The characteristic value takes into account the distance between the dust suppression robot and the nearest obstacle in front of the track. By adjusting the operating speed and path in real time, collisions with obstacles are avoided to ensure the safety of operations. Through reasonable speed and path planning, equipment wear can be reduced, equipment service life can be extended, and maintenance costs can be reduced. The calculation of the characteristic value enables the robot to accurately judge the distance to the target stack, ensure that it stops at the optimal position and performs dust suppression operations, and improve the accuracy and effectiveness of operations.

[0067] τ1, τ2, τ3 are the compensation factors corresponding to the track running speed of the dust suppression robot, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stacking preset in the database, which represent the numerical value of the influence of the track running speed of the dust suppression robot, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stacking on the track position state characteristic value of the dust suppression robot. When used, the compensation factors corresponding to the track running speed of the dust suppression robot, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stacking can be directly obtained from the database. The corresponding relationship can be a preset mapping relationship, in which the mapping relationship can be one-to-one or many-to-one. For example, the compensation factor of the track running speed of the dust suppression robot and the track running speed of the dust suppression robot A mapping set is formed, and the real-time dust suppression robot track running speed is input into the mapping set to obtain the compensation factor of the dust suppression robot track running speed, and its value range in this example is between 0 and 1; for example, the distance between the dust suppression robot and the nearest obstacle in front of the track and the compensation factor of the distance between the dust suppression robot and the nearest obstacle in front of the track form a mapping set, and the real-time dust suppression robot and the nearest obstacle in front of the track are input into the mapping set to obtain the compensation factor of the distance between the dust suppression robot and the nearest obstacle in front of the track, and its value range in this example is between 0 and 1; for example, the distance between the dust suppression robot and the target stacking and the compensation factor of the distance between the dust suppression robot and the target stacking form a mapping set, and the real-time dust suppression robot and the target stacking distance are input into the mapping set to obtain the compensation factor of the distance between the dust suppression robot and the target stacking, and its value range in this example is between 0 and 1.

[0068] Based on the eigenvalues ​​of the basic information of the stack and the travel plan of the dust suppression robot, the deployment plan of the spraying arm of the dust suppression robot is obtained by comparison.

[0069] Specifically, the deployment plan of the dust suppression robot's spray arm is obtained by comparison. The specific analysis process is: the characteristic values ​​of the basic information of the stacking and the travel plan of the dust suppression robot are stored as designated labels, and the designated labels are compared with the deployment plans of the dust suppression robot's spray arms corresponding to the designated labels stored in the database to obtain the deployment plan of the dust suppression robot's spray arm corresponding to the designated labels.

[0070] In a specific embodiment, after the stacking characteristics and travel plans are stored as labels, it can ensure that the dust suppression robot adopts the most suitable spray arm deployment plan in different working environments. By comparing with the existing plans in the database, the plan that best matches the current working conditions can be quickly found, thereby improving the accuracy and effectiveness of the operation. An accurate spray arm deployment plan can avoid excessive or insufficient spraying, ensuring that the waste of water resources and the increase in energy consumption are reduced while the dust suppression effect meets the standards. Label comparison selects the optimal plan, which can achieve efficient use of resources and can quickly generate a spray arm deployment plan that meets the current environmental conditions, reducing manual debugging and adjustment time and speeding up the startup speed of dust suppression operations. The label-based comparison method enables the dust suppression robot to automatically select the spray arm deployment plan that best suits the current conditions, reducing manual intervention and improving the intelligence level of the system. Selecting the best spray arm deployment plan can ensure that the dust suppression operation fully covers the stack, avoids the problem of uneven watering, and improves the overall dust suppression effect.

[0071] It needs to be explained that the above-mentioned dust suppression robot spray arm deployment plan is obtained by comparing the characteristic values ​​of the basic information of the stack and the travel plan of the dust suppression robot, which can accurately adjust the deployment angle and range of the spray arm, making the dust suppression operation more precise, effectively covering the surface and surrounding areas of the stack, ensuring that dust is effectively controlled, and accurately controlling the deployment range of the spray arm. It can spray only the areas that require dust suppression, avoiding watering unnecessary areas, thereby reducing the waste of water resources. The deployment of the spray arm can be accurately matched with the robot's travel path, ensuring that the spray arm is always in the best position during the movement of the robot, avoiding frequent adjustments and re-deployment, and further reducing the operation time.

[0072] It needs to be explained that there are multiple piles to be processed in the above scenario, and each pile in the scene corresponds to a dust suppression robot.

[0073] like Figure 2 As shown, the second aspect of the present invention provides a track-shared intelligent dust suppression robot spray arm deployment system, including a basic information characteristic value acquisition module, a need to start operation judgment module, an ability to start operation judgment module, a travel plan comparison module and a spray arm deployment plan comparison module.

[0074] The basic information characteristic value acquisition module is used to analyze the basic information of the stacking to obtain the characteristic value of the basic information of the stacking.

[0075] The module for judging whether to start running is used to analyze the stacking status and judge whether the dust suppression robot corresponding to the stacking needs to start running.

[0076] The operation judgment module can be started, which is used to analyze the environment in which the dust suppression robot that needs to start running is located, and judge whether the dust suppression robot can start running.

[0077] The travel plan comparison module is used to analyze the track position status of the dust suppression robot that can start running and compare to obtain the travel plan of the dust suppression robot.

[0078] The spray arm deployment plan comparison module is used to compare the spray arm deployment plan of the dust suppression robot based on the characteristic values ​​of the basic information of the stacking and the travel plan of the dust suppression robot.

[0079] It needs to be explained that the above-mentioned method and system for deploying the spray arm of an intelligent dust suppression robot that shares a track are provided, and a detailed analysis of the stacking information is carried out, which is helpful to accurately assess the dust risk and the required dust suppression intensity, thereby optimizing the use of dust suppression resources and judging whether the dust suppression robot needs to be started. This can avoid starting the robot unnecessarily, thereby saving energy and extending the service life of the equipment. By analyzing parameters such as the humidity and wind speed of the environment in which it is located, it can be ensured that the robot operates under suitable conditions, avoiding inefficient or even ineffective operations, and further improving operating efficiency. Based on the characteristic values ​​of the basic information of the stack and the robot's travel plan, the best spray arm deployment plan is compared, which can ensure the uniformity and effective coverage of watering, further reduce dust and reduce the waste of water resources.

[0080] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for deploying a spraying arm of a track-sharing intelligent dust suppression robot, characterized in that: The following steps are involved: Analyze the basic information of the stacking to obtain the characteristic value of the basic information of the stacking; Analyze the stacking status to determine whether the dust suppression robot corresponding to the stacking needs to start running; Analyze the environment where the dust suppression robot that needs to start running is located to determine whether the dust suppression robot can start running; Analyze the track position status of the dust suppression robot that can start running, and compare to get the travel plan of the dust suppression robot; Based on the eigenvalues ​​of the basic information of the stack and the travel plan of the dust suppression robot, the deployment plan of the spraying arm of the dust suppression robot is obtained by comparison.

2. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 1 is characterized in that: The basic information of stacking is analyzed, and the specific analysis process is as follows: Obtaining a basic stacking information data set, wherein the basic stacking information data set specifically includes a maximum stacking height, a stacking area, and a stacking total volume; Based on the acquired basic information data set of stacking, the basic information eigenvalues ​​of stacking are obtained through comprehensive analysis. The basic information eigenvalues ​​of stacking are used as the analysis basis for comparing the deployment plan of the spraying arm of the dust suppression robot.

3. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 1 is characterized in that: The specific analysis process of judging whether the dust suppression robot corresponding to the stack needs to start running is as follows: A stacking state data set is obtained, and a stacking state evaluation value is obtained through comprehensive analysis based on the obtained stacking state data set. The stacking state evaluation value is used as an analysis basis for determining whether the dust suppression robot corresponding to the stacking needs to start running; comparing the stacking state evaluation value with a stacking state reference evaluation value stored in a database; If the stacking state evaluation value is higher than or equal to the stacking state reference evaluation value, the dust suppression robot corresponding to the stacking state evaluation value needs to start running; If the stacking state evaluation value is lower than the stacking state reference evaluation value, the dust suppression robot corresponding to the stacking state evaluation value does not need to start running.

4. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 3 is characterized in that: The stacking status data set specifically includes stacking humidity, dust concentration in the stacking area, and dust diffusion speed in the stacking area.

5. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 1 is characterized in that: The specific analysis process of judging whether the dust suppression robot can start running is as follows: Obtaining a data set of the environment in which the dust suppression robot is located, the data set of the environment in which the dust suppression robot is located specifically includes the wind speed in the environment in which the dust suppression robot is located, the precipitation in the environment in which the dust suppression robot is located, and the absolute value of the difference between the temperature in which the dust suppression robot is located and the reference temperature; Based on the acquired data set of the environment in which the dust suppression robot is located, a comprehensive analysis is performed to obtain an evaluation value of the environment in which the dust suppression robot is located. The evaluation value of the environment in which the dust suppression robot is located is used as an analysis basis for judging whether the dust suppression robot can start operating. Compare the evaluation value of the environment in which the dust suppression robot is located with the reference evaluation value of the environment in which the dust suppression robot is located stored in the database; If the dust suppression robot's environment assessment value is higher than or equal to the dust suppression robot's environment reference assessment value, the dust suppression robot corresponding to the dust suppression robot's environment assessment value may start running; If the assessment value of the environment in which the dust suppression robot is located is lower than the reference assessment value of the environment in which the dust suppression robot is located, the dust suppression robot corresponding to the assessment value of the environment in which the dust suppression robot is located cannot start running.

6. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 5 is characterized in that: The specific analysis process of the environmental assessment value of the dust suppression robot is as follows: Wherein, ω is the environmental assessment value of the dust suppression robot, fs is the wind speed of the dust suppression robot, js is the precipitation of the dust suppression robot, wc is the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature, σ1 is the compensation factor of the set wind speed of the dust suppression robot, σ2 is the compensation factor of the set precipitation of the dust suppression robot, σ3 is the compensation factor of the absolute value of the difference between the ambient temperature of the dust suppression robot and the reference temperature, and e is a natural constant.

7. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 1 is characterized in that: The comparison results in a moving plan for the dust suppression robot, and the specific analysis process is as follows: Obtaining a dust suppression robot track position status data set, the dust suppression robot track position status data set specifically includes the dust suppression robot track running speed, the distance between the dust suppression robot and the nearest obstacle in front of the track, and the distance between the dust suppression robot and the target stack; Based on the acquired track position state data set of the dust suppression robot, the track position state characteristic value of the dust suppression robot is obtained through comprehensive analysis. The track position state characteristic value of the dust suppression robot is used as the analysis basis for comparing and obtaining the travel plan of the dust suppression robot. The dust suppression robot track position state characteristic value is compared with the dust suppression robot travel plan corresponding to each dust suppression robot track position state characteristic value stored in the database to obtain the dust suppression robot travel plan corresponding to the dust suppression robot track position state characteristic value.

8. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 7 is characterized in that: The specific analysis process of the track position state characteristic value of the dust suppression robot is as follows: Wherein, δ is the characteristic value of the track position state of the dust suppression robot, ys is the track running speed of the dust suppression robot, za is the distance between the dust suppression robot and the nearest obstacle in front of the track, mb is the distance between the dust suppression robot and the target stacking, τ1 is the compensation factor of the set track running speed of the dust suppression robot, τ2 is the compensation factor of the set distance between the dust suppression robot and the nearest obstacle in front of the track, and τ3 is the compensation factor of the set distance between the dust suppression robot and the target stacking.

9. The method for deploying the spraying arm of the track-sharing intelligent dust suppression robot according to claim 1, characterized in that: The comparison results in a deployment plan for the spray arm of the dust suppression robot. The specific analysis process is as follows: The basic information characteristic value of the stacking and the moving plan of the dust suppression robot are stored as a designated label, and the designated label is compared with the dust suppression robot spray arm deployment plan corresponding to each designated label stored in the database to obtain the dust suppression robot spray arm deployment plan corresponding to the designated label.

10. A track-shared intelligent dust suppression robot spray arm deployment system, applied to the track-shared intelligent dust suppression robot spray arm deployment method according to any one of claims 1 to 9, characterized in that: It includes a basic information characteristic value acquisition module, a need to start running judgment module, a can start running judgment module, a travel plan comparison module and a spray arm deployment plan comparison module, among which: The basic information characteristic value acquisition module is used to analyze the basic information of the stacking to obtain the characteristic value of the basic information of the stacking; The need to start running judgment module is used to analyze the stacking state and judge whether the dust suppression robot corresponding to the stacking needs to start running; The module for judging whether to start running is used to analyze the environment in which the dust suppression robot that needs to start running is located, and judge whether the dust suppression robot can start running; The travel plan comparison module is used to analyze the track position state of the dust suppression robot that can start running, and compare to obtain the travel plan of the dust suppression robot; The spray arm deployment plan comparison module is used to compare and obtain the spray arm deployment plan of the dust suppression robot based on the characteristic value of the basic information of the stacking and the travel plan of the dust suppression robot.

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