2882 results about "Water area" patented technology

The embodiment of the invention provides a BIM-based hydraulic engineering digital management method and system. The method comprises the following steps: performing multi-dimensional monitoring system deployment on a to-be-monitored area to obtain multi-dimensional hydrological data; constructing a first BIM based on the topographic data of the to-be-monitored area, the real-time work area image, the hydraulic engineering construction information of the design stage and the equipment deployment information; fusing the multi-dimensional hydrological data, the water area change data, the construction progress data and the operation and maintenance monitoring data into the first BIM, and constructing a second BIM including a full life cycle; and through the equipment characteristic curve and the water conservancy project physical model, in combination with the multi-dimensional hydrological data and the water area change data, predicting a water conservancy project structure change trend and potential risk factors in the second BIM, fusing the water conservancy project structure change trend and the potential risk factors into the second BIM, and displaying an implementation effect and improvement suggestions in real time in the second BIM. A user is assisted to realize hydraulic engineering digital management, and the engineering management efficiency is improved.

The invention discloses a multi-temporal-spatial-scale cyanobacterial bloom early warning method for middle and large lake and reservoir water areas, and belongs to the field of cyanobacterial bloom prediction and risk monitoring. The method comprises the following steps: generating a pixel-level FAI index based on target water area remote sensing data, resampling meteorological data into a pixel level, then constructing a spatial-temporal distribution data set, training an Autoformer-ST-GNN time sequence model to realize FAI index prediction, dividing cyanobacterial bloom levels according to the FAI index prediction, and obtaining a global change trend; water quality monitoring points are arranged in key areas to collect data, historical water quality and meteorological data are utilized to train a DMC-PatchTST model fused with a blue-green algae migration period, and multi-time-scale prediction of the density of blue-green algae at the monitoring points is achieved; and finally, combining the global trend with a monitoring point prediction result to construct a space-time multi-scale cyanobacterial bloom comprehensive early warning system. According to the method, multi-source data and multiple models are fused, so that cyanobacterial bloom time-space multi-scale comprehensive early warning is realized, and the method is accurate and comprehensive.

The invention belongs to the technical field of pollution tracing, and discloses a distributed water body pollution tracing method and system, and the method comprises the steps: constructing a plurality of directed node pairs according to a topological structure of each partition node in a monitored water area; according to the pollutant concentration data in the monitored water area, determining a time delay interval of a pollutant concentration peak value between each directed node pair; determining an effective node pair of which the time delay interval meets the space-time constraint from the plurality of directed node pairs, and constructing a plurality of backtracking paths according to the effective node pair; performing particle tracking simulation on the pollutant concentration data to obtain a plurality of simulation paths, and determining a particle intersection area of pollutants according to the plurality of simulation paths; and determining a pollution source area according to the plurality of backtracking paths and the space intersection of the particle intersection area, and further determining traceability positioning. According to the method, the backtracking path is constructed through dynamic time-delay analysis, high-precision identification of the pollution source is realized by combining particle tracking and gridding intersection positioning, and the problems of insufficient space-time dynamics and large positioning deviation of a traditional method are solved.

The invention discloses a complex water area garbage intelligent detection and collection method based on multi-modal perception, and the method comprises the steps: obtaining image perception data and semantic environment data of a complex water area; the method comprises the following steps: performing preprocessing, performing feature extraction and semantic coding, and then performing multi-modal feature alignment fusion, feature extraction and multi-task detection to obtain a garbage detection result, thereby effectively realizing deep fusion of semantic priori and visual features, and improving the accuracy and robustness of garbage recognition in a complex water area environment; then task importance evaluation is carried out to construct a garbage disposal priority queue, a path dynamic planning strategy oriented to energy consumption constraint and task priority collaborative optimization is constructed to carry out path generation, navigation energy consumption is reduced on the premise that task benefits are considered, and garbage detection and collection tasks in a complex water area are achieved; the system adapts to various intelligent devices such as unmanned ships, unmanned aerial vehicles and shore-based platforms, and has high autonomy, environmental adaptability and engineering deployability.

The invention relates to the technical field of environment assessment, in particular to a coastal zone culture area multi-dimensional environment assessment method and a cloud platform. The method comprises the following steps: continuously recording dissolved oxygen concentration, pH value, centigrade temperature, salinity unit, turbidity scattering unit, chlorophyll fluorescence intensity, ammonia nitrogen milligram per liter and nitrite milligram per liter, synchronously calling multi-source remote sensing images covering a culture area and an adjacent water area, extracting remote sensing reflectivity data through image correction and atmospheric correction, and calculating to obtain water color parameters. According to the method, the water quality sensor array is deployed at the key point of the culture area, continuous multi-parameter environmental data acquisition is carried out, multi-source remote sensing images are synchronously integrated, water color information is extracted in real time, and the timeliness and data accuracy of culture water area environmental monitoring are improved; trend decomposition and dynamic baseline construction are carried out based on the data sequence, so that the environmental fluctuation evaluation of the breeding area is more objective and accurate.

The invention relates to the technical field of water quality pollution detection, in particular to a water quality pollution rapid detection method driven by a quantum sensing technology. A quantum sensor array is deployed in a water area to be detected, and quantum signal response data of the water area is collected; constructing a pollutant quantum recognition model, and inputting quantum signal response data into the model to obtain an initial predicted value of pollutant concentration; generating an initial detection parameter of the quantum detection instrument based on the initial predicted value, executing primary pollution detection by the instrument according to the parameter, and collecting primary deviation data of an actual detection value and an expected detection value; determining a detection error according to the deviation data, further correcting the initial detection parameter, and generating an optimized detection parameter; and finally, the instrument performs secondary pollution detection based on the optimized detection parameters. According to the method, complex water sample pretreatment is not needed, water quality pollution detection can be rapidly and accurately completed, detection requirements of different water areas are met, and the detection efficiency and accuracy are improved.

The invention discloses a bridge ship collision early warning system based on artificial intelligence, and relates to the field of intelligent traffic infrastructure safety protection. The method is used for solving the problems of difficulty in multi-source data fusion and low risk identification accuracy in a complex water area. The method comprises the following steps: firstly, uniformly mapping a radar point cloud, an AIS signal and a visual trajectory to a coordinate system taking a pier as a center through a Lie group transformation algorithm, and constructing a ship motion state tensor; then, ship behavior characteristics are extracted through a space-time diagram convolutional network, and intention probability distribution and behavior deviation degree are output; thirdly, an orthogonal constraint variational auto-encoder is adopted to decouple the autonomous control behavior and the environment disturbance factor, and a collision risk quantized value is generated according to the norm ratio of the autonomous control behavior and the environment disturbance factor; and finally, constructing a dynamic alarm threshold value according to the behavior deviation degree and the disturbance characteristics, realizing graded early warning, and driving a behavior pattern library to update through a feedback mechanism to form a self-adaptive closed-loop early warning system.

The invention relates to the technical field of underwater detection, and discloses an underwater comprehensive detection system. The system collects multi-dimensional acoustic data including sound wave reflection intensity, propagation time delay and frequency dispersion characteristics of a target water area through an underwater sonar array; dividing the detection area into a plurality of layered units according to a water attenuation coefficient and a substrate reflection characteristic of the acoustic data, and extracting an environment intrinsic parameter of each layered unit; constructing an acoustic propagation path model based on the environmental intrinsic parameters, and generating adaptive filtering parameters in combination with a preset noise suppression strategy; calling sonar array hardware configuration data, matching filtering parameters with an array beam forming mode, and calculating a detection sensitivity threshold value of each layered unit; and integrating the sensitivity threshold and the acoustic data, generating a three-dimensional acoustic characteristic spectrum of the target water area, and marking the space coordinates and confidence level of the abnormal area. The system can improve the comprehensiveness and accuracy of underwater detection, and meets the requirement of high-precision detection.

The invention provides a digital twinning-based water flow dynamic analysis method and a big data analysis system, and the method comprises the steps: obtaining a historical water flow data set of a target water area, collecting a real-time water flow monitoring data set, and constructing a digital twinning water flow model corresponding to the target water area; performing multi-modal feature fusion processing on the historical water flow data set and the real-time water flow monitoring data set to generate a dynamic water flow feature set, loading the dynamic water flow feature set into a digital twin water flow model based on a spatial distribution topological structure of the digital twin water flow model to generate a water flow dynamic change rule set, and performing dynamic water flow change on the dynamic water flow change rule set. And generating a water flow optimization strategy set according to the water flow dynamic change rule set, and feeding back the water flow optimization strategy set to the water flow regulation and control system to execute dynamic regulation and control operation. By adopting the technical scheme of the invention, the space adaptability and the dynamic response capability of the water flow optimization strategy decision can be obviously improved.

The invention relates to the technical field of environment intelligent supervision, and discloses a visual river and lake water area health ecological supervision and management system. A data acquisition and feature extraction module of the system is responsible for acquiring multi-source ecological monitoring data of water areas of rivers and lakes, extracting spatial change features of motion trails of aquatic organisms and a time sequence of water quality parameters from the data, and identifying abnormal features according to an index variation mode corresponding to a predefined ecological health level; and generating an ecological health abnormity response label set associated with the specific geographic position. And the health state analysis module obtains key information of the marked water area section based on the label set, analyzes a change track and a deviation interval of the health state in the supervision time frame, and determines a health state lagging time period. And the evaluation delay processing module is used for extracting related time information to calculate a time difference according to the water area subareas related to the lagging time period, screening out the water area subareas which are not evaluated completely and sorting the water area subareas, and generating an adjustable configuration scheme of the monitoring time period of the water area subareas.

The invention discloses a shrimp health state early warning method and system based on water quality monitoring, and aims to improve the disease prevention and control efficiency in a shrimp culture process. The method comprises the following steps: collecting historical breeding disease data and water quality change data of a target shrimp breeding water area, and constructing a water quality pathopoiesis knowledge graph; then water quality change data in a preset monitoring time period is obtained, space-time tracing is carried out by using the water quality change prediction model, and a water quality anomaly propagation path diagram is generated; formulating a water quality monitoring strategy based on the propagation path diagram, and optimizing the layout and frequency of monitoring points; and finally, monitoring the water quality in real time according to the established monitoring strategy, and realizing dynamic early warning of the health state of the prawns by combining real-time monitoring data and a water quality pathopoiesis knowledge graph. Water quality related diseases can be effectively prevented and controlled, and the stability and yield of shrimp culture are improved.

The invention relates to the technical field of computer vision and radar perception, in particular to a ship intelligent detection system based on a convolutional neural network and radar signal processing, which comprises a ship three-dimensional perception modeling module, a visual feature hierarchical fusion module, a target detection module and an anomaly detection module. The system emphatically utilizes deep learning methods such as a convolutional neural network and the like to realize three-dimensional space modeling and visual feature extraction of a ship by a radar in a water area environment. And a layered adaptive fusion and mutual information enhancement mechanism is adopted. The end-to-end detection model introduces a spatial hierarchy weighting strategy, so that the object detection accuracy and interpretability under the conditions of multi-target density, shielding and dynamic change in a complex water scene are improved. The system realizes continuous tracking, anomaly detection and risk early warning of ship navigation behaviors based on space-time dynamic modeling. The whole scheme has high precision, strong robustness and adaptive ability, and can meet the requirements of ship detection and intelligent management and control in complex water area environments such as smart ports and water traffic.

The invention discloses an ecological environment monitoring method and system based on a geographic information technology, and relates to the technical field of ecological environment monitoring, and the method comprises the steps: carrying out the multi-source heterogeneous data fusion of a multispectral image and point-like time series data of a water ecological protection target water area, and obtaining a three-dimensional water quality dynamic situation field; future trajectory prediction and water ecological health analysis are carried out on the three-dimensional water quality dynamic situation field to obtain a global water ecological health index thermodynamic cloud picture, pollution diffusion is carried out on the global water ecological health index thermodynamic cloud picture to obtain a pollutant trajectory matrix, ecological risk prediction is carried out based on the pollutant trajectory matrix, and the ecological risk prediction result is obtained. According to the method, the spatial-temporal dynamic risk early warning grade map is obtained, the restoration scheme is optimized based on the spatial-temporal dynamic risk early warning grade map, the restoration scheme optimal solution set is obtained, the timeliness and accuracy of ecological risk early warning are improved, and the economy of restoration decision is enhanced.

The invention relates to the technical field of mathematical modeling, in particular to a mathematical model modeling method based on data analysis operation processing. The method comprises the following steps: collecting metal pollution data of a target water area by using a multi-parameter water quality sensor array; performing time sequence alignment on the metal pollution data to generate a standardized pollution data set; constructing a metal migration model based on fluid dynamics and chemical adsorption coupling; inputting the standardized pollution data set into the metal migration model for three-dimensional space interpolation calculation, and generating a metal pollutant diffusion cloud picture; pollution source reverse analysis is carried out on the metal pollutant diffusion cloud picture, and a potential pollution source coordinate set and pollution contribution degree sorting are generated. According to the method, by integrating multi-parameter water quality sensor data, fluid dynamics and chemical models and multispectral analysis, the modeling precision of the water pollution diffusion mathematical model is improved.

The invention discloses a method for evaluating enhancement and release seedling resources based on environmental DNA polymerization analysis. The method comprises the following steps: carrying out gridding partition on a target water area, collecting a water sample through a designed sampling scheme, and carrying out DNA extraction and high-throughput sequencing to obtain species sequence information of each sampling point. Sequencing data is subjected to species identification by using a bioinformatics method, released species are identified, a spatial abundance model is established, and a preliminary distribution map is generated. And establishing a DNA degradation kinetic model in combination with water area environmental parameters, and carrying out reverse correction on abundance distribution. And through a resource inversion model coupled with hydrodynamics, analyzing biomass distribution characteristics and migration laws of the release group, and obtaining a resource evaluation result. And finally, a species environment preference model is constructed based on migration path analysis, an optimal release area is matched in a target water area, a scientific scheme including release point locations, opportunities and quantity is generated, and a whole-process technical support and a decision basis are provided for enhancement and release.

The invention discloses an acoustic Doppler flow velocity measurement method and system, and the method comprises the steps: generating an emission parameter combination adaptive to a current hydrological environment according to the depth characteristics and precision requirements of a target water area; original echo signals are collected based on the emission parameter combination, and a three-dimensional flow velocity vector of temperature compensation is output; inputting the three-dimensional flow velocity vector into the dynamic segmentation network to generate a layered flow velocity distribution model; calling a layered flow velocity distribution model, fusing fluxgate compass azimuth data to carry out flow direction compensation, triggering a deviation correction algorithm when equipment inclination exceeds a limit, and outputting absolute flow velocity distribution of pose calibration; and according to absolute flow velocity distribution and echo intensity dynamic range constraint, calculating an error interval of each depth unit, and outputting a final flow velocity profile with confidence identification. According to the embodiment of the invention, the environmental adaptability and data reliability of flow velocity measurement can be improved.

The invention discloses an anti-collision early warning system for a ship navigation bridge, and belongs to the technical field of bridge collision prevention. Comprising a monitoring module used for collecting ship information in an early warning area; the information processing module is used for obtaining ship poses, mast recognition and the height difference between the highest point of the mast and the water surface based on the ship information; the dangerous water area dividing module is used for calculating the longitudinal minimum safety distance and dividing the grade of the dangerous water area based on the longitudinal minimum safety distance; the early warning module is used for obtaining a comprehensive risk value based on the ship pose, mast identification and the height difference between the highest point of the mast and the water surface; early warning grades are divided based on the comprehensive risk values and the grades of the dangerous water areas, and anti-collision early warning is carried out based on the early warning grades. The method is superior to an existing bridge anti-collision technology in the aspects of monitoring precision, environmental adaptability, early warning timeliness, warning diversity and deployment economy.

The invention relates to the technical field of water conservancy monitoring, and provides an intelligent water conservancy monitoring method for an irrigation area and related equipment thereof. Water body boundary extraction is carried out on remote sensing image data to obtain an initial water body boundary data set, time sequence interpolation processing is carried out on the initial water body boundary data set to obtain a water body change trend data set, and soil moisture content prediction deduction is carried out according to a satellite cloud picture and the water body change trend data set to generate a soil moisture content prediction data set. Performing water level and area fitting on the regional DEM according to the water body change trend data set to construct a water storage capacity model, and performing crop water demand calculation according to regional data and crop data to obtain a crop water demand matrix data set; and performing constrained programming according to the soil moisture content prediction data set, the crop water demand matrix data set and the water storage capacity model to obtain a multi-target irrigation scheduling decision set. According to the application, dynamic balance between irrigation requirements and water resource supply is realized through multi-level and multi-source data fusion and intelligent scheduling.

The invention discloses a lightweight optical flow neural network method for river velocity measurement, and the method comprises the steps: collecting a dynamic monitoring image of a water area surface flow field, calculating an approximate optical flow field through combining with a DeepFlow optical flow algorithm, and generating an optical flow label; an improved lightweight ConvFFN-Flow optical flow estimation model is built, and the model comprises a feature extraction module, a 4D related structure body module, a GRU optical flow residual error iteration module and an up-sampling module; by introducing a ConvFFN module, the model parameter scale and the calculation amount are reduced, and the optical flow prediction precision is kept; and based on pixel coordinates of front and rear frames of images of the optical flow field data, obtaining corresponding positions in a real three-dimensional space, calculating an actual displacement amount, and deducing to obtain a real flow velocity vector size and a flow direction of the water body surface. The method still has stable and high-precision optical flow estimation capability when being used for processing scenes such as fine river water surface texture and complex flow state change, and meanwhile, the calculation overhead and the storage demand are remarkably reduced.

The invention provides a water area monitoring system for cooperative operation of an unmanned aerial vehicle and an unmanned ship based on a Mesh ad hoc network. The water area monitoring system comprises the unmanned aerial vehicle, the unmanned ship, a Mesh ad hoc network module, a cooperative control system and a shore end control system, according to the unmanned plane, wide-area patrol and image acquisition, airspace and wide-area water area information is acquired through a sensor, fixed-point acquisition and water area information acquisition are realized through an unmanned ship, and data interaction is realized by relying on nodes of a Mesh ad hoc network. Through the multi-hop relay and dynamic routing technology of the Mesh ad hoc network, autonomous and reliable communication in a scene without a fixed base station is realized, and the communication coverage range and survivability are improved; on the basis of distributed task allocation and real-time data interaction, the equipment cooperation efficiency is remarkably improved, the response delay is shortened, and efficient completion of tasks in a complex environment is guaranteed.

The invention discloses a cooperative supervision method and system for a water area ecological environment, and belongs to the technical field of ecological environment supervision, and the method comprises the steps: carrying out the global monitoring of a target water area, obtaining a monitoring image sequence of the target water area, calculating the pollution confidence, recognizing a pollution region, quantifying the area, and generating a diffusion drive signal, obtaining a category label of the target pollutant; obtaining the motion trail of the target pollutant, reversely deducing the local flow velocity and flow direction of the water surface, identifying an abnormal target in the target water area, and generating an abnormal pollution association table in combination with the pollution area; according to the method, local data of a water area are collected in real time, a water area situation base map is generated, a water quality diffusion model is constructed, a multi-time-dimension pollution diffusion simulation result is generated, and plan deduction and risk assessment are performed, so that a supervision decision is upgraded from passive disposal to active prevention and control, and decision requirements of risk pre-judgment and active prevention and control are fully met.

The invention provides a water body water level monitoring method of an image segmentation model, and the method comprises the steps: obtaining multi-modal water flow data of a target water area, carrying out the feature extraction of the multi-modal water flow data, and obtaining a turbulence feature map, the multi-modal water flow data comprising water flow motion data and water body image data; performing physical constraint segmentation processing on the turbulence feature map and the water body image data to obtain a water body region segmentation mask and a corresponding pixel-level confidence map; carrying out water gauge geometric correction processing on the water body region segmentation mask to obtain a corrected water line; and performing water level value conversion processing on the corrected water level line and the pixel-level confidence map to obtain a water level measurement value and uncertainty data. By adopting the method, the real water line and the dynamic water flow artifact can be effectively distinguished, and the monitoring precision under the complex hydrological condition is ensured.

The utility model relates to the technical field of hydraulic engineering monitoring, in particular to a water level monitoring device for water resource management, which comprises a stand column, a signal box and a solar cell panel are fixedly connected to the surface and the top end of the stand column, and an adjusting mechanism comprises a first supporting rod hinged to the surface of the stand column. An electric push rod is fixedly connected to the inner wall of the bottom end of the stand column, a sliding groove is formed in the surface of the stand column, and a connecting block is slidably connected into the sliding groove; when the ultrasonic sensor needs to be maintained, the first supporting rod can be directly pulled to rotate through the electric push rod, so that the ultrasonic sensor moves towards the shore while descending, and a worker can conveniently maintain the ultrasonic sensor; the height and the distance between the ultrasonic sensor and the water area to be monitored can be randomly adjusted according to the environment, so that the monitoring data is more practical and more stable.

The invention relates to the technical field of garden water monitoring, in particular to garden water quality intelligent monitoring equipment which comprises a base, a round basin and the like. A round basin is fixedly connected to the base, and a pull ring is installed on the round basin. By releasing the water outlet pipe and under the gravity action of the counterweight ball, the water pipe vertically moves downwards, then negative pressure is generated in the water pipe, a water sample is extracted through the filtering ball head, impurities in a water area are filtered through the filtering ball head, and therefore the water sample flows along the water pipe, the round pipe, the guide pipe, the water pump and the conveying pipe; and finally, the water flows into the water collecting barrel through the conveying pipe, the extracted water sample is carried by the baffle plate and the flow deflector I together, the monitoring probe is submerged by the water, and then the monitoring probe is controlled to start to operate to detect the water sample, so that the water body in the garden is monitored, and the mode is short in period and high in efficiency, and can meet the real-time requirement.

The invention relates to the technical field of river bank protection, in particular to a river bank slope protection for cofferdam construction and a construction method thereof. S2, construction of a near-water area structure; s3, construction of a far water area structure; s4, ecological enhancement; triple optimization of river bank protection is achieved through dynamic water level monitoring and modular design, a double-layer reinforced concrete and elastic sealant structure is adopted in a near-water area, the compressive strength is improved by 20%, the crack width is smaller than or equal to 0.2 mm, and material waste is reduced by 15% in cooperation with dynamic width adjustment (+ / -2 m); the mold bag concrete slope protection is combined with an atomization spraying system, the anti-scouring capacity reaches 5 m / (m.s), the vegetation coverage rate is larger than or equal to 80% within 3 months, and the water and soil loss rate is reduced by 70%; the modular honeycomb structure inflation assembly efficiency is improved by 40%, the transportation cost is reduced by 50%, the distributed sensors achieve structure displacement / pressure three-level early warning, the operation and maintenance cost is reduced by 70%, the overall service life is prolonged by more than 5 years, and an ecological-engineering collaborative protection system is formed.

The invention discloses a pool robot control method and a pool robot, and the method comprises the steps: controlling the pool robot to move in a water area of a pool, the pool comprising a pool inner wall and the water area; wherein the pool robot is provided with a first sensing piece and / or a first sensed piece, and the bearing assembly is provided with a second sensed piece and / or a second sensing piece; in the movement process, in response to a first sensing event between the first sensing part and the second sensed part and / or a second sensing event between the second sensing part and the first sensed part, the pool robot is controlled to move to the bearing assembly so as to execute the target event. Through the above mode, the pool robot can quickly and accurately find the target position for executing the target event, so that the working efficiency of the pool robot is improved.

The invention discloses a scenic spot automatic driving yacht scheduling management algorithm. The system comprises a data acquisition and processing module, a distance calculation module, a comprehensive evaluation module, a scheduling decision module, a real-time monitoring and adjusting module and the like. The data collecting and processing module accurately obtains tourist demands and yacht state data and preprocesses the tourist demands and the yacht state data. The distance calculation module constructs a water area map model, and corrects the distance from the yacht to the boarding point in combination with water flow and wind direction factors. And the comprehensive evaluation module can evaluate the yachts in multiple dimensions and exclude unseaworthy yachts. And the scheduling decision module screens candidate yachts based on the results, selects an optimal scheduling scheme by using a weighted comprehensive evaluation method, issues an instruction and feeds back the instruction to tourists. The real-time monitoring and adjusting module monitors the state of the yacht in real time, quantifies and grades according to the task emergency degree, and adopts corresponding strategies according to different grades; the system can adapt to various scenic spot environments, significantly improves the scheduling efficiency, optimizes the resource utilization, enhances the tourist experience, and guarantees the reliable operation of the automatic driving yacht system in the scenic spot.

The utility model discloses a water area propeller and water area movable equipment. The water area propeller comprises a machine body, an operation device and a locking module. A propelling device used for outputting propelling force for propelling the water area carrier to move is arranged at the end of the machine body. The operation device is rotationally connected to the end, away from the propelling device, of the fuselage body through a transverse connecting shaft, can be folded or unfolded with the fuselage body and is used for being operated by a user to control the water area propeller to operate. The locking module comprises a first locking unit and a second locking unit, and the first locking unit and the second locking unit are arranged in the operation device and the machine body respectively. The operation device and the machine body are locked by the meshing force between the first locking unit and the second locking unit at the position between the transverse connecting shaft and the propelling device, and the operation device forms a suspension beam capable of loading the machine body between the transverse connecting shaft and the locking module.

The invention discloses a regional water supply system optimization scheduling method considering the influence of a salt tide. The method comprises the following steps: S1, constructing a multi-water-source-multi-water-plant-multi-water-demand-area layered water supply topological structure covering a target area influenced by the salt tide; s2, judging a salt tide period according to real-time water quality monitoring data of a reservoir in an area influenced by the salt tide, dynamically adjusting a target function and constraint conditions of the multi-target multi-water-source optimal scheduling model, and preferentially scheduling water sources with safe water quality; and S3, on the basis of the topological structure model constructed in the step S1, by taking the salt tide state in the step S2 as a dynamic parameter, constructing a three-dimensional objective function of'water deficit, salt tide influence and cost difference 'of the multi-objective multi-water-source optimal scheduling model, and solving a Pareto optimal solution set through an improved NSGA-III algorithm in combination with constraint conditions. The method is suitable for collaborative scheduling optimization of the multi-water-source system influenced by the salt tide, and has wide application value in the aspects of improving the water resource allocation efficiency, guaranteeing the water supply safety and the like.

The invention belongs to the technical field of mobile robots, and particularly relates to an amphibious hexapod robot which comprises a robot body, six walking feet, a protection box, propellers, a multi-sensor system and a central control unit. The six walking feet are arranged on the two sides of the robot body, and a waterproof driving joint is arranged at the tail end of each foot. The protection box is arranged at the root of the walking foot and internally integrated with propellers; the sensor system comprises a water depth sensor, an attitude sensor and a grounding detection module; the central control unit is used for collecting sensor data in real time, judging whether the current environment is a land or a water area, automatically switching a walking mode or a water propulsion mode, and meanwhile adaptively adjusting gaits and the rotating speed of propellers according to the water depth and the terrain. The robot has environment perception, mode decision, gait generation, grounding prevention protection and energy optimization strategies, full-autonomous and high-adaptability movement in the land and water environment is achieved, and the working capacity and safety of the robot in the complex environment are improved.