Industrial wireless communication system and method

Abstract

The invention relates to an industrial wireless communication system and method. The system comprises terminal equipment used for executing specific operation or data acquisition in an industrial environment; the directional antenna wireless router serves as a data transmission relay in a network, is provided with a directional antenna and is used for covering and connecting the terminal equipment in a directional mode through wireless signals so as to achieve wireless transmission of data, and rapid deployment and flexible adjustment of the router are achieved by introducing the unmanned aerial vehicle technology and the scheme. The unmanned aerial vehicle can quickly fly to the target position, and the flight height and the antenna angle are adjusted according to actual requirements, so that the timeliness and the accuracy of network coverage are ensured. The flexibility is crucial to frequent changes of the positions and the number of the terminal devices in the industrial environment, and the adaptability and the stability of the network are improved.

Description

Technical Field

[0001] The present invention relates to the field of industrial wireless communication, and particularly to an industrial wireless communication system and method. Background Art

[0002] In an industrial wireless communication network, there are numerous terminal devices and routers covering these terminals, and their positions and quantities often change due to production operation requirements. This dynamic nature poses challenges to the stability and coverage of the network. In traditional network architectures, routers mostly use omnidirectional antennas, which easily lead to problems of signal overlapping coverage and channel interference. At the same time, existing coverage judgment methods have a large amount of calculation, and the elephant herd optimization algorithm has a large number of iterations when solving router planning parameters, affecting the real-time performance and efficiency of the network.

[0003] In addition, although traditional solutions have proposed using directional antenna wireless routers to replace omnidirectional antenna routers to reduce signal interference and improve coverage efficiency, these solutions often ignore how to deploy these routers efficiently and flexibly in an actual industrial environment. Especially when facing a large number of terminal devices and a complex and changeable network environment, how to quickly and accurately adjust the positions of routers and the angles of directional antennas to ensure the stability and coverage of the network, for example:

[0004] (1) Traditional directional antenna wireless routers are connected to a wired gateway through physical lines, which limits the deployment flexibility of the routers. In an industrial environment, the positions and quantities of terminal devices often change, and routers need to be able to quickly adjust their positions and coverage directions. However, the connection method of physical lines makes it difficult to move and adjust the routers, unable to meet the requirements of a dynamically changing network environment;

[0005] (2) Traditional solutions use the elephant herd optimization algorithm to optimize and solve router planning parameters and improve the coverage judgment method to reduce computing resources. However, due to the lack of real-time position information and dynamic adjustment capabilities, the accuracy and efficiency of their coverage judgment and optimization algorithms are easily limited. Especially when facing a complex and changeable network environment, traditional solutions cannot timely and accurately adjust the positions of routers and the angles of antennas to address network coverage and channel interference problems. Summary of the Invention

[0006] The object of the present invention is to overcome the deficiencies of the prior art, meet the actual needs, and provide an industrial wireless communication system and method to solve the problem that the current traditional directional antenna wireless router is connected to the wired gateway through a physical line, which limits the deployment flexibility of the router. In an industrial environment, the positions and quantities of terminal devices often change, and it is required that the router can quickly adjust its position and coverage direction. However, the connection method of the physical line makes it difficult for the router to move and adjust, and it cannot meet the requirements of the dynamically changing network environment. The traditional solution uses the elephant herd optimization algorithm to optimize and solve the router planning parameters, and improves the coverage judgment method to reduce computing resources. However, due to the lack of real-time position information and dynamic adjustment capabilities, the accuracy and efficiency of its coverage judgment and optimization algorithm are easily limited. Especially in the face of a complex and changeable network environment, the traditional solution cannot timely and accurately adjust the position of the router and the antenna angle to cope with the technical problems of network coverage and channel interference.

[0007] To achieve the object of the present invention, the technical solution adopted by the present invention is as follows: Design an industrial wireless communication system, which includes:

[0008] Terminal devices, which are used to perform operations or data collection in an industrial environment;

[0009] A directional antenna wireless router, equipped with a directional antenna, which is used to cover and connect the terminal devices in a directional manner to achieve wireless transmission of data;

[0010] A wireless gateway, which serves as a data aggregation and forwarding center, is wirelessly connected to the directional antenna wireless router, and receives and forwards data to the backend system;

[0011] A network model construction and optimization module, which includes a real-time positioning sub-module, a data transmission sub-module, a demand analysis sub-module, a model construction sub-module, an environmental factor consideration sub-module, a simulation test sub-module, and an optimization adjustment sub-module, and is used to construct and optimize a network model according to the drone position information, network requirements, and environmental factors to improve the network coverage and communication performance.

[0012] Preferably, the directional antenna wireless router also has Wi-Fi docking, and is wirelessly connected to the wireless gateway through Wi-Fi docking to ensure that data can be efficiently and stably transmitted between the router and the wireless gateway.

[0013] Preferably, the real-time positioning sub-module uses the GPS system on the drone to obtain the accurate position information of each drone in real time, including longitude, latitude, and altitude, and transmits this information to the ground control center in real time through the data transmission sub-module.

[0014] Preferably, the model construction sub-module constructs a network model including terminals, drones, and gateways in combination with the drone position information, clarifies the communication path where the drone wirelessly covers the terminals through a directional antenna and is connected to the gateway through a wired or wireless backhaul; the environmental factor consideration sub-module considers environmental factors such as building blockages and terrain undulations on wireless communication, and modifies and optimizes the network model.

[0015] Preferably, the simulation test sub-module conducts simulation tests on the network model to verify whether the network coverage and communication performance meet the requirements; the optimization and adjustment sub-module optimizes and adjusts the network model according to the simulation test results, including adjusting the drone position and directional antenna angle parameters to improve the network coverage and communication performance, and implements the adjustment and monitors the adjustment process through the adjustment execution and monitoring sub-module.

[0016] An industrial wireless communication method includes the industrial wireless communication system described above, and further includes the following steps:

[0017] S1: Initialize the system and environmental preparation

[0018] Prepare the drone platform

[0019] Drone selection and procurement: Select a suitable drone according to the requirements of the industrial wireless communication network to ensure that its load capacity, endurance, flight stability, etc. meet the requirements;

[0020] Equipment installation: Install a GPS positioning module, a directional antenna wireless router, and a wireless charging component on each drone to ensure that the equipment is firmly fixed;

[0021] Software configuration: Configure flight control components and communication protocols for the drone to ensure that it can communicate normally with the ground control center;

[0022] Calibrate and test the drone and the directional antenna wireless router

[0023] Drone calibration: Calibrate the flight control system, sensors, GPS, etc. of the drone to ensure flight accuracy and stability;

[0024] Router test: Test the communication performance of the directional antenna wireless router, including signal strength, coverage range, transmission rate, etc., to ensure that it meets the network communication requirements;

[0025] Wireless charging efficiency test: Test the charging efficiency and stability of the wireless charging component under different conditions to ensure that it can provide continuous power support for the router;

[0026] Comprehensive test: Conduct joint debugging tests on the drone and the router to ensure that the two can work together to achieve network communication coverage;

[0027] Establish a ground control center

[0028] Hardware preparation: Build a hardware platform for monitoring screens, servers, and communication devices to ensure the ability to receive and process data and information from drones in real time;

[0029] Obtain location information and establish a network model

[0030] Obtain the location information of the drones

[0031] Real-time positioning: Use the GPS system on the drones to obtain the precise location information of each drone in real time, including longitude, latitude, and altitude;

[0032] Data transmission: Transmit the drone location information to the ground control center in real time for subsequent network model construction and optimization;

[0033] Construct a network model

[0034] Requirement analysis: Analyze the key indicators of network coverage, communication rate, and latency according to the requirements of the industrial wireless communication network;

[0035] Model construction: Combine the drone location information to construct a network model including terminals, drones, and gateways, and clarify the communication path where the drones wirelessly cover the terminals through directional antennas and are connected to the gateways through wired or wireless backhaul;

[0036] Consider environmental factors: Consider the impact of environmental factors such as building blockage and terrain undulation on wireless communication, and modify and optimize the network model;

[0037] Model verification and optimization

[0038] Simulation test: Conduct a simulation test on the network model to verify whether the network coverage and communication performance meet the requirements;

[0039] Optimization adjustment: According to the simulation test results, optimize and adjust the network model, including adjusting the drone positions and directional antenna angle parameters to improve the network coverage and communication performance;

[0040] S2. Dynamic coverage and interference optimization

[0041] Construct a fitness function

[0042] Constraint condition analysis: Analyze the coverage requirements, interference limitations, drone flight altitude, and safety distance constraint conditions according to the requirements and actual situation of the industrial wireless communication network;

[0043] Fitness function design: Combine the constraint conditions to design a fitness function for evaluating the network coverage and communication performance under different drone positions and directional antenna angles;

[0044] Application of Elephant Herd Optimization Algorithm

[0045] Algorithm Initialization: Initialize the parameters of the elephant herd optimization algorithm;

[0046] Iterative Calculation: Combine the real-time position information and the network model, and use the elephant herd optimization algorithm to iteratively calculate the optimal UAV position and the directional antenna angle. In each iteration, evaluate the quality of the current solution according to the fitness function, and update the position and speed of the elephant herd;

[0047] Convergence Judgment: Judge whether the algorithm converges, that is, whether the quality of the current solution meets the preset convergence conditions. If the conditions are met, output the optimal solution; if the conditions are not met, continue the iterative calculation;

[0048] Implementation of Dynamic Adjustment Strategy

[0049] Coverage Range Detection: Real-time monitor the coverage range of each UAV, and judge whether there are overlaps or blind spots;

[0050] Position Adjustment Trigger: When it is detected that the coverage ranges of multiple UAVs overlap, immediately trigger the position adjustment algorithm, re-plan the UAV path and the directional antenna angle according to the optimal solution, avoid interference and optimize the coverage;

[0051] Adjustment Execution and Monitoring: After receiving the adjustment instruction, the UAV executes the automatic flight adjustment. The ground control center updates the network model in real time and monitors the adjustment process to ensure that the UAV maintains a safe flight attitude and a stable communication link during the adjustment;

[0052] S3. UAV Position Adjustment and Notification

[0053] Instruction Sending

[0054] Instruction Generation: The ground control center generates the UAV position adjustment instruction according to the position adjustment algorithm;

[0055] Instruction Sending: Send the instruction to the relevant UAVs through wireless communication to ensure the accuracy and timeliness of the instruction transmission;

[0056] UAV Execution of Adjustment

[0057] Instruction Reception: After receiving the adjustment instruction, the UAV parses the instruction content and prepares to execute the adjustment;

[0058] Automatic Flight Adjustment: The UAV executes the automatic flight adjustment operation according to the instruction, including changing the flight direction, speed, and altitude parameters, and at the same time continues to monitor the position change through GPS to ensure flight accuracy and safety;

[0059] Monitoring and Verification of Adjustment Effect

[0060] Network model update: The ground control center updates the network model in real time according to the change of the UAV's position, predicts and verifies whether the adjusted network coverage and communication performance meet the requirements;

[0061] Adjustment effect evaluation: Evaluate and analyze the adjusted network coverage and communication performance. If the adjustment effect is not good, re-trigger the position adjustment algorithm for optimization;

[0062] Notification and recording

[0063] Notify on-site staff: After the adjustment is completed, notify the on-site staff to confirm the new position and record the adjustment log, including information such as the adjustment time, UAV number, and new position coordinates for subsequent analysis;

[0064] Log management and analysis: Manage and analyze the adjustment log, summarize the experiences and lessons in the adjustment process, and propose improvement measures to optimize subsequent network deployment and adjustment work;

[0065] S4. Quick adjustment of the position of the directional antenna wireless router

[0066] Transportation operation: Use the UAV to quickly transport the directional antenna wireless router to the target position, and keep the UAV's attitude stable during transportation to avoid collision or falling;

[0067] Link stability monitoring

[0068] Communication link monitoring: Continuously monitor the stability of the wireless communication link between the UAV and the router during the adjustment process to ensure that the link quality is good and there are no interruptions or packet losses that affect the network communication quality;

[0069] Emergency handling: If abnormal situations such as unstable or interrupted links occur, immediately take emergency handling measures such as re-adjusting the position or switching the communication link to ensure the continuity and stability of network communication;

[0070] S5. Wireless charging and battery life management

[0071] Wireless charging start

[0072] Automatic detection: When the directional antenna wireless router is carried on top of the UAV, the wireless charging component inside the UAV automatically detects the battery status of the router;

[0073] Charging start: If the router's battery power is insufficient, the wireless charging component automatically starts to wirelessly charge the router's battery to ensure that the router can continue to be powered during flight to meet the network communication requirements;

[0074] Intelligent battery management

[0075] Power Monitoring: Continuously monitor the battery power status of the router and dynamically adjust the charging strategy according to the power change to avoid damage to the battery caused by overcharging or over-discharging;

[0076] Task Requirement Matching: Reasonably allocate the power usage of the router according to the current task requirements and flight plan. When the task is urgent or the flight distance is long, prioritize the power supply of the router to ensure the stability and continuity of network communication;

[0077] Charging Strategy Optimization: Continuously optimize the charging strategy based on historical data and experience summary to improve the charging efficiency and battery service life;

[0078] Maintenance and Upkeep

[0079] Regular Inspection: Regularly inspect and maintain the wireless charging components of the drone and the router, including cleaning the charging interface and checking whether the charging line and connectors are loose or damaged;

[0080] Fault Handling: If a fault or abnormality is found in the wireless charging components, immediately conduct fault troubleshooting and handling to ensure the normal operation of the wireless charging function and the continuous power supply of the router;

[0081] Training and Guidance: Provide training and guidance to the staff in the ground control center on wireless charging technology and equipment usage to improve their professional skills and fault handling capabilities, ensuring the effective application and management of wireless charging technology;

[0082] S6. Monitoring and Data Analysis

[0083] Continuous Monitoring

[0084] Status Monitoring: The ground control center continuously monitors indicators such as the flight status, position information, and network communication quality of the drone to ensure that the drone remains safe and stable during flight and the network communication quality is good;

[0085] Anomaly Detection: Continuously monitor abnormal situations in the network, such as communication interruption and signal attenuation. Once an anomaly is detected, immediately conduct fault troubleshooting and handling to ensure the continuity and stability of network communication;

[0086] Data Collection and Analysis

[0087] Data Acquisition: Collect data on the flight trajectory of the drone, network performance indicators, and interference situations to ensure the accuracy and integrity of the data and provide a reliable basis for subsequent analysis;

[0088] Data Analysis: Use data analysis tools and methods to analyze and process the collected data, extract useful information, identify problems and bottlenecks in the network, and propose improvement measures and optimization suggestions;

[0089] Network Planning Strategy Adjustment

[0090] Strategy formulation: Based on the data analysis results, formulate a network planning strategy adjustment plan, including measures such as optimizing the layout of drones, adjusting the angles of directional antennas, and increasing the number of gateways to improve network coverage and communication performance;

[0091] Implementation and verification: Implement the adjustment plan and conduct verification tests.

[0092] Preferably, the network performance metrics in S6 include packet loss rate, latency, and throughput.

[0093] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0094] 1. By introducing drone technology, the present invention realizes the rapid deployment and flexible adjustment of routers. Drones can quickly fly to the target location and adjust the flight altitude and antenna angle according to actual needs, thus ensuring the timeliness and accuracy of network coverage. This flexibility is crucial for the frequent changes in the positions and quantities of terminal devices in industrial environments, improving the adaptability and stability of the network.

[0095] 2. The present invention uses a directional antenna wireless router to effectively reduce signal duplication coverage and channel interference problems, improving signal quality and network coverage efficiency. At the same time, combined with the advanced elephant herd optimization algorithm and improved coverage judgment method, the solution can more accurately evaluate the network coverage situation and adjust the position and antenna angle of the router in real time to cope with the dynamic changes of the network environment and ensure the best coverage effect.

[0096] 3. Through the introduction of drone technology and the improvement of coverage judgment and optimization algorithms, the present invention enables the solution to respond more quickly to changes in the network environment. Whether it is the movement of terminal device positions or the increase or decrease in quantity, adjustments and optimizations can be made in a short time, thereby improving the real-time performance and efficiency of the network

[0097] 4. The present invention is easy to expand the network scale. As the number of terminal devices in the industrial environment increases, it is convenient to increase the number of routers carried by drones to meet the network coverage requirements. This scalability provides convenience for future network upgrades and expansions

[0098] 5. By improving network coverage efficiency and stability, the present invention reduces the downtime and maintenance costs caused by network failures. At the same time, the rapid deployment and adjustment capabilities of drones also reduce the costs and time of manual operation and maintenance, thus achieving the maximization of cost-effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] Figure 1 is a schematic flowchart of the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0100] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0101] An industrial wireless communication system, see Figure 1 , the system includes:

[0102] Terminal devices, used to perform operations or data collection in an industrial environment;

[0103] A directional antenna wireless router, equipped with a directional antenna, used to cover and connect the terminal devices in a directional manner to achieve wireless data transmission;

[0104] A wireless gateway, serving as a data aggregation and forwarding center, wirelessly connected to the directional antenna wireless router, receiving and forwarding data to the backend system;

[0105] A network model construction and optimization module, which includes a real-time positioning sub-module, a data transmission sub-module, a requirements analysis sub-module, a model construction sub-module, an environmental factor consideration sub-module, a simulation test sub-module, and an optimization adjustment sub-module, used to construct and optimize a network model based on drone position information, network requirements, and environmental factors to improve network coverage and communication performance.

[0106] Specifically, see Figure 1 , the directional antenna wireless router also has Wi-Fi docking, and is wirelessly connected to the wireless gateway through Wi-Fi docking to ensure efficient and stable data transmission between the router and the wireless gateway.

[0107] Furthermore, see Figure 1 , the real-time positioning sub-module uses the GPS system on the drone to obtain the precise position information of each drone in real time, including longitude, latitude, and altitude, and transmits this information to the ground control center in real time through the data transmission sub-module.

[0108] It is worth noting that, see Figure 1 , the model construction sub-module constructs a network model including terminals, drones, and gateways in combination with the drone position information, clarifies the communication path where the drone wirelessly covers the terminal through a directional antenna and is connected to the gateway through a wired or wireless backhaul; the environmental factor consideration sub-module considers the impact of environmental factors such as building blockages and terrain undulations on wireless communication, and modifies and optimizes the network model.

[0109] It should be noted that, see Figure 1 , the simulation test sub-module conducts simulation tests on the network model to verify whether the network coverage and communication performance meet the requirements; the optimization adjustment sub-module optimizes and adjusts the network model according to the simulation test results, including adjusting the drone position and directional antenna angle parameters to improve network coverage and communication performance, and implementing and monitoring the adjustment process through the adjustment execution and monitoring sub-module.

[0110] An industrial wireless communication method, including an industrial wireless communication system, further includes the following steps:

[0111] S1: Initialize the system and prepare the environment

[0112] Prepare the drone platform

[0113] Drone selection and procurement: Select drones with a load capacity ≥ 5 kg, endurance ≥ 2 hours, and flight stability ≤ 0.5 m (horizontal deviation);

[0114] Equipment installation: Install a GPS positioning module (accuracy ≤ 3 m), a directional antenna wireless router (transmission rate ≥ 500 Mbps, coverage range ≥ 2 km), and a wireless charging component (charging efficiency ≥ 80%) on each drone;

[0115] Software configuration: Configure a flight control component (supporting autonomous navigation and obstacle avoidance functions) and communication protocols (TCP / IP, UDP) for the drones;

[0116] Calibrate and test the drones and directional antenna wireless routers

[0117] Drone calibration: After calibrating the flight control system, sensors, and GPS, the flight accuracy ≤ 1 m and the stability ≤ 0.3 m / s;

[0118] Router test: The signal strength ≥ -70 dBm, the actual measured coverage range ≥ 1.8 km, and the actual measured transmission rate ≥ 450 Mbps;

[0119] Wireless charging efficiency test: Under different wind speeds (0 - 10 m / s) and temperatures (-10°C to 40°C), the charging efficiency is stable between 75% - 85%;

[0120] Comprehensive test: The joint debugging of the drones and routers, with the communication delay ≤ 50 ms and the packet loss rate ≤ 0.1%;

[0121] Establish a ground control center

[0122] Hardware preparation: Set up a high-definition monitoring screen (resolution ≥ 1920x1080), a high-performance server (CPU ≥ 8 cores, memory ≥ 32 GB), and communication equipment (supporting 4G / 5G networks);

[0123] Obtain location information and establish a network model

[0124] Real-time positioning: The accuracy of the drone GPS system ≤ 2 m, and the height measurement error ≤ 10 m;

[0125] Data analysis: The drone position information is updated once per second and transmitted to the ground control center;

[0126] Network model construction: Considering building blockage (impact of buildings with a height ≥ 10m) and terrain undulation (slope ≤ 30°), optimize network coverage;

[0127] Model verification and optimization: Simulate and test the network coverage rate and communication performance, adjust the UAV position (each adjustment ≤ 50m) and the directional antenna angle (each adjustment ≤ 5°) until the coverage rate ≥ 95% and the communication rate ≥ 400Mbps;

[0128] S2. Dynamic coverage and interference optimization

[0129] Construct the fitness function

[0130] Constraints: Coverage range requirement ≥ 90%, interference limit ≤ -80dBm, UAV flight altitude 100 - 300m, safety distance ≥ 50m;

[0131] Fitness function: F = α * coverage rate + β * communication rate - γ * interference, where α = 0.6, β = 0.3, γ = 0.1;

[0132] Application of elephant herd optimization algorithm

[0133] Algorithm initialization: Number of elephant herds = 50, number of iterations = 1000, and the initial positions are randomly distributed within the network area;

[0134] Iterative calculation: Update the positions and speeds of the elephant herds in each iteration, and evaluate the quality of the current solution according to the fitness function;

[0135] Convergence judgment: When the change in the optimal solution is less than 0.1% in 20 consecutive iterations, it is considered that the algorithm converges;

[0136] Implementation of dynamic adjustment strategy

[0137] Coverage range detection: Real-time monitor the coverage range of each UAV, and trigger the position adjustment algorithm when the overlap degree ≥ 20%;

[0138] Position adjustment trigger: Re-plan the UAV path according to the optimal solution, with each adjustment amplitude ≤ 30m and adjustment angle ≤ 10°;

[0139] Adjustment execution and monitoring: The UAV automatically executes the adjustment instruction, and the ground control center updates the network model in real time, monitors the adjustment process to ensure the safe flight of the UAV and the stability of the communication link;

[0140] S3. UAV position adjustment and notification

[0141] Instruction sending

[0142] Instruction generation: The ground control center generates UAV position adjustment instructions according to the position adjustment algorithm, with an accuracy ≤ 1m;

[0143] Instruction Sending: Send instructions to relevant drones via 4G / 5G network, with transmission delay ≤ 100 ms;

[0144] Drones Execute Adjustment

[0145] Instruction Receiving: After receiving the adjustment instructions, the drones parse the instruction content and prepare to execute the adjustment, with parsing time ≤ 50 ms;

[0146] Automatic Flight Adjustment: The drones execute automatic flight adjustment operations according to the instructions, including changing the flight direction, speed (adjustment range 5 - 20 m / s), and altitude (adjustment range 100 - 300 m). Meanwhile, continue to monitor the position change through GPS to ensure flight accuracy and safety;

[0147] Monitoring and Verification of Adjustment Effects

[0148] Network Model Update: The ground control center updates the network model in real - time according to the position change of the drones, and predicts and verifies whether the adjusted network coverage and communication performance meet the requirements (coverage rate ≥ 95%, communication rate ≥ 400 Mbps);

[0149] Evaluation of Adjustment Effects: If the adjustment effects are not good (coverage rate increase < 5%, communication rate increase < 10%), then re - trigger the position adjustment algorithm for optimization;

[0150] Notification and Recording

[0151] Notify on - site staff: After the adjustment is completed, notify on - site staff via text message or email to confirm the new position, and record the adjustment log, including information such as adjustment time, drone number, new position coordinates (accuracy ≤ 1 m) for subsequent analysis;

[0152] Log Management and Analysis: Manage and analyze the adjustment log, summarize the experiences and lessons during the adjustment process, and propose improvement measures to optimize subsequent network deployment and adjustment work;

[0153] S4. Quick Adjustment of the Position of Directional Antenna Wireless Router

[0154] Transportation Operation: Use drones to quickly transport the directional antenna wireless router to the target position (error ≤ 5 m), and keep the drone attitude stable (tilt angle ≤ 10°) during transportation to avoid collision or falling;

[0155] Link Stability Monitoring

[0156] Communication Link Monitoring: Continuously monitor the stability of the wireless communication link between the drones and the router during the adjustment process to ensure good link quality (bit error rate ≤ 0.01%, packet loss rate ≤ 0.1%), and prevent situations such as interruption or packet loss from affecting network communication quality;

[0157] Emergency handling: If abnormal situations such as unstable or interrupted links occur (duration ≥ 5 seconds), immediately take emergency handling measures such as readjusting the position (adjustment range ≤ 20m) or switching communication links to ensure the continuity and stability of network communication;

[0158] S5. Wireless charging and battery life management

[0159] Wireless charging start

[0160] Automatic detection: When the directional antenna wireless router is mounted on the top of the drone, the wireless charging component inside the drone automatically detects the battery status of the router (once every 10 minutes);

[0161] Charging start: If the battery power of the router is insufficient (≤ 30%), the wireless charging component automatically starts wireless charging of the router battery (charging power ≥ 50W) to ensure that the router can continuously supply power during flight to meet the network communication requirements (battery life ≥ 1.5 hours);

[0162] Intelligent battery management

[0163] Battery power monitoring: Continuously monitor the battery power status of the router (updated once every 5 minutes), and dynamically adjust the charging strategy according to the power change (such as pausing charging when the power ≥ 70%);

[0164] Task requirement matching: Reasonably allocate the power usage of the router according to the current task requirements and flight plan (such as giving priority to ensuring the power supply of the router during emergency tasks);

[0165] Charging strategy optimization: Continuously optimize the charging strategy according to historical data and experience summary (such as adjusting the charging power, charging time, etc.) to improve the charging efficiency and battery service life (battery cycle life ≥ 500 times);

[0166] Maintenance and servicing

[0167] Regular inspection: Regularly inspect and maintain the wireless charging components of the drone and the router (once a month), including cleaning the charging interface, checking whether the charging line and connectors are loose or damaged;

[0168] Fault handling: If it is found that the wireless charging component has a fault or abnormality (such as a decrease in charging power, charging interruption, etc.), immediately conduct fault troubleshooting and handling (handling time ≤ 2 hours) to ensure the normal operation of the wireless charging function and the continuous power supply of the router;

[0169] Training and Guidance: Provide training and guidance on wireless charging technology and equipment usage to the staff of the ground control center (once every quarter), improve their professional skills and troubleshooting capabilities, and ensure the effective application and management of wireless charging technology;

[0170] S6. Monitoring and Data Analysis

[0171] Continuous Monitoring

[0172] Status Monitoring: The ground control center continuously monitors the flight status of the UAV (including flight altitude, speed, attitude, etc.), position information (longitude, latitude, altitude), and network communication quality (including signal strength, transmission rate, latency, etc.) to ensure that the UAV maintains safe and stable flight and good network communication quality during flight (signal strength ≥ -70dBm, transmission rate ≥ 400Mbps, latency ≤ 50ms);

[0173] Anomaly Detection: Real-time monitor anomalies in the network such as communication interruption (duration ≥ 10 seconds), signal attenuation (attenuation amplitude ≥ 20dB), etc. Once an anomaly is detected, immediately conduct fault troubleshooting and handling (handling time ≤ 10 minutes) to ensure the continuity and stability of network communication;

[0174] Data Collection and Analysis

[0175] Data Acquisition: Collect the UAV flight trajectory (recorded once every 1 second), network performance metrics (recorded once every 5 minutes), and interference data (recorded once every 10 minutes) to ensure the accuracy and integrity of the data and provide a reliable basis for subsequent analysis;

[0176] Data Analysis: Use data analysis tools and methods (such as Python, R language) to analyze and process the collected data (such as data cleaning, data visualization, correlation analysis, etc.), extract useful information, discover problems and bottlenecks in the network, and propose improvement measures and optimization suggestions (such as optimizing the UAV layout, adjusting the orientation of the directional antenna, etc.);

[0177] Network Planning Strategy Adjustment

[0178] Strategy Formulation: Based on the data analysis results, formulate a network planning strategy adjustment plan (such as increasing the number of UAVs, optimizing the flight path) to improve the network coverage and communication performance (coverage rate increased to ≥ 98%, communication rate increased to ≥ 500Mbps);

[0179] Implementation and Verification: Implement the adjustment plan and conduct verification tests (such as actual flight tests, network performance tests) to ensure the effectiveness and feasibility of the adjustment plan.

[0180] It is worth introducing that, see Figure 1, the network performance metrics in S6 include packet loss rate, latency, and throughput.

[0181] Example 1

[0182] Elephant Herd Optimization Algorithm and Dynamic Adjustment Strategy

[0183] S1. Algorithm Initialization

[0184] Number of elephant herds: 50

[0185] Number of iterations: 1000

[0186] Initial position: Randomly distributed within the network area. The network area is a 1000m x 1000m two-dimensional plane.

[0187] UAV parameters: Flight altitude range is 100 - 300m, and the initial altitude is randomly selected.

[0188] S2. Iterative Calculation

[0189] Fitness function: F = 0.6 × coverage rate + 0.3 × communication rate - 0.1 × interference

[0190] Coverage rate calculation: By calculating the ground area covered by each UAV and merging the overlapping parts, the total coverage rate is obtained.

[0191] Communication rate: Calculated according to the link quality (such as SNR) between UAVs.

[0192] Interference: Calculate the interference between UAVs to ensure that the interference limit ≤ -80dBm.

[0193] S3. Convergence Judgment

[0194] After each iteration, record the current optimal solution (i.e., the highest fitness value).

[0195] If the optimal solution changes less than 0.1% in 20 consecutive iterations, the algorithm is considered to have converged.

[0196] S4. Implementation of Dynamic Adjustment Strategy

[0197] Coverage Range Detection

[0198] Real-time monitor the coverage range of each UAV through sensors or communication link quality assessment.

[0199] When it is found that the overlap degree of the coverage ranges of two or more UAVs ≥ 20%, trigger the position adjustment algorithm.

[0200] Position Adjustment Trigger

[0201] According to the current optimal solution (i.e., the UAV position combination with the highest fitness), re-plan the UAV path.

[0202] Adjustment range limit: Each adjustment range ≤ 30m.

[0203] Adjustment angle limit: Each adjustment angle ≤ 10°.

[0204] Adjustment execution and monitoring

[0205] The drone automatically adjusts its position according to the adjustment instruction.

[0206] The ground control center updates the network model in real time and monitors the adjustment process.

[0207] Ensure that the drone flies under the limit of a safety distance ≥ 50m to avoid collisions.

[0208] Monitor the communication link quality to ensure the stability of the communication link during the adjustment process.

[0209] S5. Numerical example

[0210] Initial position: 50 drones are randomly distributed within the network area, and the initial altitude is randomly selected between 100 - 300m.

[0211] Iteration process:

[0212] The 1st iteration: Calculate the fitness value of the initial position and record the optimal solution.

[0213] The 2nd - 1000th iterations: Update the elephant herd positions and speeds, calculate the new fitness values, and update the optimal solution.

[0214] At the 980th iteration, the optimal solution reaches stability, with a change less than 0.1% for 20 consecutive iterations.

[0215] Convergence result:

[0216] Coverage rate: 95%

[0217] Communication rate: Average 10Mbps

[0218] Interference: -85dBm

[0219] Dynamic adjustment:

[0220] After the 1000th iteration, it is detected that the overlap degree of the coverage ranges of drones A and B is 22%.

[0221] According to the optimal solution, re - plan the paths of drones A and B, with an adjustment range of 25m and an adjustment angle of 8°.

[0222] During the adjustment process, the ground control center updates the network model in real time and monitors the drone flight and communication link quality.

[0223] After the adjustment is completed, recalculate the fitness value to ensure that the network performance meets the requirements.

[0224] Through the above algorithm and dynamic adjustment strategy, it is possible to ensure that the UAV network achieves an optimal balance in terms of coverage, communication rate, and interference limitation, while ensuring the safe flight of the UAV and the stability of the communication link.

[0225] Embodiment 2

[0226] UAV Position Adjustment and Notification

[0227] S1. Instruction Generation

[0228] Input: Current UAV position, target position (calculated by the position adjustment algorithm), UAV number.

[0229] Output: UAV position adjustment instruction, including UAV number, target position coordinates (longitude, latitude, altitude, accuracy ≤ 1m), adjustment direction, speed range (5 - 20m / s).

[0230] Steps:

[0231] Calculate the adjustment direction and distance based on the current UAV position and the target position.

[0232] Determine the speed range and flight altitude according to the UAV flight performance and adjustment requirements.

[0233] Generate a UAV position adjustment instruction containing the above information.

[0234] S2. Instruction Sending

[0235] Input: UAV position adjustment instruction.

[0236] Output: Instruction sending success / failure status.

[0237] Steps:

[0238] Establish a communication connection with the UAV through the 4G / 5G network.

[0239] Send the instruction to the UAV in the form of a data packet and set a timeout (≤ 100ms). Wait for the UAV to return a confirmation message to determine whether the instruction is sent successfully.

[0240] S3. UAV Execution of Adjustment

[0241] Input: UAV position adjustment instruction.

[0242] Output: Adjustment completion status, new position coordinates.

[0243] Steps:

[0244] After the drone receives the instruction, it parses the instruction content.

[0245] According to the target position and the current position in the instruction, it plans the flight path.

[0246] Performs automatic flight adjustment operations, including changing the flight direction, speed, and altitude.

[0247] Monitors the position change through GPS to ensure flight accuracy and safety.

[0248] When the drone reaches the target position, it returns the adjustment completion status and the new position coordinates.

[0249] S4. Monitoring and Verification of Adjustment Effects

[0250] Input: Drone new position coordinates, network model parameters.

[0251] Output: Adjustment effect evaluation result (whether it meets the requirements).

[0252] Steps:

[0253] Updates the network model according to the drone new position coordinates.

[0254] Predicts and verifies the adjusted network coverage and communication performance.

[0255] Judges whether it meets the requirements of coverage rate ≥ 95% and communication rate ≥ 400 Mbps.

[0256] If it does not meet the requirements, it triggers the position adjustment algorithm again for optimization adjustment.

[0257] S5. Notification and Recording

[0258] Input: Adjustment completion status, new position coordinates, drone number.

[0259] Output: Notification information, adjustment log.

[0260] Steps:

[0261] Generates notification information according to the adjustment completion status and the new position coordinates.

[0262] Sends the notification information to the on-site staff via text message or email.

[0263] Records the adjustment log, including information such as adjustment time, drone number, new position coordinates, etc.

[0264] Manages and analyzes the adjustment log, and proposes improvement measures to optimize the subsequent network deployment and adjustment work.

[0265] S6. Implementation Record

[0266] Scenario Description: During a certain UAV network deployment, it was found that the network coverage in a certain area was insufficient and the communication rate was low. The ground control center calculated the target coordinates for adjusting the UAV's position based on the location and generated an adjustment instruction to send to the UAV.

[0267] Value:

[0268] UAV Number: UAV001

[0269] Current Location: Longitude 116.404°, Latitude 39.915°, Altitude 200m

[0270] Target Location: Longitude 116.406°, Latitude 39.916°, Altitude 220m (accuracy ≤ 1m)

[0271] Adjustment Direction: 15° east by south

[0272] Speed Range: 10m / s

[0273] Instruction Sending Time: 2023-10-01 10:00:00

[0274] UAV Instruction Receiving Time: 2023-10-01 10:00:00.090 (transmission delay 90ms)

[0275] UAV Execution Adjustment Time: 2023-10-01 10:00:00.150 (start adjustment 50ms after parsing time)

[0276] Adjustment Completion Time: 2023-10-01 10:00:30 (flight time 30 seconds)

[0277] New Position Coordinates: Longitude 116.406°, Latitude 39.916°, Altitude 220m (accuracy ≤ 1m)

[0278] Network Coverage Rate: 90% before adjustment, 96% after adjustment

[0279] Communication Rate: 380Mbps before adjustment, 450Mbps after adjustment

[0280] Adjustment Effect Evaluation:

[0281] Coverage Rate Increase: 6% (meeting the requirement of ≥ 5%)

[0282] Communication Rate Increase: 18.4% (meeting the requirement of ≥ 10%)

[0283] Notification and Record:

[0284] Notification Information: UAV001 has been adjusted to the new position, and both the network coverage rate and the communication rate have increased.

[0285] Adjustment Log: Record information such as the adjustment time, drone number, new position coordinates, etc., and note the changes in network coverage rate and communication rate before and after the adjustment.

[0286] Through the above embodiments, it can be ensured that the drone can quickly respond to changes in network coverage and communication performance during network deployment, optimize network performance through precise position adjustment, improve network coverage rate and communication rate, and at the same time ensure the flight safety of the drone and the stability of the communication link.

[0287] Embodiment III

[0288] Quick adjustment of the position of the directional antenna wireless router

[0289] In a complex industrial environment, due to terrain obstruction, the network coverage in some areas is poor. In order to quickly optimize the network coverage in these areas, it is decided to use a drone carrying a directional antenna wireless router for quick position adjustment. The following are the specific implementation steps and values.

[0290] S1. Implementation steps

[0291] Transportation operation

[0292] Target position setting: Determine the specific position where the network coverage needs to be optimized, with coordinates (longitude 116.397128, latitude 39.916527), and the target position error requirement ≤ 5m.

[0293] Drone takeoff: Select a drone with a load ≥ 5kg and a flight endurance ≥ 2 hours, and carry the directional antenna wireless router to take off.

[0294] Flight process: The drone flies steadily to the target position at a speed of 15m / s according to the preset flight path. During the flight, the attitude of the drone remains stable, and the tilt angle is controlled within ≤ 10°, ensuring the safety of the transportation process.

[0295] Arrival at the target: The drone accurately arrives at the target position with an error of 3m, meeting the requirements.

[0296] Link stability monitoring

[0297] Communication link monitoring: After the drone flies to the target position and installs the router, immediately start monitoring the stability of the wireless communication link between the drone and the router.

[0298] Initial link quality: The monitoring results show that the initial link quality is good, with a bit error rate of 0.005% and a packet loss rate of 0.05%, both meeting the requirements (bit error rate ≤ 0.01%, packet loss rate ≤ 0.1%).

[0299] Continuous Monitoring: During the process of adjusting the router's position, continuously monitor the link quality to ensure that there are no interruptions or packet losses.

[0300] Handling of Abnormal Situations: During the adjustment process, the link suddenly became unstable, the bit error rate increased to 0.012%, the packet loss rate increased to 0.15%, and the duration exceeded 5 seconds. Immediately take emergency measures to readjust the router's position within a range of 15m, and the link quality returned to stability after the adjustment.

[0301] S2. Numerical Values

[0302] UAV Flight Parameters:

[0303] Flight Speed: 15m / s

[0304] Flight Altitude: 200m

[0305] Attitude Stable Tilt Angle: ≤10°

[0306] Error in Reaching the Target Position: 3m

[0307] Link Stability Monitoring Parameters:

[0308] Initial Bit Error Rate: 0.005%

[0309] Initial Packet Loss Rate: 0.05%

[0310] Abnormal Bit Error Rate: 0.012% (duration 5 seconds)

[0311] Abnormal Packet Loss Rate: 0.15% (duration 5 seconds)

[0312] Bit Error Rate after Adjustment: Restored to 0.008%

[0313] Packet Loss Rate after Adjustment: Restored to 0.06%

[0314] Emergency Handling Parameters:

[0315] Range of Re-adjusting the Position: 15m

[0316] Link Quality Recovery Time: 20 seconds

[0317] Through the above embodiments, the UAV was successfully used to quickly transport the directional antenna wireless router to the target position, and the link stability was continuously monitored during the adjustment process. When the link became unstable, emergency measures were taken in a timely manner to ensure the continuity and stability of network communication. Finally, the router position adjustment was successful, and the network coverage was optimized, meeting the user's needs.

[0318] Example 4

[0319] Wireless Charging and Endurance Management

[0320] S1. Implementation Steps and Numerical Values

[0321] Wireless Charging Start

[0322] Automatic Detection: When the directional antenna wireless router is mounted on the top of the drone, the wireless charging component inside the drone automatically detects the battery status of the router every 10 minutes.

[0323] Numerical Value: Detection Time Interval = 10 minutes

[0324] Charging Start: If the battery power of the router is less than 30%, the wireless charging component automatically starts wireless charging for the router battery.

[0325] Numerical Value: Charging Start Threshold = 30% Battery Power

[0326] Charging Power: ≥50W

[0327] Battery Life: Ensure that the router can continuously supply power during flight to meet the network communication requirements, and the battery life is at least 1.5 hours.

[0328] S2. Intelligent Battery Management

[0329] Battery Monitoring: Continuously monitor the battery status of the router in real time and update it every 5 minutes.

[0330] Numerical Value: Battery Monitoring Time Interval = 5 minutes

[0331] Dynamic Adjustment of Charging Strategy: Dynamically adjust the charging strategy according to the battery power change. For example, when the battery power reaches 70%, suspend charging to extend the battery life.

[0332] Numerical Value: Suspension of Charging Threshold = 70% Battery Power

[0333] Task Requirement Matching: Reasonably allocate the power usage of the router according to the current task requirements and flight plan. For example, in case of an emergency task, give priority to ensuring the power supply of the router.

[0334] Numerical Value: Emergency Task Power Allocation Priority = Highest

[0335] Optimization of Charging Strategy: Continuously optimize the charging strategy based on historical data and experience summary, such as adjusting the charging power and charging time, to improve the charging efficiency and battery life.

[0336] Numerical Value: Charging Strategy Optimization Period = Once a Week

[0337] Target Battery Cycle Life: ≥500 times

[0338] S3. Maintenance and Upkeep

[0339] Regular inspection: Regularly inspect and maintain the wireless charging components of the drone and the router, including cleaning the charging interface and checking whether the charging lines and connectors are loose or damaged.

[0340] Value: Inspection and maintenance cycle = once a month

[0341] Fault handling: If a fault or abnormality is found in the wireless charging component (such as a decrease in charging power, charging interruption, etc.), immediately conduct fault troubleshooting and handling.

[0342] Value: Fault handling time ≤ 2 hours

[0343] Training and guidance: Provide training and guidance on wireless charging technology and equipment usage to the staff in the ground control center to improve their professional skills and fault handling capabilities.

[0344] Value: Training cycle = once a quarter.

[0345] By implementing the above wireless charging and battery life management, the project team has successfully ensured the continuity and stability of the drone in network coverage tasks. The automatic detection and charging start function of the wireless charging component effectively avoids communication interruption caused by insufficient router power. The intelligent battery management strategy dynamically adjusts the charging and usage strategies according to the task requirements and battery status, prolongs the battery life, and improves the charging efficiency. Regular inspections, maintenance, and fault handling ensure the normal operation of the wireless charging function and the continuous power supply of the router. In addition, through training and guidance, the staff in the ground control center are more proficient in using wireless charging technology and equipment, effectively improving the overall operation efficiency and management level of the project.

[0346] Example 5

[0347] Monitoring and data analysis

[0348] In the suburbs of a certain city, we deployed a drone communication network to provide temporary high-bandwidth network coverage services. The network consists of 10 drones, and each drone is equipped with a GPS positioning module, a directional antenna wireless router, and a wireless charging component. The ground control center is responsible for monitoring the status of the drones, the quality of network communication, and adjusting the network planning strategy based on the collected data.

[0349] S1. Continuous monitoring

[0350] Status monitoring

[0351] Flight status: The ground control center continuously monitors the flight altitude (maintained between 150 - 250m), speed (maintained between 10 - 15m / s), attitude (tilt angle ≤ 5°), etc. of each drone to ensure the safety and stability of the drone during flight.

[0352] Location information: The drone transmits its longitude, latitude, and altitude information in real time, and the ground control center ensures the accuracy of this information for subsequent network planning.

[0353] Network communication quality: Monitoring metrics include signal strength (maintained at ≥ -65 dBm), transmission rate (maintained at ≥ 450 Mbps), latency (maintained at ≤ 40 ms), etc., to ensure good network communication quality.

[0354] Anomaly detection

[0355] During a certain monitoring, the ground control center found that the drone numbered UAV-03 suddenly experienced signal attenuation (attenuation amplitude reached 25 dB) during flight, and the duration lasted for 15 seconds.

[0356] Immediately start the troubleshooting program and find that it is due to the drone encountering a dense forest during flight, resulting in signal occlusion.

[0357] The ground control center quickly adjusted the flight path of UAV-03 to avoid the forest area and restored normal network communication quality within 5 minutes.

[0358] S2. Data collection and analysis

[0359] Data collection

[0360] Flight trajectory: Each drone records its flight trajectory, including longitude, latitude, altitude, etc., every 1 second.

[0361] Network performance metrics: Record network performance metrics, including signal strength, transmission rate, latency, etc., every 5 minutes.

[0362] Interference situation data: Record interference situation data, including the location of the interference source, interference intensity, etc., every 10 minutes.

[0363] Data analysis

[0364] Use Python to analyze the collected data. First, perform data cleaning to remove outliers and duplicate data.

[0365] Then perform data visualization to draw graphs such as drone flight trajectory graphs, network performance metric graphs, interference situation distribution graphs, etc., to visually observe the network status.

[0366] Through correlation analysis, it is found that there is a positive correlation between the flight altitude of the drone and the network transmission rate, that is, the higher the flight altitude, the faster the transmission rate.

[0367] Meanwhile, it was also found that the relative positions of the drones have a significant impact on the network coverage. When the distance between the drones is too close, strong signal interference will occur.

[0368] S3. Network Planning Strategy Adjustment

[0369] Strategy Formulation

[0370] According to the data analysis results, formulate a network planning strategy adjustment plan.

[0371] First, increase the number of drones to 12 to expand the network coverage.

[0372] Secondly, optimize the flight paths and altitudes of the drones to avoid signal attenuation caused by too low flight altitudes and reduced signal coverage caused by too high flight altitudes.

[0373] Finally, adjust the relative positions of the drones to reduce signal interference.

[0374] Implementation and Verification

[0375] Put the adjustment plan into implementation, add 2 drones, and re-plan the flight paths and altitudes.

[0376] Conduct actual flight tests and network performance tests to verify the effectiveness and feasibility of the adjustment plan.

[0377] The test results show that the network coverage rate has increased to 98.5%, and the communication rate has increased to 520 Mbps, meeting the expected goals.

[0378] S4. Numerical Example

[0379] Flight Status: Drone UAV-01, flight altitude 200 m, speed 12 m / s, attitude tilt angle 3°.

[0380] Position Information: Longitude 116.397128°, Latitude 39.916527°, Altitude 200 m.

[0381] Network Communication Quality: Signal Strength -60 dBm, Transmission Rate 480 Mbps, Delay 35 ms.

[0382] Anomaly Detection: UAV-03, signal attenuation 25 dB, duration 15 seconds, fault troubleshooting time 5 minutes.

[0383] Data Analysis: The correlation coefficient between flight altitude and network transmission rate is 0.85, and the correlation coefficient between the distance between drones and signal interference intensity is -0.70.

[0384] Adjustment plan: Add 2 drones. After optimizing the flight path, the average altitude is increased to 220m, and the relative positions between the drones are adjusted to the minimum interference distance.

[0385] Verification result: The network coverage rate is 98.5%, and the communication rate is 520Mbps, meeting the expected goals.

[0386] In addition, the components designed in the present invention are all common standard components or components known to those skilled in the art. Their structures and principles can be learned by those skilled in the art through technical manuals or by conventional experimental methods. Those skilled in the art can fully implement them without further elaboration. The content protected by the present invention does not involve improvements to the internal structure and method.

[0387] The embodiments disclosed in the present invention are preferred embodiments, but not limited thereto. Those of ordinary skill in the art can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. However, as long as they do not depart from the spirit of the present invention, they are within the protection scope of the present invention.

Claims

1. An industrial wireless communication system, characterized in that: The system includes: Terminal equipment, used to perform operations or data collection in industrial environments; A directional antenna wireless router, equipped with a directional antenna, is used to cover and connect the terminal device in a directional manner to achieve wireless transmission of data; The wireless gateway, as a data aggregation and forwarding center, is wirelessly connected to the directional antenna wireless router to receive and forward data to the back-end system; The network model construction and optimization module includes a real-time positioning submodule, a data transmission submodule, a demand analysis submodule, a model construction submodule, an environmental factor consideration submodule, a simulation test submodule and an optimization adjustment submodule. It is used to build and optimize the network model according to the UAV location information, network requirements and environmental factors to improve the network coverage and communication performance.

2. The industrial wireless communication system according to claim 1, characterized in that: The directional antenna wireless router also has Wi-Fi docking, which is wirelessly connected to the wireless gateway through the Wi-Fi docking, ensuring that data can be transmitted efficiently and stably between the router and the wireless gateway.

3. The industrial wireless communication system according to claim 1, characterized in that: The real-time positioning submodule uses the GPS system on the drone to obtain the precise location information of each drone in real time, including longitude, latitude, and altitude, and transmits this information to the ground control center in real time through the data transmission submodule.

4. The industrial wireless communication system according to claim 1, characterized in that: The model building submodule combines the drone location information to build a network model including terminals, drones, and gateways, and clarifies the communication path of the drones that wirelessly cover the terminals through directional antennas and connect to the gateways through wired or wireless backhaul; the environmental factor consideration submodule considers the impact of environmental factors such as building obstructions and terrain undulations on wireless communications, and corrects and optimizes the network model.

5. The industrial wireless communication system according to claim 1, characterized in that: The simulation test submodule performs simulation test on the network model to verify whether the network coverage and communication performance meet the requirements; the optimization and adjustment submodule optimizes and adjusts the network model according to the simulation test results, including adjusting the drone position and directional antenna angle parameters to improve the network coverage and communication performance, and implements the adjustment and monitors the adjustment process through the adjustment execution and monitoring submodule.

6. An industrial wireless communication method, characterized in that: The industrial wireless communication system comprising any one of claims 1 to 5 further comprises the following steps: S1: Initialize the system and prepare the environment Preparing the drone platform Drone selection and procurement: Select suitable drones based on the needs of the industrial wireless communication network to ensure that their load capacity, endurance, flight stability, etc. meet the requirements; Calibrate and test drones and directional antenna wireless routers UAV calibration: Calibrate the UAV’s flight control system, sensors, GPS, etc. to ensure flight accuracy and stability; Router test: Test the communication performance of the directional antenna wireless router, including signal strength, coverage, transmission rate, etc., to ensure that it meets the network communication requirements; Establishing ground control center Hardware preparation: Build monitoring screens, servers, and communication equipment hardware platforms to ensure that data and information from drones can be received and processed in real time; Get location information and build a network model Get drone location information Real-time positioning submodule: Use the GPS system on the drone to obtain the precise location information of each drone in real time, including longitude, latitude, and altitude; Data transmission submodule: transmits the location information of the UAV to the ground control center in real time for subsequent network model construction and optimization; Building a network model Demand analysis submodule: Analyze key indicators such as network coverage, communication rate, and latency based on the needs of the industrial wireless communication network; Model building submodule: Combined with the drone location information, a network model including terminals, drones, and gateways is constructed to clarify the communication path of the drones that wirelessly cover the terminals through directional antennas and connect to the gateways through wired or wireless backhaul; Environmental factors consideration submodule: Considers the impact of environmental factors such as building obstruction and terrain undulation on wireless communication, and corrects and optimizes the network model; Model validation and optimization Simulation test submodule: performs simulation test on the network model to verify whether the network coverage and communication performance meet the requirements; Optimization and adjustment submodule: Based on the simulation test results, the network model is optimized and adjusted, including adjusting the drone position and directional antenna angle parameters to improve network coverage and communication performance; S2. Dynamic coverage and interference optimization Constructing the fitness function Constraint analysis: Based on the needs and actual situation of the industrial wireless communication network, analyze the coverage requirements, interference restrictions, drone flight altitude and safety distance constraints; Fitness function design: Combined with the constraints, a fitness function is designed to evaluate the network coverage and communication performance under different UAV positions and directional antenna angles; Application of elephant herd optimization algorithm Algorithm initialization: Initialize the parameters of the elephant group optimization algorithm; Iterative calculation: Combine real-time location information and network models, and use the elephant swarm optimization algorithm to iteratively calculate the optimal drone position and directional antenna angle. In each iteration, the quality of the current solution is evaluated according to the fitness function, and the position and speed of the elephant swarm are updated; Convergence judgment: judge whether the algorithm converges, that is, whether the quality of the current solution meets the preset convergence conditions. If the conditions are met, the optimal solution is output; if not, the iterative calculation continues; Dynamically adjust strategy implementation Coverage detection submodule: monitors the coverage of each drone in real time to determine whether there is overlap or blind spot; Position adjustment trigger submodule: When overlapping coverage of multiple drones is detected, the position adjustment algorithm is immediately triggered to replan the drone path and directional antenna angle according to the optimal solution to avoid interference and optimize coverage; Adjustment execution and monitoring submodule: After receiving the adjustment command, the UAV performs automatic flight adjustment. The ground control center updates the network model in real time and monitors the adjustment process to ensure that the UAV maintains a safe flight posture and a stable communication link during the adjustment process. S3. Drone position adjustment and notification Send command Command generation: The ground control center generates the UAV position adjustment command based on the position adjustment algorithm; Command transmission: Send commands to relevant drones through wireless communication to ensure the accuracy and timeliness of command transmission; Drone execution adjustment Command reception: After receiving the adjustment command, the drone parses the command content and prepares to execute the adjustment; Automatic flight adjustment: The drone performs automatic flight adjustment operations according to instructions, including changing flight direction, speed, and altitude parameters, while continuing to monitor position changes through GPS to ensure flight accuracy and safety; Adjustment effect monitoring and verification Network model update: The ground control center updates the network model in real time according to the changes in the drone's position, predicting and verifying whether the adjusted network coverage and communication performance meet the requirements; Adjustment effect evaluation: evaluate and analyze the adjusted network coverage and communication performance. If the adjustment effect is not good, re-trigger the location adjustment algorithm for optimization and adjustment. Notification and Records Notify on-site staff: After the adjustment is completed, notify the on-site staff to confirm the new position and record the adjustment log, including the adjustment time, drone number, new position coordinates and other information for subsequent analysis; Log management and analysis: Manage and analyze adjustment logs, summarize lessons learned during the adjustment process, and propose improvement measures to optimize subsequent network deployment and adjustment work; S4, Directional antenna wireless router position quick adjustment Transportation operation: Use a drone to quickly transport the directional antenna wireless router to the target location, and keep the drone in a stable position during transportation to avoid collision or falling; Link stability monitoring Communication link monitoring: During the adjustment process, the wireless communication link stability between the drone and the router is continuously monitored to ensure that the link quality is good and there is no interruption or packet loss that affects the network communication quality; S5, wireless charging and battery life management Wireless charging enabled Automatic detection: When the directional antenna wireless router is mounted on top of the drone, the wireless charging component inside the drone automatically detects the battery status of the router; Charging start: If the battery of the router is low, the wireless charging component will automatically start to wirelessly charge the battery of the router, ensuring that the router can continue to supply power to meet network communication needs during the flight; Intelligent power management Power monitoring: monitor the battery status of the router in real time and dynamically adjust the charging strategy according to the power changes to avoid damage to the battery caused by overcharging or discharging; Mission demand matching: Rationally allocate the power usage of the router according to the current mission requirements and flight plan. When the mission is urgent or the flight distance is long, the power supply of the router is prioritized to ensure the stability and continuity of network communication; Charging strategy optimization: Continuously optimize charging strategy based on historical data and experience to improve charging efficiency and battery life; Maintenance and care Regular inspection: Regularly inspect and maintain the wireless charging components of the drone and router, including cleaning the charging port and checking whether the charging line and connector are loose or damaged; Troubleshooting: If a wireless charging component is found to be faulty or abnormal, immediately troubleshoot and handle the problem to ensure the normal operation of the wireless charging function and the continuous power supply of the router; Training and guidance: Provide training and guidance on wireless charging technology and equipment use to the staff of the ground control center to improve their professional skills and troubleshooting capabilities to ensure the effective application and management of wireless charging technology; S6. Monitoring and data analysis Continuous monitoring Status monitoring: The ground control center continuously monitors the flight status, location information, network communication quality and other indicators of the drone to ensure that the drone remains safe and stable during flight and that the network communication quality is good; Anomaly detection: Real-time monitoring of abnormal conditions in the network, such as communication interruption and signal attenuation, etc. Once an abnormality is found, immediate troubleshooting and processing are carried out to ensure the continuity and stability of network communication; Data collection and analysis Data collection: Collect drone flight trajectories, network performance indicators, and interference data to ensure the accuracy and completeness of the data and provide a reliable basis for subsequent analysis; Data analysis: Use data analysis tools and methods to analyze and process the collected data, extract useful information to find problems and bottlenecks in the network, and propose improvement measures and optimization suggestions; Network planning strategy adjustment Strategy formulation: Develop network planning strategy adjustment plans based on data analysis results, including optimizing drone layout, adjusting directional antenna angles, and increasing the number of gateways to improve network coverage and communication performance; Implementation and Verification: Put the adjustment plan into practice and conduct verification testing.

7. The industrial wireless communication method according to claim 6, characterized in that: In S1, a GPS positioning module, a directional antenna wireless router and a wireless charging component need to be installed on each drone to ensure that the equipment is firmly fixed. At the same time, the drone needs to be configured with a flight control component and a communication protocol to ensure that it can communicate normally with the ground control center.

8. The industrial wireless communication method according to claim 6, characterized in that: After the router test is completed in S1, the charging efficiency and stability of the wireless charging component need to be tested under different conditions to ensure that it can provide continuous power support for the router. Finally, the drone and the router are tested together to ensure that the two can work together to achieve network communication coverage.

9. The industrial wireless communication method according to claim 6, characterized in that: The network performance indicators in S6 include packet loss rate, delay, and throughput.

10. The industrial wireless communication method according to claim 6, characterized in that: If abnormal situations such as link instability or interruption occur during the S4 link stability monitoring, emergency measures such as readjusting the position or switching the communication link will be taken immediately to ensure the continuity and stability of network communication.

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