Multi-modal sensing unmanned operation platform for improving water quality of rivers and lakes and intelligent decision-making method

Abstract

The invention discloses a multi-mode perception unmanned operation platform for river and lake water quality improvement and an intelligent decision-making method, and the platform comprises an intelligent control center, and an autonomous navigation system, a multi-parameter water quality detection system, a dual-mode aeration system and an intelligent medicament decision-making system which are connected with the intelligent control center. Autonomous navigation operation of a complex water area is achieved through the autonomous navigation system, the multi-parameter water quality detection system provides a multi-mode sensing sensor array, comprehensive water quality parameter detection can be conducted on the water areas of rivers and lakes, and the dual-mode aeration system conducts aeration according to dissolved oxygen parameters. A working mode instruction intelligently judged by the intelligent control center is executed, aeration treatment is conducted, the intelligent medicament decision-making system dynamically calculates the medicament adding amount according to the water quality parameters, and accurate adding is achieved. According to the system, efficient integrated collaborative operation of autonomous navigation operation, full-dimensional water quality parameter real-time monitoring, dual-mode precise aeration and an on-demand dosing mechanism is realized, and the effect and efficiency of river and lake water quality improvement can be effectively improved.

Description

Technical Field

[0001] The present application relates to the technical field of river and lake water quality improvement, and in particular to a multimodal perception unmanned operation platform and intelligent decision-making method for river and lake water quality improvement. Background Art

[0002] With the increasing global shortage of water resources and water pollution, the ecological health and water quality improvement of rivers and lakes have become important issues in the field of environmental protection. Traditional methods for monitoring and treating river and lake water quality usually rely on manual sampling, laboratory analysis and fixed monitoring equipment. These methods have limitations such as low efficiency, high cost and poor real-time performance, and are difficult to meet the needs of dynamic monitoring and precise treatment of complex water environments. In addition, traditional treatment methods such as chemical agent injection and physical dredging often lack targetedness and intelligent decision-making support, which may lead to secondary pollution or waste of resources. Therefore, there is an urgent need for an unmanned operation platform for water quality improvement that integrates intelligent navigation, full-dimensional water quality detection, precise aeration, on-demand drug administration and composite power supply. It is particularly suitable for scenarios such as the treatment of black and odorous water bodies in rivers and lakes and water quality regulation in aquaculture. Summary of the Invention

[0003] To address the problems of low efficiency, high cost, poor real-time performance, and the inability of operating devices to operate autonomously and sustainably in complex environments associated with traditional river and lake water quality improvement methods, the present invention provides a multimodal perception unmanned operation platform for river and lake water quality improvement. This platform implements autonomous navigation, real-time monitoring of all-dimensional water quality parameters, and the efficient, integrated collaboration of dual-mode precision aeration and on-demand dosing mechanisms, effectively improving the effectiveness and efficiency of river and lake water quality improvement. The present invention also relates to an intelligent decision-making method for this multimodal perception unmanned operation platform for river and lake water quality improvement.

[0004] The present invention is achieved through the following technical solutions:

[0005] A multi-modal sensing unmanned operation platform for improving river and lake water quality, including an intelligent control center and an autonomous navigation system, a multi-parameter water quality detection system, a dual-mode aeration system, and an intelligent drug decision-making system, all connected to the intelligent control center;

[0006] The intelligent control center is used to receive and process data from various systems and generate control instructions to coordinate the operation of various systems; during the inspection operation stage, it receives the water quality parameters of river and lake water transmitted by the multi-parameter water quality detection system and the position and path information of the autonomous navigation system, analyzes the data based on the water quality detection requirements, and coordinates the multi-parameter water quality detection system to perform water quality detection at sampling points on the preset navigation path, and at the same time receives the preset or temporary obstacle avoidance path information generated by the autonomous navigation system and sends control execution instructions to drive the autonomous navigation system to navigate along the preset navigation path; during the event response stage, based on the real-time abnormal data of the multi-parameter water quality detection system, it intelligently determines the working mode of the dual-mode aeration system, and sends corresponding control instructions to the dual-mode aeration system and the intelligent agent decision-making system to coordinate the two to perform aeration treatment and agent delivery;

[0007] The autonomous navigation system is used to ensure the autonomous navigation of the unmanned operating platform in river and lake waters; it includes a laser SLAM module, an environmental modeling module, an RTK-GNSS positioning module, a multi-target path planning module, an obstacle avoidance control module and a dynamic heading correction module connected in sequence, the laser SLAM module is used to measure the distance and direction of surrounding objects through a laser radar, identify obstacles in real time, and transmit the identified obstacle information to the environmental modeling module and the multi-target path planning module; the environmental modeling module is used to construct a raster map of the operating waters based on the pre-acquired satellite map of the river and lake area and the obstacle information transmitted in real time by the laser SLAM module; the RTK-GNSS positioning module is used to provide centimeter-level positioning function; the multi-target path planning The module is used in the inspection operation phase of the unmanned operation platform. When receiving the information transmitted by the laser SLAM module that an obstacle is detected on the preset navigation path, it automatically plans a temporary obstacle avoidance path by introducing the improved A* algorithm based on energy consumption cost and pollution level in combination with the grid map, and sends the temporary obstacle avoidance path information to the intelligent control center; the obstacle avoidance control module receives the control execution instruction of the intelligent control center, generates the heading control instruction according to the temporary obstacle avoidance path, and controls the navigation direction of the unmanned operation platform; the dynamic heading correction module receives the control execution instruction of the intelligent control center, and after the unmanned operation platform completes the obstacle avoidance, it automatically guides it to return to the preset navigation path by comparing the deviation between the real-time positioning data provided by the RTK-GNSS positioning module and the preset navigation path;

[0008] The multi-parameter water quality detection system is used to perform multimodal sensing detection of water quality parameters of rivers and lakes according to sampling points on a preset navigation path through coordination of an intelligent control center during the inspection operation phase; the multi-parameter water quality detection system includes a multimodal sensing sensor array composed of a spectrometer, an electrochemical sensor and a COD sensor, as well as an interconnected Internet of Things communication module and a data fusion processor, wherein the spectrometer is used to detect dissolved organic matter, inorganic matter, heavy metals, transparency and turbidity in river and lake water; the electrochemical sensor includes an NH3-N detection electrode, a dissolved oxygen sensor and a pH sensor, which are used to detect NH3-N, dissolved oxygen and pH values in river and lake water, and the COD sensor is used to detect COD in river and lake water. The Internet of Things communication module is respectively connected to each part of the multimodal sensing array, and is used to transmit the water quality parameters detected by the spectrometer, electrochemical sensor and COD sensor to the data fusion processor, and the data fusion processor is used to comprehensively analyze the water quality parameters, evaluate the current water quality, and use a lightweight trend prediction model to evaluate the water quality change trend based on the water quality parameters received multiple times;

[0009] The dual-mode aeration system is used to execute the working mode of intelligent control center intelligent determination and perform aeration treatment in the event response stage according to the real-time detection value of dissolved oxygen parameters in river and lake water provided by the dissolved oxygen sensor in the multi-parameter water quality detection system. When the detection value is between the first threshold and the second threshold, the microporous aeration mode is executed, and when the detection value is lower than the first threshold, the supersaturated dissolved oxygen mode is executed; the dual-mode aeration system includes a nano aeration tube array, a double-helix gas-liquid mixing chamber, an oxygen booster tank, an air compressor and a variable frequency drive module, the variable frequency drive module, the air compressor and the nano aeration tube array are connected in sequence, and the oxygen booster tank, the double-helix gas-liquid mixing chamber and the nano aeration tube array are connected in sequence; in the microporous aeration mode The variable frequency drive module receives control instructions from the intelligent control center to dynamically adjust the input driving force, driving the air compressor to deliver air to the nano aeration tube array. The nano aeration tube array is a structure composed of several aeration tubes with nano-scale tiny pores, which then release bubbles into the river and lake water through the tiny pores; in the supersaturated dissolved oxygen mode, the oxygen booster tank is opened to inject pure oxygen into the double helix gas-liquid mixing chamber. The double helix gas-liquid mixing chamber is a cavity with a double helix structure inside and is connected to the river and lake water body. The water in the river and lake in the cavity and the pure oxygen injected by the oxygen booster tank are mixed under the guidance of the double helix structure. The mixed gas and liquid are then delivered to the nano aeration tube array and then released into the river and lake water through the nano aeration tube array;

[0010] The intelligent drug decision-making system is used to dynamically calculate the drug dosage based on the water quality parameters of river and lake water provided by the multi-parameter water quality detection system, and release the drug into the river and lake water; it includes a drug storage module, an adaptive drug dosing calculation module, a three-dimensional spraying module, a multi-degree-of-freedom robotic arm and a controllable vortex nozzle. The adaptive drug dosing calculation module receives the water quality parameters transmitted by the multi-parameter water quality detection system, dynamically calculates the required drug dosage based on the adaptive drug dosing algorithm, generates drug dosing control instructions, and sends the calculation results and drug dosing control instructions to the intelligent control center. After analysis and processing, the intelligent control center sends control execution instructions to the three-dimensional spraying module and the multi-degree-of-freedom robotic arm; the three-dimensional spraying module is respectively connected to the drug storage module and the controllable vortex nozzle, and controls the controllable vortex nozzle according to the instructions of the intelligent control center to release the liquid drug stored in the drug storage module into the river and lake water according to the calculated dosage; the multi-degree-of-freedom robotic arm performs solid drug delivery according to the instructions of the intelligent control center.

[0011] Preferably, the multimodal perception unmanned operation platform also includes a composite energy system, which is connected to the intelligent control center for intelligent distribution and management of energy; the composite energy system includes a dual-axis tracking solar panel, a vertical axis wind turbine, an MPPT controller, an AC / DC converter, a lithium battery pack, a supercapacitor pack, and an intelligent power distribution module, and the MPPT controller is respectively connected to the dual-axis tracking solar panel and the lithium battery pack to control the maximum power point tracking of the dual-axis tracking solar panel and stably output the electric energy generated by the dual-axis tracking solar panel to the power-consuming equipment or the lithium battery pack, and the power-consuming equipment is an autonomous navigation system, a multi-parameter water quality detection system, and a plurality of parameters. The measurement system, dual-mode aeration system and intelligent drug decision-making system each involve components involving electricity consumption. The AC / DC converter is respectively connected to the vertical axis wind turbine and the lithium battery pack, and is used to convert the electric energy generated by the vertical axis wind turbine into direct current and stably output it to the power-consuming device or the lithium battery pack. The supercapacitor group is used to provide fast power transmission to the power-consuming device with instantaneous high power demand. The intelligent power distribution module is respectively connected to the MPPT controller, AC / DC converter, lithium battery pack and supercapacitor group, and is used to intelligently distribute electricity to the power-consuming device according to the real-time power demand and priority of each power-consuming device and the power status of the lithium battery pack and supercapacitor group.

[0012] Preferably, the multimodal sensing unmanned operation platform further includes a cloud monitoring system, an audible and visual alarm device, and a self-inspection and maintenance system, and the cloud monitoring system, the visual alarm device, and the self-inspection and maintenance system are all connected to the intelligent control center.

[0013] The cloud monitoring system is deployed on a cloud server and connected to the intelligent control center via LoRa / 5G dual-mode communication to receive data from the intelligent control center and provide remote monitoring functions;

[0014] The sound and light alarm device is used to receive the alarm instruction sent by the intelligent control center and issue an alarm;

[0015] The self-inspection and maintenance system is used to receive OTA remote upgrade instructions, upgrade the software of the intelligent control center, and send self-inspection request data to the intelligent control center during the initialization phase of the unmanned operation platform; the intelligent control center sends self-inspection instructions to the multi-parameter water quality detection system, the dual-mode aeration system, the intelligent drug decision-making system, the composite energy system and the autonomous navigation system according to the self-inspection request data received from the self-inspection and maintenance system, and performs sensor status checks in each system.

[0016] Preferably, in the dual-mode aeration system, the intelligent control center controls the flow rate of bubbles released by the nano aeration tube array according to the dissolved oxygen value monitored by the multi-parameter water quality detection system; when the dissolved oxygen value is less than or equal to 2.0 mg / L, the supersaturated dissolved oxygen mode is automatically activated, and the nano aeration tube array releases bubbles at a flow rate of 100%; when the dissolved oxygen value is greater than 2.0 mg / L and less than 4.0 mg / L, the microporous aeration mode is automatically activated, and the flow rate of bubbles released by the nano aeration tube array is controlled according to the ratio of the dissolved oxygen value to 4.0 mg / L.

[0017] Preferably, in the dual-mode aeration system, the swirl angle of the double-helix gas-liquid mixing chamber is 15 degrees ± 2 degrees, and the thickness of the inner wall ceramic coating is 80 μm; the pore size distribution of the nano aeration tube array is 25 μm to 45 μm, and the porosity is greater than or equal to 82%; the variable frequency drive module dynamically adjusts the power of the air compressor according to the real-time detection value of the dissolved oxygen parameter in the river and lake water, and the power adjustment range is 0.5 kW to 3 kW, with an accuracy of ±2%.

[0018] Preferably, in the intelligent drug decision-making system, the drug storage module is equipped with a heating device, adopts a partitioned heating cabin, and controls the temperature at 45°C±3°C to ensure the activity and fluidity of the drug; the intelligent drug decision-making system also includes a drug delivery pipeline, which is used to connect the three-dimensional spraying module with the drug storage module, and is equipped with a vibrator for periodic vibration to prevent the drug from settling and clogging in the pipeline; the controllable vortex nozzle is made of titanium alloy material.

[0019] Preferably, the adaptive dosing calculation module in the intelligent drug decision system first determines the water quality index based on the water quality parameters transmitted by the multi-parameter water quality detection system, and then calculates the required drug dosage according to the interval rule of the water quality index, and generates the corresponding drug dosing control instruction; wherein, the calculation formula of the water quality index is as follows:

[0020] WQI=0.25×COD+0.28×NH3-N+0.22×pH+0.15×Turbidity+0.1×DO

[0021] Wherein, WQI represents water quality index, COD represents chemical oxygen demand parameter, NH3-N represents NH3-N parameter, pH represents pH parameter, Turbidity represents turbidity parameter, and DO represents dissolved oxygen parameter;

[0022] When WQI is greater than 100, calculate the dosage according to the following formula:

[0023] total=5e^0.02×(WQI-100)

[0024] Among them, total represents the dosage, the unit is liter / square kilometer;

[0025] When WQI is greater than 80 and WQI is less than or equal to 100, the dosage is 3 liters / km2;

[0026] When WQI is less than or equal to 80, the dosage is 1 liter / square kilometer.

[0027] Preferably, the intelligent power distribution module of the composite energy system intelligently distributes power to the power-consuming equipment, including:

[0028] Calculate the total energy power required by the unmanned operation platform using the following formula:

[0029] P required =P mobility +P aeration +P sensing

[0030] Among them, P required Indicates the total power required for energy, P mobility Represents the total power of the autonomous navigation system, P aeration Represents the total power of the dual-mode aeration system, P sensingrepresents the sum of the total power of the multi-parameter water quality monitoring system and the total power of the intelligent drug decision-making system; if the total amount of electricity generated by the dual-axis tracking solar panels and the vertical-axis wind turbine meets the total energy demand, the unmanned operation platform will give priority to using the electricity generated by the dual-axis tracking solar panels and the vertical-axis wind turbine, and store the unconsumed electricity generated by the dual-axis tracking solar panels and the vertical-axis wind turbine in the lithium battery pack;

[0031] If the total amount of electricity generated by the dual-axis tracking solar panels and vertical-axis wind turbines cannot meet the total energy demand, the unmanned operation platform uses a mixed power supply mode of electricity generated by the dual-axis tracking solar panels and vertical-axis wind turbines, lithium battery packs, and supercapacitor packs, and supplies power to the electrical equipment according to the preset priority order of the electrical equipment.

[0032] Preferably, in the autonomous navigation system, the improved A* algorithm introduces energy consumption cost factor and pollution level factor during path planning, and the improved cost function is:

[0033] cost=0.7×distance+0.2×energy_consumption+0.1×pollution_level

[0034] Among them, distance represents the distance between the unmanned work platform and the obstacle, which is obtained by the laser SLAM module, energy_consumption represents the energy consumption cost, pollution_level represents the pollution level of rivers and lakes in the work area, and cost represents the comprehensive cost of executing a certain path, which is obtained by weighted summing the distance, energy consumption cost, and pollution level according to different weights to evaluate the advantages and disadvantages of different path planning schemes.

[0035] An intelligent decision-making method based on the above-mentioned multimodal perception unmanned operation platform for river and lake water quality improvement includes the following steps:

[0036] Initialization phase steps: The intelligent control center sends self-test instructions to the multi-parameter water quality detection system, dual-mode aeration system, intelligent drug decision-making system, composite energy system, and autonomous navigation system based on the self-test request data of the self-test maintenance system to check the status of the sensors within each system; the environmental modeling module uses the laser SLAM module to build a local map based on the modeling instructions of the intelligent control center, and matches it with the pre-acquired satellite map of the river and lake area to generate a raster map of the river and lake area including static and dynamic obstacles, and applies the preset navigation path to the raster map;

[0037] Inspection operation phase steps: During the inspection process, the multi-parameter water quality detection system uses electrochemical sensors and COD sensors to detect water quality parameters in river and lake areas at preset collection time according to the detection instructions of the intelligent control center. It uses a spectrum analyzer to perform spectral analysis of the operating water area at preset spectral analysis time to obtain full-dimensional water quality parameters, and sends the obtained water quality parameters to the data fusion processor through the Internet of Things communication module for comprehensive water quality analysis; when the intelligent control center receives data that the laser SLAM module detects obstacles on the preset navigation path, it sends avoidance instructions to the autonomous navigation system, and the autonomous navigation system controls the multi-target path planning module, uses the improved A* algorithm and combines the grid map to plan the optimal temporary obstacle avoidance path, and after the obstacle avoidance is completed, the autonomous navigation system controls the heading to guide the system back to the preset navigation path;

[0038] Steps in the event response phase: When the intelligent control center receives abnormal water quality parameter data sent by the data fusion processor, it activates a three-level alarm, sends the abnormal water quality parameter data to the cloud monitoring system, and sends a warning instruction to the sound and light alarm device, which sounds an alarm. It also sends an aeration emergency processing instruction to the dual-mode aeration system, which turns on the supersaturated dissolved oxygen mode for emergency oxygenation treatment and automatically switches the aeration mode according to the real-time dissolved oxygen value. It also sends a medication emergency processing instruction to the intelligent drug decision-making system, which dynamically calculates the dosage of the drug according to the water quality parameters and administers the drug to improve the water quality.

[0039] Energy management strategy steps: Based on the real-time power demand of electrical equipment, the electricity generated by solar energy and wind energy, the electricity generated by lithium battery packs and supercapacitor packs are intelligently allocated to electrical equipment. When the electricity generated by dual-axis tracking solar panels and vertical axis wind turbines is not consumed in real time, the excess electricity is stored in the lithium battery packs; during the night time period, the intelligent control center sends low-power instructions to the autonomous navigation system, multi-parameter water quality detection system, dual-mode aeration system, intelligent drug decision-making system, self-inspection and maintenance system and sound and light alarm device respectively, so that they enter low-power mode; when the power of the lithium battery pack is lower than the preset power value, the intelligent control center sends a return instruction to the autonomous navigation system, and the autonomous navigation system controls the multi-target path planning module to use the improved A* algorithm and combine the grid map to plan the return path for return.

[0040] The beneficial effects of the present invention are as follows:

[0041] The present invention provides a multimodal perception unmanned operation platform for improving the water quality of rivers and lakes, comprising an intelligent control center and an autonomous navigation system, a multi-parameter water quality detection system, a dual-mode aeration system and an intelligent drug decision-making system all connected to the intelligent control center. The intelligent control center is used to receive and process data from each system, generate control instructions to coordinate the operation of each system, and realize real-time data interaction and collaborative control of multiple modules by integrating the autonomous navigation system, the multi-parameter water quality detection system, the dual-mode aeration system and the intelligent drug decision-making system, ensuring the automated execution of the entire process of inspection, detection and emergency response. From full-dimensional water quality detection, autonomous navigation operation, dual-mode precise aeration to on-demand drug delivery, an efficient, integrated and collaboratively operated water quality improvement system is formed, which can comprehensively and accurately monitor and improve the water quality of rivers and lakes, effectively improve the water quality of rivers and lakes, and improve the ecological environment of water bodies.

[0042] The intelligent control center receives and processes large amounts of data from various systems, generates precise control instructions, and achieves effective coordination of the autonomous navigation system, multi-parameter water quality detection system, dual-mode aeration system and intelligent drug decision-making system, ensuring the collaborative work between various systems, enabling the entire operation platform to achieve intelligent operation, and improving the operating efficiency and stability of the entire operation platform; in the inspection operation stage, based on the water quality detection needs, combined with the water quality parameters of the multi-parameter water quality detection system and the position and path information of the autonomous navigation system, the water quality detection sampling points and the navigation path of the unmanned operation platform are accurately coordinated, making the water quality detection work more orderly and efficient, and ensuring the acquisition of comprehensive and accurate water quality data; in the event response stage, based on the real-time abnormal data of the multi-parameter water quality detection system, the working mode of the dual-mode aeration system is intelligently determined, and the dual-mode aeration system and the intelligent drug decision-making system are coordinated to carry out corresponding processing, which can quickly and accurately respond to abnormal water quality conditions and improve water quality in a timely manner.

[0043] The autonomous navigation system includes a laser SLAM module, an environmental modeling module, an RTK-GNSS positioning module, a multi-target path planning module, an obstacle avoidance control module and a dynamic heading correction module connected in sequence. The environmental modeling module can use the RTK-GNSS positioning module to accurately locate the position of the unmanned operation platform in the river and lake area by satellite, and use the obstacle information transmitted in real time by the laser SLAM module, and match it with the pre-acquired satellite map of the river and lake area to accurately locate the global posture, generate a raster map of the operating waters including static obstacles and dynamic obstacles, and apply the preset navigation path to the raster map. Laser SLAM technology can achieve high-precision map construction and positioning functions, with a positioning error of no more than 5 cm (95% confidence interval), which means that in 95% of cases, the unmanned operation platform can determine its own position with an error accuracy of no more than 5 cm, which improves the navigation of the unmanned operation platform in complex environments. Accuracy and obstacle avoidance capability; during the inspection operation stage, when the information that an obstacle is detected on the preset navigation path is received from the laser SLAM module, the multi-target path planning module automatically plans the optimal temporary obstacle avoidance path by introducing the improved A* algorithm that takes into account energy consumption cost and pollution level in combination with the grid map, and the obstacle avoidance control module generates a heading control instruction according to the temporary obstacle avoidance path, so as to realize the automatic avoidance of obstacles by the unmanned operation platform; after the unmanned operation platform completes obstacle avoidance, it automatically guides it to return to the preset navigation path by comparing the deviation between the real-time positioning data provided by the RTK-GNSS positioning module and the preset navigation path, and continues to inspect the water quality of rivers and lakes according to the preset path, realizing the autonomous navigation of the unmanned operation platform in river and lake waters, solving the problems that traditional operation devices cannot operate autonomously for a long time in complex environments and the efficiency of single-point operations is low, and improving the navigation accuracy and obstacle avoidance capability of the unmanned operation platform in complex environments.

[0044] The multi-parameter water quality detection system includes a multimodal sensor array consisting of a spectrometer, electrochemical sensors, and COD sensors, as well as an interconnected IoT communication module and data fusion processor. The spectrometer can detect dissolved organic matter, inorganic matter, heavy metals, transparency, and turbidity in river and lake water. The electrochemical sensors, including an NH3-N detection electrode, a dissolved oxygen sensor, and a pH sensor, can detect NH3-N, dissolved oxygen, and pH in river and lake water. The COD sensor can detect COD in river and lake water. This multimodal sensor array can enhance the unmanned operation platform's comprehensive perception of complex river and lake water environments and achieve real-time monitoring of all-dimensional water quality parameters. The data fusion processor can receive water quality parameters detected by each device in the multimodal sensor array through the IoT communication module, conduct a comprehensive analysis of the water quality parameters to assess the current water quality, and use a lightweight trend prediction model to assess water quality trends. The water quality parameters and assessment results are transmitted to the intelligent control center to achieve real-time monitoring of water quality parameters and timely emergency response when water quality anomalies occur, solving the problem of delayed response of traditional equipment.

[0045] The dual-mode aeration system includes a nano-aeration tube array, a double-helix gas-liquid mixing chamber, an oxygen booster tank, an air compressor, and a variable frequency drive module. The variable frequency drive module, air compressor, and nano-aeration tube array are connected in sequence. The oxygen booster tank, double-helix gas-liquid mixing chamber, and nano-aeration tube array are connected in sequence. During the event response phase, the dual-mode aeration system can execute the working mode intelligently determined by the intelligent control center and perform aeration treatment based on the real-time detection value of the dissolved oxygen parameter in the river and lake water provided by the dissolved oxygen sensor in the multi-parameter water quality detection system. In the microporous aeration mode, the variable frequency drive module receives control instructions from the intelligent control center to dynamically adjust the input driving force, driving the air compressor to deliver air to the nano-aeration tube array to release bubbles into the river and lake water for conventional oxygenation treatment. In the supersaturated dissolved oxygen mode, the oxygen booster tank injects pure oxygen into the double-helix gas-liquid mixing chamber to mix the river and lake water with oxygen, dissolving the oxygen into the water, and then delivering it to the nano-aeration tube array to oxygenate the river and lake water at full flow, increasing the oxygen dissolution efficiency and achieving emergency oxygenation treatment. The intelligent dual-mode aeration mechanism solves the problem of low oxygenation efficiency of traditional equipment, achieves precise aeration, and improves operational efficiency.

[0046] The intelligent drug decision-making system includes a drug storage module, an adaptive drug dosing calculation module, a three-dimensional spraying module, a multi-degree-of-freedom robotic arm and a controllable vortex nozzle. The adaptive drug dosing calculation module can dynamically calculate the required drug dosage based on water quality parameters using an adaptive drug dosing algorithm. The intelligent control center sends control execution instructions to the three-dimensional spraying module and the multi-degree-of-freedom robotic arm according to the calculation results. The three-dimensional spraying module, which is respectively connected to the drug storage module and the controllable vortex nozzle, controls the controllable vortex nozzle according to the instructions to release the liquid drug stored in the drug storage module into the river and lake water according to the calculated dosage. The multi-degree-of-freedom robotic arm carries out solid drug delivery according to the instructions. The mechanism of dynamically calculating the drug dosage based on water quality parameters can solve the problem of inaccurate drug delivery of traditional equipment and realize on-demand drug delivery. It can not only quickly respond to serious pollution situations, but also avoid waste caused by excessive use of drugs, improve work efficiency and save drug costs.

[0047] The unmanned operation platform of the present invention also includes a composite energy system connected to an intelligent control center. The composite energy system includes a dual-axis tracking solar panel, a vertical-axis wind turbine, an MPPT controller, an AC / DC converter, a lithium battery pack, a supercapacitor pack, and an intelligent power distribution module. The MPPT controller is respectively connected to the dual-axis tracking solar panel and the lithium battery pack, and can control the maximum power point tracking of the dual-axis tracking solar panel to achieve efficient power generation of the dual-axis tracking solar panel, and can stably output the electric energy generated by the dual-axis tracking solar panel to the electrical equipment or lithium battery pack. The AC / DC converter is respectively connected to the vertical-axis wind turbine and the lithium battery pack, and can convert the electric energy generated by the vertical-axis wind turbine into direct current and stably output it to the electrical equipment or the lithium battery pack, which can extend the operation time of the unmanned operation platform and solve the problem that traditional equipment cannot provide continuous power supply at night / rainy weather. The intelligent power distribution module is connected to the MPPT controller, AC / DC converter, lithium battery pack and supercapacitor pack respectively. It intelligently distributes power to the power-consuming equipment based on the real-time power demand and priority of each power-consuming equipment and the power status of the lithium battery pack and supercapacitor pack, realizing efficient energy management and thereby improving the continuous operation time of the unmanned operation platform.

[0048] The unmanned operation platform of the present invention also includes a cloud monitoring system, an audible and visual alarm device, and a self-inspection and maintenance system, all of which are connected to the intelligent control center. The cloud monitoring system can receive data uploaded in real time by the intelligent control center through LoRa / 5G dual-mode communication to achieve remote monitoring. The audible and visual alarm device can receive alarm instructions from the intelligent control center and sound an alarm to remind on-site patrol personnel in river and lake water areas that there are abnormal conditions. The self-inspection and maintenance system is used to receive OTA remote upgrade instructions and perform software upgrades on the intelligent control center. The software system can be remotely upgraded as needed. The operation is simple and convenient. During the initialization phase of the unmanned operation platform, self-inspection request data is sent to the intelligent control center, and the intelligent control center distributes self-inspection instructions to each system for sensor detection. If a sensor fault is found, the intelligent control center uploads the fault information to the cloud monitoring system to remind remote monitoring personnel to repair the equipment. Daily scheduled self-inspections can promptly detect damaged equipment, so that it can be replaced or repaired in time without affecting the patrol operations in river and lake water areas.

[0049] The double-helix gas-liquid mixing chamber of the present invention has a swirl angle of 15 degrees ± 2 degrees, and the inner wall ceramic coating is 80 μm thick, effectively improving the gas-liquid mixing efficiency. At the same time, the ceramic coating can enhance the wear resistance and corrosion resistance of the device. The nano-aeration tube array has a pore size distribution of 25 μm to 45 μm, with a porosity greater than or equal to 82%. The release of bubbles through the tiny pores can significantly improve the dissolution efficiency of oxygen, which is suitable for the needs of efficient oxygenation. The variable frequency drive module dynamically adjusts the power of the air compressor according to the real-time detection value of the dissolved oxygen parameter in the river and lake water. The power adjustment range is 0.5 kW to 3 kW, with an accuracy of ± 2%, which can achieve precise aeration control.

[0050] The medicine storage module of the present invention is equipped with a heating device, adopts a partitioned heating cabin, and controls the temperature at 45°C±3°C, which can prevent the medicine from crystallizing at low temperatures and ensure the activity and fluidity of the medicine; a vibrator is installed in the medicine delivery pipeline to prevent the medicine from being blocked by periodic vibration, thereby ensuring the normal operation of the intelligent medicine decision-making system; the controllable vortex nozzle is made of titanium alloy material, which has excellent corrosion resistance, can extend the service life of the nozzle, and ensure the accuracy of medicine delivery.

[0051] The adaptive dosing calculation module of the intelligent drug decision-making system of the present invention dynamically calculates the dosage of the drug according to the water quality index of the river and lake water, and releases the drug into the river and lake water. The water quality index is obtained by weighted calculation of parameters such as chemical oxygen demand, NH3-N, pH value, turbidity, and dissolved oxygen, which can accurately reflect the water quality of the river and lake water. Then, the dosage of the drug is dynamically adjusted according to the water quality index, which can achieve on-demand drug administration without wasting drugs.

[0052] The intelligent power distribution module of the composite energy system of the present invention determines the energy distribution plan based on the total power demand of the unmanned operation platform. If the total power generation of solar energy and wind energy meets the total power demand, the unmanned operation platform will give priority to using the electricity generated by solar energy and wind energy, and store the unconsumed electricity generated by solar energy and wind energy in the lithium battery pack. If the total power generation of solar energy and wind energy cannot meet the total power demand, the unmanned operation platform will use a mixed power supply mode of electricity generated by solar energy and wind energy, lithium battery pack, and supercapacitor pack, and supply power according to the preset priority order of the power-consuming equipment. In this way, efficient and stable operation can be achieved under different environmental conditions, solving the problem of low operating efficiency of traditional equipment and the inability to achieve long-term autonomous operation in complex environments.

[0053] This paper adopts an improved A* algorithm for path planning, introduces energy consumption cost factors and pollution level factors into path planning, and uses a weighted method to form an improved cost function with distance. Compared with the traditional A* algorithm path planning mainly based on distance, this weighted method enables path planning to consider not only the shortest distance, but also energy consumption and pollution level, thereby achieving optimal path selection in complex environments.

[0054] The present invention also relates to an intelligent decision-making method for a multimodal sensing unmanned operation platform for improving the water quality of rivers and lakes. Intelligent decision-making is made for the work of the above-mentioned multimodal sensing unmanned operation platform for improving the water quality of rivers and lakes, including initialization stage steps, inspection operation stage steps, event response stage steps and energy management strategy steps. By autonomous cruising and using a multimodal sensing sensor array to collect multiple water quality parameters during the cruising stage, real-time monitoring of water quality parameters is achieved; through the real-time obstacle recognition, automatic avoidance, and automatic return to the preset navigation path of the autonomous navigation system, the navigation accuracy and obstacle avoidance capability in complex environments are significantly improved, and the problem of limited operation of traditional equipment in complex waters is solved; through the automatic switching aeration mode mechanism of the dual-mode aeration system and the dynamic calculation of the agent dosage mechanism according to the water quality parameters by the intelligent agent decision-making system, the problems of low oxygenation efficiency and inaccurate agent delivery of the traditional method are effectively solved; through solar energy and wind energy, combined with an intelligent distribution strategy, the problem of the traditional method being unable to provide continuous power supply at night or in rainy weather is solved, and long-term autonomous operation in complex environments is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a diagram of the preferred architecture of the multimodal perception unmanned operation platform for improving river and lake water quality of the present invention.

[0056] Figure 2 This is a preferred structural diagram of the autonomous navigation system of the present invention.

[0057] Figure 3 This is a flow chart of the path planning algorithm of the present invention.

[0058] Figure 4 This is a preferred structural diagram of the multi-parameter water quality detection system of the present invention.

[0059] Figure 5 This is a preferred structural diagram of the dual-mode aeration system of the present invention.

[0060] Figure 6 This is a preferred structural diagram of the intelligent drug decision-making system of the present invention.

[0061] Figure 7 This is a diagram of the preferred structure of the composite energy system of the present invention.

[0062] Figure 8 This is the preferred energy management circuit topology diagram of the present invention.

[0063] Figure 9 This is a flow chart of the intelligent decision-making method of the multimodal perception unmanned operation platform for improving river and lake water quality of the present invention. DETAILED DESCRIPTION

[0064] The present invention will be described below with reference to the accompanying drawings.

[0065] The present invention discloses a multi-modal sensing unmanned operation platform for improving river and lake water quality. The unmanned operation platform can automatically complete obstacle avoidance and autonomous navigation in river and lake waters, conduct real-time monitoring of water quality parameters in all dimensions, and perform precise aeration and on-demand drug administration when water quality parameters are abnormal. The efficient integrated collaborative operation of the dual-mode precise aeration and on-demand drug administration mechanism can effectively improve the effect and efficiency of river and lake water quality improvement. Specifically, Figure 1 As shown, the unmanned operation platform includes an intelligent control center and an autonomous navigation system connected to the intelligent control center, a multi-parameter water quality detection system, a dual-mode aeration system, an intelligent drug decision-making system, a self-inspection and maintenance system, a composite energy system, a cloud monitoring system and an audio-visual alarm device. Among them, the autonomous navigation system includes a laser SLAM module, an environmental modeling module, an RTK-GNSS positioning module, a multi-target path planning module, an obstacle avoidance control module and a dynamic heading correction module; the multi-parameter water quality detection system includes a spectrometer, an electrochemical sensor, a COD sensor, an Internet of Things communication module and data fusion processor; the dual-mode aeration system includes a nano aeration tube array, a double-helix gas-liquid mixing chamber, an oxygen booster tank, an air compressor and a variable frequency drive module; the intelligent drug decision-making system includes a drug storage module, an adaptive dosing calculation module, a three-dimensional spraying module, a multi-degree-of-freedom robotic arm and a controllable vortex nozzle; the composite energy system includes a dual-axis tracking solar panel, a vertical axis wind turbine, an MPPT controller, an AC / DC converter, a lithium battery pack, a supercapacitor pack and an intelligent power distribution module; the cloud monitoring system is connected to the intelligent control center via LoRa / 5G dual-mode communication.

[0066] Specifically, the intelligent control center can receive and process data from each system or module connected to it, and generate control instructions to coordinate the operation of each system or module. For example, in the inspection operation stage, it receives the water quality parameters of river and lake water transmitted by the multi-parameter water quality detection system and the location and path information of the autonomous navigation system. Based on the water quality detection requirements, it analyzes the data and coordinates the multi-parameter water quality detection system to conduct water quality detection at the sampling points on the preset navigation path to realize automatic detection of water quality parameters. At the same time, it receives the preset or temporary obstacle avoidance path information generated by the autonomous navigation system and sends control execution instructions to drive the autonomous navigation system to navigate according to the preset navigation path to realize autonomous navigation operation; in the event response stage, based on the real-time abnormal data of the multi-parameter water quality detection system, it intelligently determines the working mode of the dual-mode aeration system, and sends corresponding control instructions to the dual-mode aeration system and the intelligent agent decision-making system to coordinate the two to perform aeration treatment and agent delivery, thereby improving the effect and efficiency of river and lake water quality improvement.

[0067] The autonomous navigation system of the embodiment of the present invention is used to ensure the autonomous navigation of unmanned operation platforms in river and lake waters, such as Figure 2 As shown, it includes a laser SLAM module, an environment modeling module, an RTK-GNSS positioning module, a multi-target path planning module, an obstacle avoidance control module and a dynamic heading correction module connected in sequence; the laser SLAM module can measure the distance and direction of surrounding objects through the laser radar, identify obstacles in real time, and pass the identified obstacle information to the environment modeling module and the multi-target path planning module; the environment modeling module can build a raster map of the operating water area based on the pre-acquired satellite map of the river and lake area and the obstacle information transmitted in real time by the laser SLAM module; the RTK-GNSS positioning module can provide centimeter-level positioning function; the multi-target path planning module is used in the inspection operation stage of the unmanned operation platform. When the optical SLAM module transmits information that an obstacle is detected on the preset navigation path, it automatically plans the optimal temporary obstacle avoidance path by introducing the improved A* algorithm that takes into account energy consumption cost and pollution level and combines it with the grid map, and sends the temporary obstacle avoidance path information to the intelligent control center; the obstacle avoidance control module receives the control execution instructions from the intelligent control center, generates heading control instructions based on the temporary obstacle avoidance path, and controls the navigation direction of the unmanned operation platform; the dynamic heading correction module receives the control execution instructions from the intelligent control center, and after the unmanned operation platform completes obstacle avoidance, it automatically guides it to return to the preset navigation path by comparing the deviation between the real-time positioning data provided by the RTK-GNSS positioning module and the preset navigation path, so as to continue to perform the inspection operation task.

[0068] Preferably, the improved A* algorithm introduces energy consumption cost factor and pollution level factor in path planning, and the improved cost function is:

[0069] cost=0.7×distance+0.2×energy_consumption+0.1×pollution_level

[0070] Among them, distance represents the distance between the unmanned work platform and the obstacle, which can be obtained through the laser SLAM module. Energy_consumption represents the energy consumption cost, that is, the total energy power required by the unmanned work platform. Pollution_level represents the pollution level of rivers and lakes in the work area. Cost represents the comprehensive cost of executing a certain path. The cost is obtained by weighted summing distance, energy consumption cost energy_consumption, and pollution level pollution_level according to different weights to evaluate the advantages and disadvantages of different path planning schemes.

[0071] Furthermore, if Figure 3 As shown, the intelligent control center of the unmanned operation platform of an embodiment of the present invention receives the current satellite positioning information obtained by the RTK-GNSS positioning module in the initialization stage, and determines the starting point position in combination with the preset navigation path; during the navigation process of the unmanned operation platform (inspection operation stage), when the multi-target path planning module receives the information transmitted by the laser SLAM module that obstacles (such as floating objects, other ships, etc.) are detected on the preset navigation path, it uses the rapid exploration random tree (RRT) algorithm in combination with the grid map to generate multiple candidate obstacle avoidance paths, and then selects the optimal candidate obstacle avoidance path as a temporary obstacle avoidance path by introducing the improved A* algorithm with energy consumption cost and pollution level, and uses the temporary obstacle avoidance path as the navigation path to avoid obstacles. After completing obstacle avoidance and the inspection task is not completed, the dynamic heading correction module compares the deviation between the real-time positioning data provided by the RTK-GNSS positioning module and the preset navigation path. If the deviation distance is greater than 1.5 meters, the heading correction PID controller is activated to perform heading correction and automatically guide it back to the preset navigation path to continue the inspection task. Finally, the intelligent control center generates a navigation log report and sends it to the cloud monitoring system for backup.

[0072] The multi-parameter water quality detection system of the embodiment of the present invention is used to perform multi-modal sensing detection of water quality parameters of rivers and lakes according to sampling points on a preset navigation path through the coordination of the intelligent control center during the inspection operation phase, such as Figure 4As shown, it includes a multimodal sensing sensor array consisting of a spectrum analyzer, an electrochemical sensor and a COD sensor, as well as an interconnected Internet of Things communication module and a data fusion processor, wherein the spectrum analyzer can detect dissolved organic matter, inorganic matter, heavy metals, transparency and turbidity in river and lake water, the electrochemical sensor includes an NH3-N detection electrode, a dissolved oxygen sensor and a pH sensor, the NH3-N detection electrode can detect NH3-N (ammonia nitrogen) in river and lake water, the dissolved oxygen sensor can detect dissolved oxygen in river and lake water, the pH sensor can detect the pH value in river and lake water, and the COD sensor can detect COD (chemical oxygen demand) in river and lake water. The Internet of Things communication module is respectively connected to each part of the multimodal sensing array, and is used to transmit the water quality parameters detected by the spectrum analyzer, electrochemical sensor and COD sensor to the data fusion processor. The data fusion processor can perform a comprehensive analysis on the received water quality parameters, evaluate the current water quality, and use a lightweight trend prediction model to evaluate the water quality change trend based on the water quality parameters received multiple times, and transmit the evaluation results and water quality parameters to the intelligent control center. If abnormal water quality is found, the intelligent control center will upload the abnormal data to the cloud monitoring system, so that supervisors can know the time and area of water quality changes in a timely manner, and send alarm instructions to the sound and light alarm device to control it to sound the alarm, reminding on-site personnel of abnormal water quality. It realizes real-time monitoring of water quality parameters and intelligent early warning, and solves the problem of delayed response of traditional equipment.

[0073] Furthermore, the multi-parameter water quality detection system uses electrochemical sensors and COD sensors to detect water quality parameters in river and lake areas every 15 minutes according to the detection instructions of the intelligent control center, and uses a spectrometer analyzer to perform spectral analysis of the operating waters every 2 hours to obtain full-dimensional water quality parameters.

[0074] The dual-mode aeration system is used to execute the working mode determined by the intelligent control center and perform aeration treatment according to the real-time detection value of dissolved oxygen parameters in river and lake water provided by the dissolved oxygen sensor in the multi-parameter water quality detection system during the event response phase. When the detection value is between the first threshold and the second threshold, the microporous aeration mode is executed, and when the detection value is lower than the first threshold, the supersaturated dissolved oxygen mode is executed. Figure 5As shown, the dual-mode aeration system includes a nano-aeration tube array, a double-helix gas-liquid mixing chamber, an oxygen booster tank, an air compressor, and a variable frequency drive module. The variable frequency drive module, air compressor, and nano-aeration tube array are connected in sequence, and the oxygen booster tank, double-helix gas-liquid mixing chamber, and nano-aeration tube array are connected in sequence. In the microporous aeration mode, the variable frequency drive module receives control instructions from the intelligent control center to dynamically adjust the input driving force, driving the air compressor to deliver air to the nano-aeration tube array. The nano-aeration tube array is a structure composed of a number of aeration tubes with nanometer-scale micro-pores, which then release bubbles into the river and lake water through the micro-pores. In the supersaturated dissolved oxygen mode, the oxygen booster tank is opened to inject pure oxygen into the double-helix gas-liquid mixing chamber. The double-helix gas-liquid mixing chamber is a cavity with a double-helix structure inside and is connected to the river and lake water. The water in the river and lake in the cavity and the pure oxygen injected by the oxygen booster tank are mixed under the guidance of the double-helix structure. The mixed gas and liquid are then delivered to the nano-aeration tube array and released into the river and lake water through the nano-aeration tube array. The double helix structure mainly plays the role of guiding and promoting gas-liquid mixing. After the pure oxygen injected by the oxygen booster tank and the water from the rivers and lakes in the cavity enter the mixing chamber at the same time, they flow along the spiral path under the guidance of the double helix structure. This can increase the contact area and contact time between the gas and liquid, so that the pure oxygen can be better dispersed in the liquid, thereby achieving efficient gas-liquid mixing.

[0075] Preferably, the intelligent control center controls the flow rate of bubbles released by the nano-aeration tube array based on the dissolved oxygen (DO) value monitored by the multi-parameter water quality detection system: when the DO value is less than or equal to 2.0 mg / L (preferably the first threshold value) (emergency mode), the supersaturated DO mode is automatically activated, and the nano-aeration tube array releases bubbles at 100% flow rate, rapidly increasing the dissolved oxygen level in the water. When the DO value is greater than 2.0 mg / L (preferably the first threshold value) and less than 4.0 mg / L (preferably the second threshold value) (normal mode), the microporous aeration mode is automatically activated or switched to microporous aeration mode, and the flow rate of bubbles released by the nano-aeration tube array is controlled based on the ratio of the DO value to 4.0 mg / L, that is, the aeration rate is dynamically adjusted according to the DO value. For example, when the DO value is 3.0 mg / L, the aeration rate is adjusted to 50%.

[0076] Preferably, the swirl angle of the double-helix gas-liquid mixing chamber is 15 degrees ± 2 degrees, and the thickness of the inner wall ceramic coating is 80 μm, which effectively improves the gas-liquid mixing efficiency. At the same time, the ceramic coating can enhance the wear resistance and corrosion resistance of the device; the pore size distribution of the nano aeration tube array is 25 μm to 45 μm, and the porosity is greater than or equal to 82%. The release of bubbles through tiny pores can significantly improve the dissolution efficiency of oxygen, which is suitable for efficient oxygenation needs; the frequency conversion drive module dynamically adjusts the power of the air compressor according to the real-time detection value of the dissolved oxygen parameter in river and lake water. The power adjustment range is 0.5kW to 3kW, and the accuracy is ±2%, which can achieve precise aeration control.

[0077] The intelligent drug decision-making system of the embodiment of the present invention is used to dynamically calculate the amount of drug to be added based on the water quality parameters of rivers and lakes (including dissolved organic matter, inorganic matter, heavy metals, transparency, turbidity, dissolved oxygen, NH3-N, pH value, COD, etc.) provided by the multi-parameter water quality detection system, and to add drugs to the river and lake water. Figure 6 As shown, it includes a drug storage module, an adaptive dosing calculation module, a three-dimensional spraying module, a multi-degree-of-freedom robotic arm, a controllable vortex nozzle and a drug delivery pipeline. The adaptive dosing calculation module receives water quality parameters transmitted by the multi-parameter water quality detection system, dynamically calculates the required drug dosage based on the adaptive dosing algorithm, generates dosing control instructions, and sends the calculation results and dosing control instructions to the intelligent control center. After analysis and processing, the intelligent control center sends control execution instructions to the three-dimensional spraying module and the multi-degree-of-freedom robotic arm; the three-dimensional spraying module is connected to the drug storage module through a drug delivery pipeline, and the three-dimensional spraying module is also connected to the controllable vortex nozzle. According to the instructions of the intelligent control center, the controllable vortex nozzle is controlled to release the liquid drug stored in the drug storage module into the river and lake water according to the calculated dosage; the multi-degree-of-freedom robotic arm performs solid drug delivery according to the instructions of the intelligent control center.

[0078] Furthermore, when the unmanned operation platform is improving the water quality in the area with abnormal water quality, the multi-target path planning module of the autonomous navigation system automatically plans a water quality improvement operation path in the area with abnormal water quality, such as within a radius of 50 meters, based on the water quality improvement instructions received from the intelligent control center, and sends the water quality improvement operation path information to the intelligent control center. The obstacle avoidance control module receives the control execution instructions from the intelligent control center, generates a heading control instruction according to the water quality improvement operation path, and controls the unmanned operation platform to automatically navigate in the area with abnormal water quality. Then, the dual-mode aeration system and the intelligent agent decision-making system perform aeration and drug treatment (such as adding nitrifying agents) to improve the water quality in the operation area.

[0079] Preferably, in order to ensure the stability and reliability of the intelligent drug decision-making system, the following three-proof design is adopted: First, the drug storage module is equipped with a heating device, a partitioned heating cabin is used, and the temperature is controlled at 45℃±3℃, which can prevent the drug from crystallizing at low temperatures to ensure the activity and fluidity of the drug; Second, a vibrator is installed in the drug delivery pipeline, and periodic vibration is used to prevent the drug from precipitating and clogging in the pipeline to ensure the normal operation of the intelligent drug decision-making system; Third, the controllable vortex nozzle is made of titanium alloy material, which has excellent corrosion resistance, can extend the service life of the nozzle, and ensure the accuracy of drug delivery.

[0080] The adaptive dosing calculation module of the embodiment of the present invention first determines the water quality index based on the water quality parameters transmitted by the multi-parameter water quality detection system, then calculates the required dosage of the agent based on the interval rule of the water quality index, and generates the corresponding dosing control instruction: wherein, the calculation formula of the water quality index is as follows:

[0081] WQI=0.25×COD+0.28×NH3-N+0.22×pH+0.15×Turbidity+0.1×DO

[0082] Wherein, WQI represents water quality index, COD represents chemical oxygen demand parameter, NH3-N represents NH3-N parameter, pH represents pH parameter, Turbidity represents turbidity parameter, and DO represents dissolved oxygen parameter;

[0083] When WQI is greater than 100 (severe pollution), calculate the dosage according to the following formula:

[0084] total=5e^0.02×(WQI-100)

[0085] Where total represents the dosage, in liters per square kilometer; that is, a dosage of 5 liters per square kilometer is multiplied by the exponential function e^0.02×(WQI-100). As the WQI increases, the dosage increases exponentially to quickly respond to severe pollution.

[0086] When WQI is greater than 80 and WQI is less than or equal to 100 (moderate pollution), the dosage is 3 liters / km2 to stabilize the water quality problem;

[0087] When WQI is less than or equal to 80 (mild pollution), the dosage is 1 liter / square kilometer. Keep the dosage low to avoid excessive use of the drug.

[0088] Furthermore, the weight values of each water quality parameter in the calculation formula of the water quality index are determined based on experience and can be adjusted later according to needs.

[0089] The composite energy system of the embodiment of the present invention is used for intelligent distribution and management of energy, such as Figure 7 As shown, the hybrid energy system includes dual-axis tracking solar panels, vertical axis wind turbines, MPPT controllers, AC / DC converters, lithium battery packs (such as 48V 100Ah), supercapacitor group (such as 500F), intelligent power distribution module, the MPPT controller is respectively connected to the dual-axis tracking solar panel and the lithium battery group, and is used to control the maximum power point tracking of the dual-axis tracking solar panel and stably output the electric energy generated by the dual-axis tracking solar panel to the power consumption equipment or the lithium battery group. The power consumption equipment is the components involving power consumption in the autonomous navigation system, the multi-parameter water quality detection system, the dual-mode aeration system and the intelligent pharmaceutical decision-making system. The AC / DC converter is respectively connected to the vertical axis wind turbine and the lithium battery group, and is used to convert the electric energy generated by the vertical axis wind turbine into direct current and stably output it to the power consumption equipment or the lithium battery group. The supercapacitor group is used to provide rapid power transmission to power consumption equipment with instantaneous high power demand. The intelligent power distribution module is respectively connected to the MPPT controller, AC / DC converter, lithium battery group and supercapacitor group, and is used to intelligently distribute power to the power consumption equipment according to the real-time power demand and priority of each power consumption equipment and the power status of the lithium battery group and supercapacitor group.

[0090] Dual-axis tracking solar panels and vertical axis wind turbines can generate electricity through solar energy and wind power, solving the problem that traditional equipment cannot provide continuous power supply at night or in rainy weather. The MPPT controller is used to control the maximum power point tracking of the dual-axis tracking solar panels and stably output the electricity generated by the dual-axis tracking solar panels to the power consumption equipment or lithium battery pack. The AC / DC converter is used to convert the AC power generated by the vertical axis wind turbine into DC power and stably output it to the power consumption equipment or lithium battery pack. The supercapacitor group is used to provide fast power transmission to power consumption equipment with instantaneous high power demand. The intelligent power distribution module can intelligently distribute power sources to power consumption equipment according to the power of the power consumption equipment. The intelligent power distribution module includes a dynamic load distributor, such as Figure 8 As shown, the dynamic load distributor supplies power to the intelligent drug decision-making system and the dual-mode aeration system through PWM control, supplies power to the autonomous navigation system through CAN bus voltage regulation, and supplies power to the multi-parameter water quality detection system through isolated power supply.

[0091] Furthermore, if Figure 8The energy management circuit topology shown in the figure shows the energy distribution and management mechanism of the hybrid energy system. In this system, the energy input layer includes dual-axis tracking solar panels (i.e. dual-axis tracking solar panels) and vertical axis wind turbines, which provide electricity through photovoltaic input and wind power input respectively; the electricity output by the dual-axis tracking solar panels is processed by the MPPT controller, and the electricity output by the vertical axis wind turbine is processed by the AC / DC converter and transmitted in the form of DC output; the energy storage system includes a lithium battery pack (48V / 100Ah) and a supercapacitor pack (500F), with the lithium battery pack serving as the main power supply and the supercapacitor pack used for transient compensation. Intelligent power distribution module of the hybrid energy system (corresponding to Figure 8 The intelligent distribution of power to power-consuming devices (such as intelligent pharmaceutical decision-making systems, dual-mode aeration systems, autonomous navigation systems, multi-parameter water quality detection systems, etc.) includes:

[0092] Calculate the total energy power required by the unmanned operation platform using the following formula:

[0093] P required =P mobility +P aeration +P sensing

[0094] Among them, P required Indicates the total power required for energy, P mobility It represents the total power of the autonomous navigation system, which can be obtained through the navigation propulsion system of the unmanned operation platform. aeration Represents the total power of the dual-mode aeration system, P sensing represents the sum of the total power of the multi-parameter water quality monitoring system and the total power of the intelligent drug decision-making system; if the total amount of electricity generated by the dual-axis tracking solar panels and vertical axis wind turbines (corresponding to Figure 8 P_total in the energy requirement) to meet the total power (corresponding to Figure 8 The intelligent power distribution module allocates the unmanned operation platform to preferentially use the electric energy generated by the dual-axis tracking solar panels and the vertical axis wind turbine, and stores the unconsumed electric energy generated by the dual-axis tracking solar panels and the vertical axis wind turbine in the lithium battery pack;

[0095] If the total amount of electricity generated by the dual-axis tracking solar panels and vertical-axis wind turbines cannot meet the total energy demand, the intelligent power distribution module allocates a mixed power supply mode of electricity generated by the dual-axis tracking solar panels and vertical-axis wind turbines, lithium battery packs, and supercapacitor packs to the unmanned operation platform, and supplies power to the power-consuming equipment according to the preset priority order of the power-consuming equipment (such as the priority order of intelligent drug decision-making system > dual-mode aeration system > autonomous navigation system > multi-parameter water quality detection system);

[0096] Among them, the intelligent power distribution module uses PWM control to supply power to the intelligent drug decision-making system and dual-mode aeration system, uses CAN bus voltage regulation to supply power to the autonomous navigation system, and uses isolated power supply to supply power to the multi-parameter water quality detection system. In addition, Figure 8 The report also outlines a power distribution strategy: supercapacitors are prioritized for responding to transient demand; lithium batteries are used as the primary energy source; and power supply modes are dynamically switched: pure regenerative power supply when P_total ≥ load, and hybrid power supply when P_total < load. This energy management approach ensures that all electrical devices on the unmanned platform receive stable and appropriate power under varying energy supply conditions, ensuring the platform's normal operation.

[0097] The self-check and maintenance system of this embodiment of the present invention is used to receive OTA remote upgrade instructions, perform software upgrades on the intelligent control center, and send self-check request data to the intelligent control center during the initialization phase of the unmanned operation platform. Based on the self-check request data received from the self-check and maintenance system, the intelligent control center sends self-check instructions to the multi-parameter water quality detection system, dual-mode aeration system, intelligent drug decision-making system, composite energy system, and autonomous navigation system to check the status of sensors within each system. If a sensor fails, the intelligent control center promptly sends the fault information to the cloud monitoring system, allowing remote supervisors to promptly detect the sensor failure and perform repairs or replacements.

[0098] The present invention also provides an intelligent decision-making method for a multi-modal sensing unmanned operation platform for improving river and lake water quality, such as Figure 9 As shown, the following steps are included:

[0099] Initialization phase steps: The intelligent control center sends self-test instructions to the multi-parameter water quality detection system, dual-mode aeration system, intelligent drug decision-making system, composite energy system and autonomous navigation system according to the self-test request data of the self-test maintenance system, and performs sensor status checks in each system; the environmental modeling module uses the laser SLAM module to build a local map according to the modeling instructions of the intelligent control center, and matches it with the pre-acquired satellite map of the river and lake area to generate a grid map of the river and lake area including static obstacles and dynamic obstacles (the length and width of the grid can be 0.5m and 0.5m), and applies the preset navigation path to the grid map. The construction of the local map and the improvement of the grid map of the river and lake area will continue as the unmanned operation platform conducts inspections;

[0100] Inspection operation phase steps: During the inspection process, the multi-parameter water quality detection system uses electrochemical sensors and COD sensors to conduct water quality parameter detection (including NH3-N, dissolved oxygen, pH value, chemical oxygen demand, etc.) in the river and lake area every preset collection time (such as 15 minutes) according to the detection instructions of the intelligent control center. The spectrum analyzer is used to perform a spectral analysis of the operating water area every preset spectral analysis time (such as 2 hours) to obtain full-dimensional water quality parameters including dissolved organic matter, inorganic matter, heavy metals, transparency and turbidity, and the obtained water quality parameters are sent to the data fusion processor through the Internet of Things communication module for comprehensive water quality analysis; when the intelligent control center receives data that the laser SLAM module detects an obstacle on the preset navigation path, it sends an avoidance instruction to the autonomous navigation system, and the autonomous navigation system controls the multi-target path planning module, and uses the improved A* algorithm and combined with the grid map to plan the optimal temporary obstacle avoidance path. After the obstacle avoidance is completed, the autonomous navigation system controls the heading to guide the return to the preset navigation path;

[0101] Steps in the event response phase: When the intelligent control center receives abnormal water quality parameter data sent by the data fusion processor, it activates a three-level alarm, sends the abnormal water quality parameter data to the cloud monitoring system, and sends a warning instruction to the sound and light alarm device, which sounds an alarm. It also sends an aeration emergency processing instruction to the dual-mode aeration system, which turns on the supersaturated dissolved oxygen mode for emergency oxygenation treatment and automatically switches the aeration mode according to the real-time dissolved oxygen value. It also sends a medication emergency processing instruction to the intelligent drug decision-making system, which dynamically calculates the dosage of the drug according to the water quality parameters and administers the drug to improve the water quality.

[0102] Energy management strategy steps: According to the real-time power demand of the electrical equipment, the electricity generated by solar energy and wind energy, the electricity generated by lithium battery packs and supercapacitor packs are intelligently allocated to the electrical equipment. When the electricity generated by the dual-axis tracking solar panels and vertical axis wind turbines is not consumed in real time, the excess electricity is stored in the lithium battery pack; during the night time period, the intelligent control center sends low-power instructions to the autonomous navigation system, multi-parameter water quality detection system, dual-mode aeration system, intelligent drug decision-making system, self-inspection and maintenance system and sound and light alarm device respectively, so that they enter low-power mode (standby power consumption is less than or equal to 25W) to reduce energy consumption; when the power of the lithium battery pack is lower than the preset power value (such as the remaining battery power is less than 20% of the total power), the intelligent control center sends a return instruction to the autonomous navigation system, and the autonomous navigation system controls the multi-target path planning module to use the improved A* algorithm and combine the grid map to plan the return path for return.

[0103] The present invention provides a multimodal sensing unmanned operation platform and intelligent decision-making method for improving river and lake water quality. This platform utilizes multimodal sensing technology, combined with intelligent decision-making algorithms and autonomous navigation modules, to achieve real-time monitoring of water quality parameters, precise aeration, on-demand drug delivery, and efficient energy management. This effectively addresses the issues of low operating efficiency and the inability of traditional devices to achieve long-term autonomous operation in complex environments. A dual-mode aeration system and intelligent drug decision-making system improve oxygenation efficiency and drug delivery accuracy. An autonomous navigation module based on an improved A* algorithm and laser SLAM ensures long-term autonomous operation in complex environments. A composite energy system combining coupled tracking solar energy and vertical axis wind turbines ensures continuous power supply to the equipment in various environments.

[0104] It should be noted that the specific embodiments described above can enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although this specification has described the present invention in detail with reference to the drawings and embodiments, those skilled in the art should understand that the present invention can still be modified or replaced with equivalents. In short, all technical solutions and improvements that do not depart from the spirit and scope of the present invention should be included in the scope of protection of the patent for the present invention.

Claims

1. A multimodal sensing unmanned operation platform for improving river and lake water quality, characterized by: It includes an intelligent control center and an autonomous navigation system, a multi-parameter water quality detection system, a dual-mode aeration system and an intelligent drug decision-making system, all of which are connected to the intelligent control center; The intelligent control center is used to receive and process data from various systems and generate control instructions to coordinate the operation of various systems. During the inspection operation phase, it receives water quality parameters of river and lake water transmitted by the multi-parameter water quality detection system and the position and path information of the autonomous navigation system. Based on the water quality detection requirements, it analyzes the data and coordinates the multi-parameter water quality detection system to perform water quality detection at sampling points on the preset navigation path. At the same time, it receives preset or temporary obstacle avoidance path information generated by the autonomous navigation system and sends control execution instructions to drive the autonomous navigation system to navigate along the preset navigation path. During the incident response phase, the system intelligently determines the operating mode of the dual-mode aeration system based on real-time abnormal data from the multi-parameter water quality detection system, and sends corresponding control instructions to the dual-mode aeration system and the intelligent agent decision-making system to coordinate the aeration treatment and agent delivery. The autonomous navigation system is used to ensure the autonomous navigation of the unmanned operating platform in river and lake waters; it includes a laser SLAM module, an environmental modeling module, an RTK-GNSS positioning module, a multi-target path planning module, an obstacle avoidance control module and a dynamic heading correction module connected in sequence, the laser SLAM module is used to measure the distance and direction of surrounding objects through a laser radar, identify obstacles in real time, and transmit the identified obstacle information to the environmental modeling module and the multi-target path planning module; the environmental modeling module is used to construct a raster map of the operating waters based on the pre-acquired satellite map of the river and lake area and the obstacle information transmitted in real time by the laser SLAM module; the RTK-GNSS positioning module is used to provide centimeter-level positioning function; the multi-target path planning The module is used in the inspection operation phase of the unmanned operation platform. When receiving the information transmitted by the laser SLAM module that an obstacle is detected on the preset navigation path, it automatically plans a temporary obstacle avoidance path by introducing the improved A* algorithm based on energy consumption cost and pollution level in combination with the grid map, and sends the temporary obstacle avoidance path information to the intelligent control center; the obstacle avoidance control module receives the control execution instruction of the intelligent control center, generates the heading control instruction according to the temporary obstacle avoidance path, and controls the navigation direction of the unmanned operation platform; the dynamic heading correction module receives the control execution instruction of the intelligent control center, and after the unmanned operation platform completes the obstacle avoidance, it automatically guides it to return to the preset navigation path by comparing the deviation between the real-time positioning data provided by the RTK-GNSS positioning module and the preset navigation path; The multi-parameter water quality detection system is used to perform multimodal sensing detection of water quality parameters of rivers and lakes according to sampling points on a preset navigation path through coordination of an intelligent control center during the inspection operation phase; the multi-parameter water quality detection system includes a multimodal sensing sensor array composed of a spectrometer, an electrochemical sensor and a COD sensor, as well as an interconnected Internet of Things communication module and a data fusion processor, wherein the spectrometer is used to detect dissolved organic matter, inorganic matter, heavy metals, transparency and turbidity in river and lake water; the electrochemical sensor includes an NH3-N detection electrode, a dissolved oxygen sensor and a pH sensor, which are used to detect NH3-N, dissolved oxygen and pH values in river and lake water, and the COD sensor is used to detect COD in river and lake water. The Internet of Things communication module is respectively connected to each part of the multimodal sensing array, and is used to transmit the water quality parameters detected by the spectrometer, electrochemical sensor and COD sensor to the data fusion processor, and the data fusion processor is used to comprehensively analyze the water quality parameters, evaluate the current water quality, and use a lightweight trend prediction model to evaluate the water quality change trend based on the water quality parameters received multiple times; The dual-mode aeration system is used to execute the working mode of intelligent control center intelligent determination and perform aeration treatment in the event response stage according to the real-time detection value of dissolved oxygen parameters in river and lake water provided by the dissolved oxygen sensor in the multi-parameter water quality detection system. When the detection value is between the first threshold and the second threshold, the microporous aeration mode is executed, and when the detection value is lower than the first threshold, the supersaturated dissolved oxygen mode is executed; the dual-mode aeration system includes a nano aeration tube array, a double-helix gas-liquid mixing chamber, an oxygen booster tank, an air compressor and a variable frequency drive module, the variable frequency drive module, the air compressor and the nano aeration tube array are connected in sequence, and the oxygen booster tank, the double-helix gas-liquid mixing chamber and the nano aeration tube array are connected in sequence; in the microporous aeration mode The variable frequency drive module receives control instructions from the intelligent control center to dynamically adjust the input driving force, driving the air compressor to deliver air to the nano aeration tube array. The nano aeration tube array is a structure composed of several aeration tubes with nano-scale tiny pores, which then release bubbles into the river and lake water through the tiny pores; in the supersaturated dissolved oxygen mode, the oxygen booster tank is opened to inject pure oxygen into the double helix gas-liquid mixing chamber. The double helix gas-liquid mixing chamber is a cavity with a double helix structure inside and is connected to the river and lake water body. The water in the river and lake in the cavity and the pure oxygen injected by the oxygen booster tank are mixed under the guidance of the double helix structure. The mixed gas and liquid are then delivered to the nano aeration tube array and then released into the river and lake water through the nano aeration tube array; The intelligent drug decision-making system is used to dynamically calculate the drug dosage based on the water quality parameters of river and lake water provided by the multi-parameter water quality detection system, and release the drug into the river and lake water; it includes a drug storage module, an adaptive drug dosing calculation module, a three-dimensional spraying module, a multi-degree-of-freedom robotic arm and a controllable vortex nozzle. The adaptive drug dosing calculation module receives the water quality parameters transmitted by the multi-parameter water quality detection system, dynamically calculates the required drug dosage based on the adaptive drug dosing algorithm, generates drug dosing control instructions, and sends the calculation results and drug dosing control instructions to the intelligent control center. After analysis and processing, the intelligent control center sends control execution instructions to the three-dimensional spraying module and the multi-degree-of-freedom robotic arm; the three-dimensional spraying module is respectively connected to the drug storage module and the controllable vortex nozzle, and controls the controllable vortex nozzle according to the instructions of the intelligent control center to release the liquid drug stored in the drug storage module into the river and lake water according to the calculated dosage; the multi-degree-of-freedom robotic arm performs solid drug delivery according to the instructions of the intelligent control center.

2. The multimodal sensing unmanned operation platform for improving river and lake water quality according to claim 1 is characterized in that: It also includes a composite energy system, which is connected to an intelligent control center for intelligent distribution and management of energy; the composite energy system includes a dual-axis tracking solar panel, a vertical axis wind turbine, an MPPT controller, an AC / DC converter, a lithium battery pack, a supercapacitor pack, and an intelligent power distribution module. The MPPT controller is connected to the dual-axis tracking solar panel and the lithium battery pack respectively, and is used to control the maximum power point tracking of the dual-axis tracking solar panel and stably output the electric energy generated by the dual-axis tracking solar panel to the electrical equipment or the lithium battery pack. The electrical equipment is an autonomous navigation system, a multi-parameter water quality detection system, and a dual-mode aeration system. The system and the intelligent drug decision system each involve components involving electricity consumption. The AC / DC converter is respectively connected to the vertical axis wind turbine and the lithium battery pack, and is used to convert the electric energy generated by the vertical axis wind turbine into direct current and stably output it to the electrical equipment or the lithium battery pack. The supercapacitor group is used to provide fast power transmission to electrical equipment with instantaneous high power demand. The intelligent power distribution module is respectively connected to the MPPT controller, AC / DC converter, lithium battery pack and supercapacitor group, and is used to intelligently distribute electricity to the electrical equipment according to the real-time power demand, priority and power status of each electrical equipment of the lithium battery pack and supercapacitor group.

3. The multimodal sensing unmanned operation platform for improving river and lake water quality according to claim 2 is characterized in that: It also includes a cloud monitoring system, an audible and visual alarm device, and a self-checking and maintenance system, all of which are connected to the intelligent control center. The cloud monitoring system is deployed on a cloud server and connected to the intelligent control center via LoRa / 5G dual-mode communication to receive data from the intelligent control center and provide remote monitoring functions; The sound and light alarm device is used to receive the alarm instruction sent by the intelligent control center and issue an alarm; The self-check maintenance system is used to receive OTA remote upgrade instructions, perform software upgrades on the intelligent control center, and send self-check request data to the intelligent control center during the initialization phase of the unmanned operation platform; The intelligent control center sends self-inspection instructions to the multi-parameter water quality detection system, the dual-mode aeration system, the intelligent drug decision-making system, the composite energy system and the autonomous navigation system based on the self-inspection request data received from the self-inspection maintenance system, and performs sensor status checks in each system.

4. The multimodal sensing unmanned operation platform for improving river and lake water quality according to any one of claims 1 to 3, characterized in that: In the dual-mode aeration system, the intelligent control center controls the flow rate of bubbles released by the nano-aeration tube array based on the dissolved oxygen value monitored by the multi-parameter water quality detection system. When the dissolved oxygen value is less than or equal to 2.0 mg / L, the supersaturated dissolved oxygen mode is automatically activated, and the nano-aeration tube array releases bubbles at 100% of the flow rate. When the dissolved oxygen value is greater than 2.0 mg / L and less than 4.0 mg / L, the microporous aeration mode is automatically activated, and the flow rate of bubbles released by the nano-aeration tube array is controlled based on the ratio of the dissolved oxygen value to 4.0 mg / L.

5. The multimodal sensing unmanned operation platform for improving river and lake water quality according to any one of claims 1 to 3, characterized in that: In the dual-mode aeration system, the swirl angle of the double-helix gas-liquid mixing chamber is 15 degrees ± 2 degrees, and the thickness of the inner wall ceramic coating is 80 μm; the pore size distribution of the nano-aeration tube array is 25 μm to 45 μm, and the porosity is greater than or equal to 82%; the variable frequency drive module dynamically adjusts the power of the air compressor based on the real-time detection value of the dissolved oxygen parameter in the river and lake water. The power adjustment range is 0.5 kW to 3 kW, and the accuracy is ± 2%.

6. The multimodal sensing unmanned operation platform for improving river and lake water quality according to any one of claims 1 to 3, characterized in that: In the intelligent drug decision-making system, the drug storage module is equipped with a heating device, adopts a partitioned heating cabin, and controls the temperature at 45°C±3°C to ensure the activity and fluidity of the drug; the intelligent drug decision-making system also includes a drug delivery pipeline, which is used to connect the three-dimensional spraying module and the drug storage module, and is equipped with a vibrator for periodic vibration to prevent the drug from settling and clogging in the pipeline; the controllable vortex nozzle is made of titanium alloy material.

7. The multimodal sensing unmanned operation platform for improving river and lake water quality according to claim 1 is characterized in that: The adaptive dosing calculation module in the intelligent drug decision-making system first determines the water quality index based on the water quality parameters transmitted by the multi-parameter water quality detection system, then calculates the required drug dosage based on the interval rules for determining the water quality index, and generates corresponding drug dosing control instructions; wherein, the calculation formula of the water quality index is as follows: WQI=0.25×COD+0.28×NH3-N+0.22×pH+0.15×Turbidity+0.1×DO Wherein, WQI represents water quality index, COD represents chemical oxygen demand parameter, NH3-N represents NH3-N parameter, pH represents pH parameter, Turbidity represents turbidity parameter, and DO represents dissolved oxygen parameter; When WQI is greater than 100, calculate the dosage according to the following formula: total=5e^0.02×(WQI-100) Among them, total represents the dosage, the unit is liter / square kilometer; When WQI is greater than 80 and WQI is less than or equal to 100, the dosage is 3 liters / km2; When WQI is less than or equal to 80, the dosage is 1 liter / square kilometer.

8. The multimodal sensing unmanned operation platform for improving river and lake water quality according to claim 2 is characterized in that: The intelligent power distribution module of the composite energy system intelligently distributes power to the power-consuming equipment, including: Calculate the total energy power required by the unmanned operation platform using the following formula: P required =P mobility +P aeration +P sensing Among them, P required Indicates the total power required for energy, P mobility Represents the total power of the autonomous navigation system, P aeration Represents the total power of the dual-mode aeration system, P sensing represents the sum of the total power of the multi-parameter water quality monitoring system and the total power of the intelligent drug decision-making system; if the total amount of electricity generated by the dual-axis tracking solar panels and the vertical-axis wind turbine meets the total energy demand, the unmanned operation platform will give priority to using the electricity generated by the dual-axis tracking solar panels and the vertical-axis wind turbine, and store the unconsumed electricity generated by the dual-axis tracking solar panels and the vertical-axis wind turbine in the lithium battery pack; If the total amount of electricity generated by the dual-axis tracking solar panels and vertical-axis wind turbines cannot meet the total energy demand, the unmanned operation platform uses a mixed power supply mode of electricity generated by the dual-axis tracking solar panels and vertical-axis wind turbines, lithium battery packs, and supercapacitor packs, and supplies power to the electrical equipment according to the preset priority order of the electrical equipment.

9. The multimodal sensing unmanned operation platform for improving river and lake water quality according to claim 1 is characterized in that: In the autonomous navigation system, the improved A* algorithm introduces energy consumption cost factor and pollution level factor in path planning. The improved cost function is: cost=0.7×distance+0.2×energy_consumption+0.1×pollution_level Among them, distance represents the distance between the unmanned work platform and the obstacle, which is obtained by the laser SLAM module, energy_consumption represents the energy consumption cost, pollution_level represents the pollution level of rivers and lakes in the work area, and cost represents the comprehensive cost of executing a certain path, which is obtained by weighted summing the distance, energy consumption cost, and pollution level according to different weights to evaluate the advantages and disadvantages of different path planning schemes.

10. An intelligent decision-making method based on the multimodal perception unmanned operation platform for improving river and lake water quality according to any one of claims 3 to 9, characterized in that: The following steps are involved: Initialization phase steps: The intelligent control center sends self-test instructions to the multi-parameter water quality detection system, dual-mode aeration system, intelligent drug decision-making system, composite energy system, and autonomous navigation system based on the self-test request data of the self-test maintenance system to check the status of the sensors within each system; the environmental modeling module uses the laser SLAM module to build a local map based on the modeling instructions of the intelligent control center, and matches it with the pre-acquired satellite map of the river and lake area to generate a raster map of the river and lake area including static and dynamic obstacles, and applies the preset navigation path to the raster map; Inspection operation phase steps: During the inspection process, the multi-parameter water quality detection system uses electrochemical sensors and COD sensors to detect water quality parameters in river and lake areas at preset collection time according to the detection instructions of the intelligent control center. It uses a spectrum analyzer to perform spectral analysis of the operating water area at preset spectral analysis time to obtain full-dimensional water quality parameters, and sends the obtained water quality parameters to the data fusion processor through the Internet of Things communication module for comprehensive water quality analysis; when the intelligent control center receives data that the laser SLAM module detects obstacles on the preset navigation path, it sends avoidance instructions to the autonomous navigation system, and the autonomous navigation system controls the multi-target path planning module, uses the improved A* algorithm and combines the grid map to plan the optimal temporary obstacle avoidance path, and after the obstacle avoidance is completed, the autonomous navigation system controls the heading to guide the system back to the preset navigation path; Steps in the event response phase: When the intelligent control center receives abnormal water quality parameter data sent by the data fusion processor, it activates a three-level alarm, sends the abnormal water quality parameter data to the cloud monitoring system, and sends a warning instruction to the sound and light alarm device, which sounds an alarm. It also sends an aeration emergency processing instruction to the dual-mode aeration system, which turns on the supersaturated dissolved oxygen mode for emergency oxygenation treatment and automatically switches the aeration mode according to the real-time dissolved oxygen value. It also sends a medication emergency processing instruction to the intelligent drug decision-making system, which dynamically calculates the dosage of the drug according to the water quality parameters and administers the drug to improve the water quality. Energy management strategy steps: Based on the real-time power requirements of power-consuming devices, electricity generated by solar and wind power, lithium-ion battery packs, and supercapacitors is intelligently distributed to power-consuming devices. When the electricity generated by dual-axis tracking solar panels and vertical-axis wind turbines is not consumed in real time, the excess electricity is stored in the lithium-ion battery pack. During the nighttime period, the intelligent control center sends low-power instructions to the autonomous navigation system, multi-parameter water quality detection system, dual-mode aeration system, intelligent drug decision-making system, self-inspection and maintenance system, and sound and light alarm device, respectively, to make them enter low-power mode; when the power of the lithium battery pack is lower than the preset power value, the intelligent control center sends a return instruction to the autonomous navigation system, and the autonomous navigation system controls the multi-target path planning module to use the improved A* algorithm and combine the grid map to plan the return path for returning.

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