57 results about "Snow cover" patented technology

The utility model relates to the technical field of snowsweepers, in particular to a driving gear box for a snowplow, which comprises a first shell, a second shell is movably connected to the surface of the first shell, a fixing bolt is movably connected to the surface of the second shell, and a mounting screw hole is in threaded connection to the surface of the fixing bolt. And the surface of the first shell is fixedly connected with a snow-proof cover. The oil cup is in threaded connection with the upper cover, the upper cover is movably connected with the pressure spring, the upper cover is in threaded connection with the adjusting nut, the oil cup is fixedly connected with the needle valve, the adjusting nut is fixedly connected with the reset spring, the oil cup is fixedly connected with the filter screen, the oil cup is fixedly connected with the connecting block, the oil cup is filled with lubricating oil, and the button is opened. And the transparent pipe can continuously drip lubricating oil to the fourth gear, so that manual oil brushing after the second shell is disassembled is not needed, and meanwhile, the dripping speed of the lubricating oil can be adjusted by rotating the adjusting nut.

The invention discloses a highway ice and snow covered pavement traffic safety risk grade prediction method. The method comprises the following steps: firstly, collecting vehicle operation data, meteorological data and road information data; then, dynamic response generated in the braking or accelerating process of the vehicle is analyzed, key parameters such as the speed, the acceleration and the braking force of the vehicle are combined, and the numerical value of the road surface friction coefficient is estimated; afterwards, environmental factors such as ice and snow, temperature and snowfall intensity are comprehensively considered, the road adhesion coefficient obtained through estimation is corrected, a numerical value better fitting the actual road condition is obtained, and road adhesion coefficient data finally used for risk assessment are calculated; and then, in combination with the corrected road adhesion coefficient under the ice and snow weather condition, carrying out detailed analysis on the adhesion coefficients of different areas by applying a risk assessment function. According to the method, low-cost, high-frequency and wide-coverage attachment coefficient estimation is realized, and the comprehensive risk condition of the ice and snow covered pavement can be reflected more comprehensively and stereoscopically.

The invention provides an electric car hood and a heating control method thereof, the electric car hood comprises a hood outer plate and a hood inner plate which are arranged in a stacked mode, and a reinforcing part clamped between the hood inner plate and the hood outer plate, and the reinforcing part is made of an electric heating material so as to generate heat in an electrified state. According to the electric car hood, on one hand, accumulated snow covering the hood can be conveniently melted, and the influence of the accumulated snow on the sight of a car driver is reduced; and on the other hand, the reinforcer has certain rigidity, and the overall structural rigidity of the electric car hood can be improved.

The invention relates to the technical field of meteorological short-term climate prediction, and discloses a temperature prediction method based on hybrid space-time neural network and multi-scale feature fusion. The method comprises the following steps: acquiring a historical temperature data sequence and a multi-source meteorological data sequence, wherein the multi-source meteorological data sequence comprises wind speed data, soil temperature data, snow cover data and sea temperature data; strict time sequence feature extraction is conducted on the historical temperature data sequence, a temperature short-term fluctuation feature set and a temperature long-term trend feature set are obtained, and it is ensured that only historical information is used without data leakage through strict time sequence feature extraction; and on the basis of the multi-source meteorological data sequence, the temperature short-term fluctuation feature group and the temperature long-term trend feature group, predicating through an improved LSTM neural network to obtain predicated temperature data of a preset number of days in the future. The accuracy of temperature prediction is improved by constructing a temperature short-term fluctuation feature group and a temperature long-term trend feature group during temperature prediction.

This invention discloses a machine learning-based method for reconstructing snow cover area in mountainous areas, comprising: acquiring and preprocessing optical remote sensing data and topographic data; the optical remote sensing data includes MOD09GA data and Landsat8OLI data; the preprocessing includes topographic correction and snow cover identification; using the snow cover area generated from the Landsat8OLI data using a snow cover identification algorithm as the ground truth label, and constructing a sample dataset based on the preprocessed MOD09GA data and topographic data; dividing the sample dataset into a training set and a validation set at a 4:1 ratio to train and validate an XGBoost model; the XGBoost model improves prediction performance by combining multiple decision trees; and using the trained XGBoost model to predict snow cover area on new input data. This method can generate daily 30-meter (m) snow cover area data, which has important research significance and value for mountainous snow cover monitoring, hydrological process simulation, and ecosystem evolution.

The invention discloses a photovoltaic snow covering depth and power loss forecasting method and system based on multi-source data fusion, and belongs to the technical field of photovoltaic power forecasting. The problems of high-precision accumulated snow influence assessment, short-term risk early warning and power loss quantitative prediction of a photovoltaic system in cold and alpine regions are solved. The method comprises the following steps: selecting three numerical weather forecasting modes, namely a global forecasting system operated by the National Environmental Forecasting Center, a wind energy and solar energy forecasting system of the China Meteorological Administration and a unified mode weather forecast of the British Meteorological Administration, acquiring weather forecasting data, performing unified space-time interpolation, abnormal value correction and unit conversion, and then performing set averaging to obtain a set average value; ensemble forecast data is obtained; based on a temperature-irradiance condition and a friction force mechanism, an accumulated snow covering model is constructed, a photovoltaic panel snow covering range and photovoltaic power loss are obtained, early warning information of snow covering time, duration and power loss is generated through matching of station longitude and latitude and national grid forecasting, and photovoltaic snow covering depth and power loss forecasting based on multi-source data fusion is completed.

The application discloses a distribution box with anti-freezing function, which comprises a box body and a box cover, the box body is internally provided with a heating mechanism, the box cover is provided with a mounting seat and an air outlet mechanism rotatably mounted in the mounting seat, and the air outlet mechanism can spray the high-temperature gas generated by the heating mechanism in a changeable form along the outer surface of the box cover. The distribution box has the advantages that: 1. the heating mechanism can firstly improve the surface temperature of the box cover to melt the bottom layer of snow on the surface of the box cover; 2. the air outlet mechanism can lead the high-temperature gas generated by the heating mechanism out of the box body and spray the high-temperature gas in a changeable form along the outer surface of the box cover, so that the snow on the box cover can be melted in a multi-dimensional manner, the melting process of the whole snow is accelerated, and a thick snow layer is avoided; and the application is dedicated to solving the problem of snow covering on the box cover of the distribution box, preventing the thick snow layer from causing frost in the distribution box and affecting the reliability and continuity of power supply, and preventing the box cover from being in a low-temperature and high-humidity environment for a long time and reducing the service life.

This application discloses a method and system for identifying and assessing foreign object impacts on rail vehicles based on multimodal fusion. It constructs a multi-source monitoring data and operating environment parameter dataset by acquiring image information, structural vibration response information, and impact acoustic information of multiple key structural parts of the rail vehicle, combined with operating parameters, ambient temperature, and track snow cover information obtained from the onboard positioning system. Based on this, a multimodal fusion analysis method is used to identify foreign object impact events, determining the time of foreign object occurrence, impact time, and impact characteristic parameters. Furthermore, the impact load is calculated based on the foreign object's size and material parameters, and the foreign object's entrainment capacity and critical size range are analyzed using an aerodynamic adsorption model. Finally, statistical analysis of the impact events is performed, and the risk level of key structural parts is assessed. This application enables accurate identification and quantitative analysis of foreign object impact behavior on rail vehicles during winter ice and snow, improving operational safety.

The utility model discloses a hand-operated control opening and closing assembly and a passenger ladder platform awning, and belongs to the technical field of passenger ladder platform awnings. According to the technical scheme, aiming at the problem that an existing electric opening and closing device is high in maintenance cost, a nested structure of a movable shell on the outer wall of a fixed rod and a sliding rod is matched with a rack and gear meshing transmission mechanism, and manual rotation torque is converted into horizontal push-pull motion of the sliding rod; a synchronous wheel transmission assembly is arranged to connect the rotating shaft and the movable pipe, and manual driving control is achieved through an adjusting rod-fixed disc-spring mechanism; a conical top end support, a rotating rod and a supporting rod are adopted to form an awning framework, and a movable sleeve supporting mechanism is matched to prevent canvas from drooping. According to the awning, the adjusting rod is manually rotated to drive the transmission system, the rotating rod drives the canvas to be unfolded or folded, countersunk mounting holes are formed in the base to facilitate fixation, and conical flow guide structures are adopted at the joints of all components. The device is suitable for rain and snow shielding scenes of airport passenger ladder platforms.

The application relates to an axle box spring snow cover sleeving device and a working method, which comprises a feeding mechanism, a lifting component, a supporting piece, a transfer mechanism, a first horizontal moving mechanism, a vertical moving mechanism and a suction disc assembly, a sleeving mechanism, a lifting mechanism, a second horizontal moving mechanism, a swing mechanism and a supporting opening mechanism.

This invention relates to a method for the layout of charging facilities that embeds cold-region features and integrates across scales, belonging to the field of electric vehicle charging facility planning and spatial optimization technology. Addressing the shortcomings of existing technologies in fully considering the constraints of low temperatures and snow cover in cold regions and insufficient linkage between urban and community scales, leading to poor matching of layout needs and fairness, this method first collects multi-scale data and performs downscaling and spatial alignment. Second, it constructs a four-dimensional feature set at the urban scale, corrects the weights using a cold-region intensity factor, and identifies highly imbalanced areas. Then, it transfers these features to the community scale to identify dual-objective hotspot grids and uses a GWR-XGBoost model to evaluate micro-spatial adaptability. Finally, it constructs a multi-objective layout optimization model considering cold-region and safety constraints to solve for the Pareto optimal layout scheme, achieving a 10m-level layout at the community scale. This invention is applicable to the field of electric vehicle charging facility planning and spatial optimization in cold-region cities.

The invention belongs to the technical field of porcelain insulator equipment, and discloses a porcelain insulator with an ice and snow prevention cover structure, which is technically characterized by comprising a core column, an umbrella disc is arranged on the surface of the core column, a fixed cover is fixedly mounted on the surface of the core column, and a plurality of groups of protective covers are sleeved in the fixed cover. A positioning mechanism matched with the protective cover is arranged in the fixing cover, the positioning mechanism comprises a guiding assembly and an adjusting assembly, a cleaning mechanism is arranged on the upper surface of the umbrella disc, the cleaning mechanism comprises a sweeping assembly and a driving assembly, and the guiding assembly and the adjusting assembly are arranged to be matched with each other, so that the umbrella disc is cleaned. The relative positions of the protective covers and the umbrella disc can be conveniently adjusted, when protection is not needed, the protective covers are integrally located on the outer side of the umbrella disc, interference to the umbrella disc is avoided, when protection is needed, the protective covers are integrally connected to the outer side of the umbrella disc in a sleeving mode, all-directional closed protection can be conducted on the umbrella disc, and accumulated snow is effectively prevented from being generated on the surface of the umbrella disc.

This invention relates to the field of lidar snow depth estimation technology, specifically providing a hemispherical-scale snow depth estimation method and system based on spaceborne lidar. The method includes: downloading and preprocessing snow cover-related data collected by the spaceborne lidar within a preset hemispherical scale; obtaining snow cover period and snowless period light segments within the preset hemispherical scale based on the preprocessed snow cover-related data; obtaining the intersection points of the snow cover period and snowless period light segments using a dynamic discrimination rule based on a slope-limited intersection point distance threshold; obtaining snow depth values ​​based on the intersection points and a snow depth estimation model; and correcting the snow depth values ​​based on a snow depth reference error model to obtain corrected snow depth values, thus completing the hemispherical-scale snow depth estimation based on spaceborne lidar. This invention is not limited by factors such as altitude or cost when generating snow depth data, and can compensate for sparse station snow depth data. It plays an important role in verifying the authenticity of snow depth products, constructing snow cover models, and measuring snow depth in high-altitude mountainous areas.

The invention provides a snow depth measuring method based on a laser radar and intelligent image recognition, which comprises the following steps: a ruler is fixed on a track plate, four corners of the ruler are provided with circular positioning points, and the ruler is provided with scale numbers and indication grid lines; shooting a track image including the scale based on a camera; preprocessing the track image, and positioning circular positioning points at four corners of the scale to obtain a scale region of interest; the scale numbers and the indication grid lines are used as templates, the accumulated snow covering upper limit scale on the ruler is recognized through a template matching algorithm, and a snow depth corresponding value is determined; identifying the track image by using a pre-trained snow depth identification model, and judging whether snowfall exists or not; the snow depth value output by the laser radar is obtained, and the laser radar and the camera are rigidly fixed to the same platform and jointly calibrated; acquiring a track image, and identifying a snow depth scene based on the snow depth identification model; and fusing the three results to obtain a snow depth measurement result.

The utility model discloses an excavator antiskid track shoe, and the device includes: track shoe body, be equipped with grid groove on the track shoe body, all be equipped with conical tooth in the complete quadrilateral area surrounded by the grid groove, the track shoe body includes base layer and antiskid layer, the grid groove and conical tooth all place on the antiskid layer surface. The utility model has the advantages that: the grid groove set up on the antiskid layer surface of track shoe body and the conical tooth in the quadrilateral area surrounded by the grid groove greatly increase the contact area and friction force between track shoe and ground. In the complex terrain such as muddy, soft or ice and snow cover, the conical tooth can penetrate into the ground, and the grid groove can further hinder the relative sliding between the track shoe and the ground, effectively solve the problem that the existing track shoe is insufficient in antiskid performance and easy to slip in these harsh environments, thereby improve the stability and operation efficiency of the excavator walking, reduce the energy consumption increase caused by the slip.

This invention relates to the field of data evaluation technology, and discloses a multi-source mapping data fusion evaluation method and system for agricultural insurance. The method includes: acquiring images of a target planting area before and after the snowmelt period; extracting the reflectance difference of the snow spectrum of each plot unit in the images under shaded and unshaded conditions to obtain the change in snow cover rate of the plot unit per unit time; identifying accelerated ablation blocks in the target planting area based on the change in snow cover rate; and constructing a snowmelt runoff catchment tree based on the topological connection between the water runoff direction of the slope where the accelerated ablation block is located and the downstream plots; based on the snowmelt runoff catchment tree, this invention can solve the problems of existing technologies having ambiguity in determining the range of runoff scour caused by snowmelt, lacking a nighttime temperature correction mechanism for runoff freezing, and having large deviations between simulated snowmelt flow and actual conditions.

The application discloses a distributed photovoltaic power uncertainty quantification and prediction method based on multi-modal fusion and adaptive learning, comprising the following steps: S1, acquiring first snow cover data; S2, collecting second snow influence data; S3, completing multi-modal data fusion in a three-dimensional feature space; S4, dividing an anomaly detection domain according to a preset threshold condition in the three-dimensional feature space; S5, for the labeled area in the anomaly detection domain, iteratively generating a power prediction band based on Monte Carlo simulation; S6, activating a dynamic compensation algorithm, calculating a compensation coefficient and feeding the coefficient back to the power prediction band simulation input; S7, forming an anomaly detection-compensation adjustment-detection domain adaptive closed-loop iteration mechanism. The application quantifies the on-site uncertainty such as snow and hot spots in photovoltaic power prediction, and significantly improves the prediction accuracy and system response speed through the dynamic compensation and threshold adaptive mechanism.

The utility model provides a kind of anti-icing tower monitoring equipment, including monitoring main part, protective box, snow removing mechanism, snow removing plate, connecting rod, moving block, motor, transmission mechanism, linkage mechanism, when deicing, motor starts, its output end realizes the up-and-down movement of moving block in the process of rotation by transmission mechanism, moving block drives two connecting rods hinged with it, to make two snow removing plates synchronous action and swing at set angle under the action of linkage mechanism, and then break open the ice and snow covered on protective box, ice and snow after breaking open is separated from monitoring equipment under the action of gravity;Therefore, the utility model eliminates the problem of energy waste caused by the need to always open the electric heating wire in protective box until the ice and snow outside protective box is completely melted in traditional deicing mode.

The application discloses a power transmission line insulator snow cover identification method and device and electronic equipment. The method comprises the following steps: acquiring multiple insulator images; using an image enhancement method to respectively perform image enhancement processing on the multiple insulator images to obtain multiple first insulator images; using a pre-constructed denoising convolutional neural network to respectively perform denoising processing on the multiple first insulator images to obtain multiple second insulator images; inputting the multiple second insulator images into a pre-constructed initial insulator snow cover identification model for training to obtain a target insulator snow cover identification model; and using the target insulator snow cover identification model to identify a to-be-identified insulator image to obtain a snow cover identification result corresponding to the to-be-identified insulator image. The application solves the technical problem of low identification accuracy of the power transmission line insulator snow cover identification method in the related art and the inability to identify potential fault risks of the power transmission line in a timely manner.

The application discloses a high-resolution peak snow depth inversion device and method based on a geographical weighted random forest, and comprises the following modules: a data acquisition module, which is used for acquiring multi-source data of a research area, including MODIS remote sensing snow data, Sentinel-1VV / VH backscattering data, terrain data and meteorological station snow depth observation data; a high-resolution snow cover data set construction module, which is used for processing the MODIS remote sensing snow data to obtain a high-resolution cloud-free binary snow cover data set; a feature construction module, which is used for constructing a comprehensive feature set containing snow spatio-temporal process feature indexes, backscattering feature indexes and terrain feature indexes; a model construction and analysis module, which is used for training a geographical weighted random forest model through the comprehensive feature set and inversing the peak snow depth of the research area according to the optimal model. The application can realize the estimation of high-resolution peak snow depth.

The utility model discloses a self -adaptation illumination regulation tobacco seedling shed, including base, the upper surface of base is installed with surface layer glass, and the lower surface of surface layer glass is installed with electric heating wire, the upper surface of base and located surface layer glass's inside face is installed with lower layer glass. In the utility model, its light intensity sensor is used for real -time monitoring the light intensity in the big -arch shelter, when the snow covers the big -arch shelter surface, causes the insufficient illumination, can start the fan and resistance heating rod, and the wind force passes through the heating box, and the wind force temperature rises, and the hot air enters the air interlayer between surface layer glass and lower layer glass, and the heat is outwardly radiated heat through surface layer glass and lower layer glass, on one hand, keeps the temperature of big -arch shelter, avoids the freeze injury of tobacco seedling, on the other hand, indirectly heats the snow, promotes the snow melting, prevents the snow from blocking the sunlight, and cannot illuminate tobacco seedling, and secondly, the setting of electric heating wire, directly heats the snow contact surface, and shortens the snowmelt time.

A transport sled that is configured to receive and retain items such as but not limited to hunting gear, camping equipment and wild game within an interior cavity thereof. The transport sled includes a body having a bottom portion and a top portion wherein the top portion is hingedly secured to the bottom portion. The bottom portion is concave in form having an outer surface configured to slidably traverse across a snow covered surface. The top portion is hexagonal dome shaped forming an interior cavity. The top portion includes storage compartments operable to receive and retain items proximate thereto. The body includes stationary members movably coupled to the rear end of the body. The stationary members move between a first position and a second position wherein in the second position the teeth members of the stationary members engage the snow covered surface to inhibit movement of the transport sled.

A method and system for monitoring low-temperature rain, snow, and freezing in complex terrain areas comprises the following steps: Step 1: Collecting satellite observation data of the monitoring area for large-scale monitoring of cold air movement, snow cover, and surface temperature, and identifying lower atmospheric inversion layer data; Step 2: Obtaining atmospheric vertical structure data through a ground-based remote sensing vertical observation system; Step 3: Collecting image data of the monitoring area through UAV-based remote sensing; Step 4: Deploying ground data acquisition units to collect data including rainfall and snowfall, snow thickness, temperature, road icing, and power line icing; Step 5: Collecting historical disaster data for the monitoring area; Step 6: Cleaning, fusing, and extracting features from various data using machine learning algorithms; Step 7: Constructing an assessment model reflecting low-temperature rain, snow, and freezing disasters based on the extracted feature data, and generating prediction results for low-temperature rain, snow, and freezing natural disasters in the monitoring area.

The invention relates to the technical field of ice and snow surveying and mapping, and discloses an unmanned aerial vehicle refined surveying and mapping method for natural ice and snow surface digital elevation. According to the method, a surveying and mapping area is deconstructed into an airspace flight layer, an ice and snow covering layer and a bedrock terrain layer; unmanned aerial vehicle flight attitude parameters and illumination intensity distribution data of an airspace flight layer are obtained, and a multispectral image sequence and a laser point cloud data set of an ice and snow covering layer are collected according to the data; performing multi-resolution adaptive decomposition on the laser point cloud data set to generate an ice and snow layer point cloud data component set, and extracting ice and rock junction spectral features in combination with a multi-spectral image sequence; predicting a reference elevation model based on the features and bedrock terrain layer historical data, calculating an elevation residual value of an ice and snow layer point cloud data component set and the reference elevation model, identifying and eliminating abnormal point cloud data according to a preset terrain anomaly criterion, reconstructing an ice and snow surface point cloud topological structure, and generating a digital elevation surface model in combination with a multispectral image sequence. And high-precision and refined surveying and mapping of natural ice and snow surfaces can be realized.

The application relates to the technical field of solar energy equipment, in particular to a solar energy curved surface heat collector capable of automatically positioning a heat source, which comprises rotating columns, the upper ends of the rotating columns are uniformly fixedly connected with supporting rods, the upper ends of the supporting rods are uniformly fixedly connected with fixing rings, and the inside of the fixing rings is fixedly connected with heat receiving pipes; the lower ends of the rotating columns are uniformly fixedly connected with fixing plates, the two sides of the fixing plates are fixedly connected with supporting frames, the upper ends of the supporting frames are fixedly connected with curved surface boxes, and the inside of the curved surface boxes is movably connected with reflecting plates. The snow removing mechanism comprises heating plates, the inside of the curved surface boxes is fixedly connected with the heating plates at the lower ends, and the upper ends of the heating plates and the reflecting plates are uniformly fixedly connected with springs; the snow removing mechanism arranged in the curved surface boxes can effectively remove the snow covering the reflecting plates in heavy snow weather, the light cannot be reflected to the heat receiving pipes due to the snow covering the reflecting plates, and the heat receiving medium in the heat receiving pipes is prevented from being affected by the snow.

This invention discloses a method for heat regulation of snow shelters based on snow-covered feature image recognition, belonging to the field of image recognition technology. The method includes the following steps: acquiring a continuous image brightness change sequence of the snow shelter surface; extracting brightness values ​​at different time points for the same spatial location; constructing a brightness time evolution matrix corresponding to each spatial location to characterize the change law of the snow shelter surface brightness over time; and based on the brightness time evolution matrix, trajectories are marked for regions where the brightness shows a continuous decreasing trend in the time dimension and a continuous translation feature in the spatial dimension, forming a shadow migration region sequence. This invention eliminates dynamic shadow interference by constructing a brightness time evolution matrix, avoiding heat distribution shifting with shadows, and achieving accurate identification and stable heating of the actual snow-covered area. Simultaneously, it dynamically monitors the melting trend during heating, increasing heat intensity when stagnation occurs to suppress ice shell formation and improve operational safety.

The application discloses a metal roof snow melting method, device, equipment, medium and product. The method comprises the following steps: receiving the temperature of the metal roof collected by the temperature sensor and the snow cover information of the metal roof collected by the color recognition device, wherein the snow cover information comprises a snow cover area, a snow cover position and a snow amount; generating a snow melting instruction according to the temperature of the metal roof, the snow cover area, the snow cover position and the snow amount, and sending the snow melting instruction to a snow melting device, so that the snow melting device executes the snow melting instruction. Through the technical scheme of the application, the problem that the roof structure is damaged or even collapses due to excessive snow can be solved.

This invention discloses a method for improving snow cover in the Noah-MP land surface process model considering topographic effects. The method includes: calculating topographic factors within the study area based on digital elevation model data, including a slope-aspect composite factor, a topographic shading factor, and an altitude correction factor; calculating a comprehensive topographic influence factor and a topographic enhancement factor based on the topographic factors; dynamically calculating the critical snow depth using the comprehensive topographic influence factor to obtain a dynamic critical snow depth; calculating a baseline snow cover using the dynamic critical snow depth; and then enhancing and correcting the baseline snow cover using the topographic enhancement factor to obtain a topographically sensitive snow cover. This invention significantly improves the model's simulation performance in complex terrain areas by coupling multi-source topographic factors, dynamically adjusting the critical snow depth, and correcting the snow cover, while simultaneously feeding the improved snow cover back into albedo and radiation calculations.

The application discloses an assembled steel corrugated plate structure snow shed tunnel, and relates to the technical field of shed tunnels, which comprises a shed body, a snow cover monitoring and removing mechanism and a snow accumulation pushing mechanism. Through the arrangement of the snow cover monitoring and removing mechanism, the gravity of the snow on the arc-shaped snow cover plate can drive the shed body to start operating synchronously, the traction rope is rotated and stored or released, the sliding rod can slide above the arc-shaped snow cover plate, the snow removal brush and the snow shovel plate can be attached to the outer surface of the arc-shaped snow cover plate to remove the snow on the outer surface of the arc-shaped snow cover plate, the snow accumulation can be completely and uniformly removed, the working efficiency is improved, the cleanliness after snow removal is ensured, and when the snow accumulation reaches a certain degree, the gravity of the snow naturally triggers the start of the mechanism, manual intervention or external signals are not required, the snow accumulation is prevented for a long time, and the structural pressure or safety hazards caused by excessive snow accumulation are reduced.

The invention provides an intelligent ice and snow removing system for a solar panel of solar power supply equipment. The intelligent ice and snow removing system comprises a control system, at least one cleaning execution unit and at least one environment monitoring sensor arranged on each photovoltaic module or a collection position of the photovoltaic modules, the environment monitoring sensor is used for collecting state information of a covering object on the surface of the photovoltaic module and comprises a physical cleaning module and a hot ice melting module. Through combination of the temperature and humidity sensor and image recognition, the system can accurately judge the ice and snow covering type, thickness and area on the surface of the solar panel, intelligent cleaning triggering based on the actual state is achieved, and maloperation or missing movement is avoided. Two cleaning mechanisms of physical cleaning and liquid ice melting are integrated, a single or combined cleaning mode can be selected according to the ice and snow types and severity, and the cleaning efficiency and adaptability are improved. A user can check the state of the solar panel in real time through a mobile phone or a monitoring platform, set a cleaning strategy or manually start cleaning, and the operation and maintenance convenience and response speed of the system are improved.