CN-121990657-A - Algae precise prevention and control system based on air-water cooperative intelligent decision and application thereof

CN121990657ACN 121990657 ACN121990657 ACN 121990657ACN-121990657-A

Abstract

The invention discloses an alga precise prevention and control system based on an air-water cooperative intelligent decision and application thereof. The invention establishes 1) an algae prevention and control zero-delay response system, which is a fusion depth forest inversion model, a GNSS-RTK high-precision positioning module, an algae inhibiting bacteria activation and addition integrated device and a dynamic decision model based on fuzzy rules, and is used for constructing a minute-level quick response system, breaking, prevention and control and response hysteresis difficult problem, 2) a data-driven precise addition system, which is used for realizing fungus agent addition depth self-adaption, concentration field homogenization and eliminating drug effect deficiency, waste and algae inhibiting efficiency attenuation caused by space-time mismatch through dose dynamic optimization and activator structure innovation, and 3) a full-intelligent operation system, which is a double closed-loop structure based on multi-mode obstacle avoidance and remote sensing-execution-evaluation, so as to achieve detection-decision-Shi Cequan link unattended operation, and breaks through the scale deployment bottleneck and environmental adaptation limitation of traditional man-machine coupling.

Inventors

WANG XIAOMIN
WEI YANFEI
JIANG TAO
HUA JUNFENG
ZHU XIAOHANG
QIU ZHENZHEN
DAI CHUHAN
ZHAO MENGFEI
LI YURU
YU TAO

Assignees

浙江省环境科技股份有限公司

Dates

Publication Date: 20260508
Application Date: 20260105

Claims (10)

1. The algae precise prevention and control system based on the air-water cooperative intelligent decision is characterized by comprising an unmanned aerial vehicle hyperspectral water quality inversion and hot spot marking system, an unmanned ship precise dosing and autonomous track control system and a data platform cooperative decision system; The unmanned aerial vehicle hyperspectral water quality inversion and hot spot marking system comprises an unmanned aerial vehicle, a hyperspectral water quality inversion system and a first hot spot marking system, wherein the hyperspectral water quality inversion system and the first hot spot marking system are carried on the unmanned aerial vehicle; the unmanned aerial vehicle hyperspectral water quality inversion and hot spot marking system comprises the following steps that an unmanned aerial vehicle is used for inspecting a specified water area along a preset route, the concentration of chlorophyll a is inverted in real time by utilizing a hyperspectral water quality inversion system, when the inverted concentration of chlorophyll a exceeds a preset threshold value, a first hot spot marking system records coordinates of risk points, generates a first four-element mark containing coordinates, time, indexes and concentration values corresponding to the indexes, and transmits the first four-element mark to a data platform collaborative decision system; The unmanned ship accurate dosing and autonomous flight path control system comprises an unmanned ship, a microbial inoculum activating and adding device, a fluorescence chlorophyll a sensor and a second hot spot marking system, wherein the microbial inoculum activating and adding device is carried on the unmanned ship; the unmanned ship sails along the planned track, the fluorescence chlorophyll a sensor synchronously detects the chlorophyll a concentration in the water area, when the detected chlorophyll a concentration is higher than a preset limit value, the second hot spot marking system records the point coordinates with the over-limit value, generates a second four element mark comprising the coordinates, time, indexes and concentration values thereof, and transmits the second four element mark to the data platform collaborative decision-making system; The data platform collaborative decision-making system comprises a track dynamic planning system and a dose dynamic decision-making model, and is used for planning a fungus throwing track of the unmanned ship based on a first four-element mark after the unmanned ship completes inspection, and dynamically regulating and controlling the ship speed of the unmanned ship and the fungus agent activating and throwing dose of the fungus agent throwing device according to concentration classification based on a second four-element mark.
2. The precise algae prevention and control system based on air-water collaborative intelligent decision-making according to claim 1, wherein the hyperspectral water quality inversion system comprises a hyperspectral water quality imager and an edge calculation module; the wavelength range of the hyperspectral water quality imager is 400-1000nm, the spectral resolution is better than 5nm, and the spatial resolution is better than 0.2 m; The edge calculation module is internally provided with a lightweight depth forest inversion model, and after fractional differential pretreatment and gradual discriminant analysis feature screening are carried out on 300 wave bands within the range of 400-1000nm, the chlorophyll a concentration of the water area is calculated in real time, the spatial resolution is better than 0.2m, the average relative error is less than 10%, the data are processed in real time by an airborne terminal, and the delay is less than 60s.
3. The algae precise prevention and control system based on the air-water cooperative intelligent decision according to claim 1, wherein the first hot spot marking system and the second hot spot marking system adopt GNSS-RTK positioning modules, support the GPS L1/L2 and Beidou B1/B2 dual-frequency carrier phase differential positioning, access local continuous operation reference station service through a 4G network, receive differential correction data in RTCM 3.2 format in real time, output frequency of 10Hz, horizontal positioning precision of better than +/-1.5 cm, and elevation precision of better than +/-3 cm.
4. The algae precise prevention and control system based on air-water cooperative intelligent decision as claimed in claim 1, wherein the unmanned ship is further equipped with a multi-mode autonomous obstacle avoidance system; the multi-mode autonomous obstacle avoidance system is integrated with a millimeter wave radar and a forward looking camera, and a dynamic map is constructed in real time in navigation so as to realize centimeter-level avoidance of obstacles.
5. The precise algae prevention and control system based on intelligent air-water cooperative decision as claimed in claim 1, wherein the microbial agent activating and adding device comprises a microbial agent storage cabin, a screw conveyor, a microbial agent activator and a flow impeller; The volume of the microbial inoculum storage cabin is 50L, and the microbial inoculum storage cabin is used for storing microbial inoculum dry powder; The screw conveyor is arranged at the bottom of the microbial inoculum storage cabin and is used for conveying microbial inoculum dry powder to the microbial inoculum activator at a constant speed, and the power of the screw conveyor is 0.12kW; The microbial inoculum activator is L-shaped, so that the adding depth of the microbial inoculum is ensured to be 0.5m below the water surface; The impeller is arranged in the microbial inoculum activator, the power of the impeller is 0.37kW, the efficient mixing of microbial inoculum and water is realized by utilizing paddle turbulence, the mixing efficiency is more than 95 percent, the concentration gradient of the microbial inoculum is less than 0.5g/m 3 .m, and the effective addition of the microbial inoculum is realized; The microbial inoculum is algae inhibiting bacteria, is ecological friendly and does not cause adverse effect on aquatic animals and plants.
6. The algae precise prevention and control system based on the intelligent air-water cooperative decision according to claim 1, wherein, And the flight path dynamic programming system identifies the point position of chlorophyll a concentration exceeding the threshold value in the water by analyzing the first four element mark, clusters the point position of chlorophyll a concentration exceeding the threshold value through a clustering algorithm to form a key area needing unmanned ship dosing, finally combines the key area distribution, unmanned ship routing inspection route and river water system distribution condition, generates the optimal navigation route of the unmanned ship based on a simulated annealing algorithm, and realizes the visual display of the navigation route by depending on a GIS map.
7. The precise algae prevention and control system based on the air-water cooperative intelligent decision according to claim 1, wherein the dose dynamic decision model takes chlorophyll a concentration and the change rate thereof as input, PID parameters are established on line through a preset fuzzy rule, the ship speed is dynamically corrected, the self-adaptive control of response time <5 seconds and overshoot of <10% is realized, and an accurate mathematical model of algae growth dynamics is not required to be established.
8. The precise algae prevention and control system based on air-water collaborative intelligent decision-making according to claim 1, wherein the data platform collaborative decision-making system dynamically regulates the ship speed and the fungus dosage according to hydrologic conditions and chlorophyll a concentration classification.
9. The use of an algae precise prevention and control system based on air-water collaborative intelligent decision-making according to any one of claims 1-8 for precise prevention and control of algae outbreaks in a body of water.
10. An algae outbreak accurate prevention and control method based on an air-water cooperative intelligent decision, which is characterized in that the algae accurate prevention and control system based on the air-water cooperative intelligent decision is adopted according to any one of claims 1 to 8; The method comprises the following steps: The unmanned aerial vehicle inspection of appointed waters along the preset route, utilize the hyperspectral water quality inversion system to invert chlorophyll a concentration in real time, when the inverted chlorophyll a concentration exceeds the preset threshold value, the first hot spot marking system records the risk point location coordinates, generates the first four element mark comprising coordinates, time, index and index corresponding concentration value and transmits to the data platform collaborative decision system; the data platform collaborative decision-making system plans a fungus throwing track of the unmanned ship based on the first four-element mark after the unmanned ship completes the inspection; The unmanned ship sails along the planned track, a fluorescence chlorophyll a sensor synchronously detects the chlorophyll a concentration of the water area, when the detected chlorophyll a concentration is higher than a preset limit value, a second hot spot marking system records the coordinates of the point positions with the overrun value, generates a second four-element mark comprising the coordinates, time, indexes and concentration values thereof, and transmits the second four-element mark to a data platform collaborative decision-making system; The data platform collaborative decision-making system dynamically regulates and controls the ship speed of the unmanned ship and the fungus agent activating and adding amount of the fungus agent adding device according to concentration classification based on the second four-element mark.

Description

Algae precise prevention and control system based on air-water cooperative intelligent decision and application thereof Technical Field The invention relates to the technical field of water environment algae treatment, in particular to an algae precise prevention and control system based on air-water cooperative intelligent decision and application thereof. Background The technical maturity of the current water area microbial inoculum adding device presents an imbalance situation with relatively perfect mechanical automation and serious lag of intelligent autonomy. Although the existing patent documents realize automatic replacement of links such as throwing, stirring, conveying and the like (such as CN210251895U, CN213294735U, CN112850816A and the like) on the mechanical execution level, the existing patent documents still stagnate in a primary automation stage in three core dimensions of intelligent decision making, precise decision making and unmanned operation and maintenance, and do not reach the level of autonomy driven by artificial intelligence. The following problems are common in the prior art through analysis: 1. response hysteresis. Under proper conditions (warm air temperature, strong illumination and high nutrition), the algae breeding period can be shortened to 2-30 hours, and the algae breeding period grows in logarithmic scale. The conventional algae treatment usually requires several days from sampling detection, analysis and judgment to measure landing, and a control window before the critical point of algae outbreak is often missed. 2. Shi Ce blindness. The traditional automatic dosing equipment (such as a fixed pontoon and a uniform spraying boat) adopts a preset program to carry out open-loop dosing, the dosing time, the dose and the point position of the automatic dosing equipment are judged according to experience, the automatic dosing equipment is preset manually, and the non-uniformity of the spatial distribution of algae is not considered, so that the treatment efficiency is low, the partial dose of the chemical agent is insufficient and excessive and coexists, and the algae bloom is out of control. 3. Operational dependencies. The traditional treatment equipment focuses on the optimization of a single mechanical structure, is mostly in a remote control or semi-automatic mode, the obstacle avoidance, the track planning and the dosage decision-making all need deep manual intervention, the autonomous decision-making and fault-tolerant capability of the system are lost, and the unmanned operation cannot be realized. Resulting in high operation and maintenance costs and difficulty in deployment in remote or dangerous waters. Part of treatment is introduced into an unmanned ship platform, but a closed loop architecture of air wide area sensing-water surface precise execution-cloud collaborative decision is not realized, the dosing strategy is still based on threshold judgment instead of a prediction model, and the system robustness and environmental adaptability are limited. Disclosure of Invention Aiming at the technical problems and the defects existing in the field, the invention provides an alga precise prevention and control system based on an air-water cooperative intelligent decision and application thereof. In order to solve the problem of response lag, the invention constructs an algae prevention and control zero-delay response system, wherein the unmanned aerial vehicle hyperspectral data realizes on-board real-time inversion, eliminates post-treatment waiting, adopts a high-precision positioning module for unmanned aerial vehicles and unmanned ships, shortens the time from identification to planning, integrates algae inhibition activation and dosing, shortens the traditional step-by-step time sequence, adopts a dynamic decision model for dosing, accelerates the operation time through a preset fuzzy rule, and breaks through response bottleneck. In order to solve the problem of blind adding, the invention constructs a data-driven accurate adding system, wherein the system relies on an unmanned ship to sense data in real time, dynamically optimizes the dosage in cooperation with a decision-making platform, avoids the phenomenon of partial shortage or excessive adding of the microbial inoculum, optimizes a microbial inoculum activator, adjusts the adding depth of the microbial inoculum and improves the utilization rate of the microbial inoculum. In order to solve the problem of operation and maintenance dependence, the invention constructs a full-intelligent operation system, wherein an unmanned ship is provided with a multi-mode autonomous obstacle avoidance system to ensure unmanned safe navigation in a complex water area, the system forms a double closed-loop control framework of remote sensing inversion, track planning, in-situ addition and effect feedback, and deep fusion of hyperspectral feedforward guidance of the unmanned ship and real-time feedback of the unmanned ship