120 results about "Severe weather" patented technology

According to the multi-source information fusion robot positioning method and system for the unstructured environment provided by the invention, fusion processing is carried out on multi-source information data such as laser point cloud, environment image information and acceleration which are acquired in real time, so that the multi-source information fusion robot positioning method and system for the unstructured environment can be realized in a severe weather state and a dynamic unstructured environment. Carrying out high-robustness real-time positioning under the condition of violent illumination change; in a geometrically degraded roadway area, registration positioning of laser point cloud emission fails due to lack of enough external characteristics, and at the moment, the visual positioning module can still work normally and complete robot repositioning by detecting matched image information; in an environment lacking enough illumination, the laser point cloud and acceleration information can still provide enough positioning fusion data input for the computing unit.

The present application discloses a method, system, and computer system for detecting inclement weather driving conditions. The method includes obtaining an image captured by a camera mounted to a vehicle, determining a classification for road and weather conditions using a condition prediction model to analyze the image, in response to determining that the classification for road and weather conditions matches a particular predefined road and weather classification, determining an active measure associated with the particular predefined road and weather classification, and causing the active measure to be performed.

The application relates to a photovoltaic power station AI identification and vectorization method based on sub-millimeter images, which comprises the following steps: acquiring and preprocessing multi-modal image data of a target area; fusing the preprocessed data in multiple modes, identifying photovoltaic panel abnormalities and faults based on a fusion feature map, and grading to generate a pixel-level segmentation mask, feedback error, and obtain an abnormality identification result; combining the abnormality identification result, the fusion feature map and the preprocessed multi-modal data to complete implicit fault confirmation, grading, tracing and trend judgment; inputting the segmentation mask, fault contour and fusion feature map to a coordinate calibration module, calibrating the coordinates combined with the spatial features of the fusion data to obtain calibrated coordinates; and based on the calibrated coordinates, the abnormality identification result and the fault contour, extracting the contour, associating the attributes and converting them into a standard vector format. The application improves the identification accuracy under complex terrain and severe weather, simultaneously realizes accurate grading and judgment of abnormal areas such as photovoltaic panel damage and shielding, and provides direct data support for power station operation and maintenance.

The application provides a millimeter wave radar and video fusion tower clearance real-time monitoring method, which comprises a video monitoring camera system and a millimeter wave radar system; first, the two systems are installed at the bottom of the cabin and rotated to point to the blade clearance area, realizing image acquisition and radar reflection point data acquisition in the blade movement cycle; then the controller system calculates the blade tip clearance value according to the collected image data and radar reflection points, qualitatively evaluates the deviation of the two according to the spatial relationship between the blade tip trajectory line and the blade tip reflection point, and ensures the high-precision clearance monitoring of the blade tip and the tower. The clearance monitoring method of the fusion of the two sensors can realize the functions of mutual checking of the accuracy between the systems in normal weather, selection of the clearance for unit control in severe weather, stronger environmental adaptability and working condition adaptability, and avoids the problems of failure of a single sensor due to environmental influence or low clearance accuracy.

This invention discloses a geological disaster rainfall monitoring and early warning device, belonging to the field of geological disaster monitoring technology. It includes a liquid level sensor, a water pump, a motor, and a base plate. The base plate is slidably fitted onto the lower end of a square rod, and multiple first anchor rods are inserted and installed on the base plate. A cylinder is fixed to the top of the square rod, and an upper rod body is fixed to the upper end of the cylinder. A rotating wheel and a bevel gear ring are rotatably mounted on the cylinder, and the bevel gear ring is fixedly installed to the bottom surface of the rotating wheel. Two lead screws are symmetrically rotatably mounted on the side of the square rod near the top. The top ends of the lead screws mesh with the bevel gear ring for transmission. This invention enables convenient rainfall monitoring and allows for adjustment of its installation height as needed. After installation, it can better cope with severe weather such as strong winds and heavy rains, ensuring that the device can safely and stably monitor rainfall. Furthermore, it allows for convenient cleaning of photovoltaic panels, ensuring their high power generation efficiency.

This invention relates to an adaptive severe weather image restoration method based on continuous testing, belonging to the field of computer vision and image processing technology. It includes the following steps: constructing a severe weather dataset and dividing it into training and testing sets; constructing a severe weather image restoration framework, including a pre-trained model DA-CLIP, a student model, and a teacher model; inputting the publicly available dataset into the pre-trained model DA-CLIP for training, and initializing the student and teacher models using the parameters of the trained DA-CLIP model; inputting the training set of the severe weather dataset into the student and teacher models respectively for model training and optimization, obtaining a trained severe weather image restoration framework; inputting the test set images of the severe weather dataset into the trained severe weather image restoration framework to obtain the image restoration result. This invention can improve the model's image restoration performance under complex and realistic weather conditions.

This invention relates to the field of precast box culvert construction technology, specifically a precast box culvert construction method, including the following steps: construction preparation, rebar processing and binding, formwork installation, concrete pouring, concrete curing, culvert section storage, transportation and installation, and joint and waterproofing treatment. This invention has the following advantages: It employs centralized precasting in a closed shed, effectively avoiding the impact of severe weather such as strong winds, rain, and snow on culvert section construction; the culvert sections are precast horizontally, reducing construction difficulty; and the use of sleeves to connect the main reinforcing bars avoids the adverse effects of strong winds on welding quality during arc welding. Furthermore, the use of an adjustable rebar binding platform enables rapid and precise rebar binding, ensuring the quality of the rebar binding spacing and protective layer. This effectively solves the binding difficulties caused by the variety of rebar types and limited space in culvert sections.

The invention provides a vehicle scene reconstruction method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring image data acquired by a vehicle, multi-frame millimeter wave radar data and inertial measurement unit data; when it is recognized that the weather state of the environment where the vehicle is located is severe weather, the severity level of the severe weather is determined; according to the severity level, performing fusion processing on the multiple frames of millimeter wave radar data to obtain accumulated radar data; performing enhancement processing on the accumulated radar data to generate enhanced radar data; performing dedegradation processing on the image data according to the enhanced radar data to generate an enhanced image; and generating three-dimensional scene reconstruction data of the surrounding environment of the vehicle according to the enhanced image, the enhanced radar data and the inertial measurement unit data. Therefore, a stable and accurate three-dimensional scene reconstruction result can be output in severe weather.

This utility model discloses a conveniently assembled and disassembled photovoltaic sunflower device, relating to the field of photovoltaic power generation technology. It includes a photovoltaic base, the top of which is equipped with multiple sets of petal-shaped photovoltaic panels via an electrically operated cornering platform. The bottom of the photovoltaic base is equipped with a positioning seat assembly pre-embedded in the ground. The positioning seat assembly includes a pre-embedded frame, within which a positioning plate slidably mounted on the bottom of the photovoltaic base. This utility model, through the positioning seat assembly, ensures that the top of the photovoltaic sunflower is at a suitable horizontal height, eliminating the need for manual disassembly and assembly of the petal-shaped photovoltaic panels, thus facilitating subsequent disassembly and maintenance. It also lowers the center of gravity of the photovoltaic sunflower, making it better able to withstand severe weather. Furthermore, the frame and inner lining plate protect the petal-shaped photovoltaic panels from damage caused by falling objects during severe weather, extending the device's service life.

The utility model discloses a kind of wind pressure resistance reinforcing structure of broken bridge aluminum door and window, belong to aluminum door and window reinforcing technical field, the inside of first frame body is equipped with protruding frame, the corner of protruding frame is equipped with first limit strip, first limit groove for clamping is formed between multiple first limit strips, the middle section of protruding frame is equipped with abutting arc part, and inner groove is formed in the inside of abutting arc part;The inside of second frame body is equipped with inner boss, and the corner of inner boss is equipped with second limit strip. By first, second limit groove clamping cooperation, and the reinforcing rib structure of oblique support strip, insertion strip and abutting strip composition, improve broken bridge aluminum door and window wind pressure resistance performance, make it keep stable under severe weather. First, second frame body and its related components integrated design, reinforcing structural stability, reduce security risk. Abutting arc part and opening cover and other components design, stable structure, ensure that door and window long-term stable durable, prolong service life.

This invention discloses a method for synthesizing severe weather lidar point clouds by combining real priors with geometrically guided intensity generation. First, a weather simulation module is used to convert clear weather data into pseudo-severe weather data with physical constraints from the statistical regularities of real datasets, constructing a high-quality training set. Then, using a structure-intensity decomposition diffusion model, a high-fidelity geometric structure is generated first through an asymmetric conditional diffusion process, and then matching reflection intensity information is generated based on the structure. This method effectively overcomes the modeling difficulties caused by geometry-intensity coupling in existing technologies, and achieves high-fidelity severe weather point cloud synthesis in the absence of large-scale real data.

The application discloses a kind of robust camera-lidar multimodal contrast pre-training method and system of anti spacetime bias.The method comprises: generating distance projection map to lidar point cloud;Multi-scale representation is extracted using image encoder and distance projection map encoder respectively;The hierarchical alignment of global vector and regional level block vector is completed by semantic perception branch and geometric perception branch;Space consistency constraint and sparsity regularization are introduced to suppress the representation collapse of low information area;Multi-scale attention aggregation is used to form the final cross-modal representation and is trained with bidirectional contrast loss, and finally a general camera-lidar data representation with robust migration capability for downstream three-dimensional perception tasks is obtained.The method of the application can more robustly provide fused features for downstream three-dimensional perception tasks, and the features can be extended to various severe weather scenarios and road conditions, improving the reliability of autonomous driving in severe scenarios.

The utility model discloses a bench based on solar power supply relates to the field of public facilities, to solve the inconvenient use of prior art under the severe weather condition. The bench board upper end face groove installs solar panel, and the bench board lower end one side installs the storage box, and the storage box installs the singlechip, inverter and battery, and solar panel, inverter and battery are electrically connected in proper order, the bench board upper end is close to the storage box one side and is equipped with the rainwater sensor, and the output of rainwater sensor is connected with the input of singlechip, the bench rear end is equipped with the rain -proof subassembly, and the rain -proof subassembly includes first side fixed plate, and the first side fixed plate between two installs the rolling up pole along the output shaft end of drive box, and the rain -proof canopy is rolled up outside the rolling up pole, and the other end of rain -proof canopy is fixed with fixed shaft.

This invention relates to the technical field of seedling support, and discloses a fixing device for assisting the growth of municipal landscaping seedlings. The seedling support mechanism includes: several support units arranged around the seedling, with the lower end of each support unit resting on the ground; fixing wires that secure the seedling and the support units; each support unit further includes: an arc-shaped clamping block abutting against the side wall of the seedling, with the fixing wire securing the clamping block to the seedling; and a ground-mounted box, placed on the ground, with a sliding seat slidably mounted on the inner wall of the ground-mounted box near the opening via two sliding rods, and a balancing block at the upper end of the sliding seat. This fixing device for assisting the growth of municipal landscaping seedlings does not hinder the upward extension of the seedlings. In severe weather, when the seedlings are blown by strong winds, the multiple sets of support units arranged in a circular array provide excellent support and fixation for the seedlings.

This invention provides a multimodal incremental railway fastener defect detection method and system under severe weather conditions, belonging to the field of target recognition technology. Step 1: Sequentially construct training and validation sets for multimodal railway fasteners under rain, snow, fog, strong light, low light, and normal weather conditions; construct a global test set containing multimodal railway fastener data for all six weather conditions. Step 2: Construct a full-cycle closed-loop mechanism for multimodal target detection to achieve continuous learning in continuously evolving scenarios. Step 3: Propose a dual-space replay screening strategy for meta-features to extract challenging and representative high-value samples for inclusion in the replay pool. Step 4: Propose a wavelet-guided non-adversarial detail injection module to resolve the adversarial conflict between noise removal and style preservation in incremental learning. This invention can continuously adapt to various severe weather changes in railway scenarios, effectively alleviate the problem of catastrophic forgetting, and achieve accurate detection of fastener defects under various severe weather conditions.

This utility model discloses a protective device for a building deformation monitoring equipment, belonging to the technical field of monitoring equipment. It includes a building wall. Through the installation of protective components, the deformation monitoring equipment body is quickly installed inside a protective housing. The protective housing protects the internal deformation monitoring equipment body from damage caused by rain, severe weather, or other factors. It also prevents the internal sensor components from corroding due to contact with rainwater, thus ensuring the accuracy of the monitoring data and enabling the equipment to perform its monitoring function normally. The support rollers on both sides and the second damping shock-absorbing spring reduce damage to the deformation monitoring equipment body from external impacts. The shock-absorbing rod and the first damping shock-absorbing spring at the bottom effectively absorb vibrations caused by building deformation, preventing damage to the monitoring equipment due to vibration and extending the equipment's service life.

The application relates to a power transmission line fault maintenance method and system under severe weather. The method comprises the following steps: performing baseline correction on a traveling wave current signal to identify a wave peak interval corresponding to the traveling wave, determining the symmetry deviation of the wave peak interval according to the difference between the trend item components of two sequences, screening a plurality of suspected fault traveling waves according to the fitting goodness of each wave peak interval, the shape similarity between the two sequences and the symmetry deviation, determining the spatial similarity according to the similarity between each suspected fault traveling wave and a plurality of suspected fault traveling waves at the opposite end, determining the incident waves at both ends of the power transmission line according to the energy intensity of the wave peak interval and the spatial similarity, correcting the initial speed of the incident wave according to the preset corresponding relationship and the main frequency of each incident wave, and positioning the fault point according to the corrected speed and the arrival time of the corresponding incident wave. The method improves the fault positioning accuracy and reliability, and reduces the operation and maintenance difficulty of the power transmission line.

The application discloses a dual-polarization weather radar speed ambiguity resolution method based on lag-1 cross-correlation, which utilizes lag-1 cross-correlation of adjacent radial directions instead of radial velocity of the adjacent radial directions in a traditional algorithm to calculate an ambiguity resolution reference speed. This makes the ambiguity resolution speed range of the ATAR mode expand to twice that of the traditional algorithm, so that the speed measurement range is consistent with that of the single-polarization mode. Application of the algorithm improves the reliability of speed data of the ATAT mode weather radar in severe weather detection.

The application relates to the technical field of image cleaning, and particularly discloses a power transmission and transformation equipment image enhancement and defect identification method for severe weather, the image enhancement method comprising the following steps: collecting power transmission and transformation equipment image quality data and environment data at each image acquisition time through a data acquisition module; combining the environment data at each image acquisition time to clean and correct the quality data of the power transmission and transformation equipment image, so that the reliability and rationality of the power transmission and transformation equipment image quality data are improved, the accuracy of calculating the haze influence index of the power transmission and transformation equipment image at each image acquisition time is improved, and the rationality of the haze influence degree evaluation result at each shooting time is improved; on the basis, the contrast of the image is compensated by combining the haze influence index with high accuracy, so that the distinguishing degree of the power transmission and transformation equipment and the background is enhanced, the accuracy of subsequent image defect identification is improved, and the power transmission and transformation equipment image is enhanced.

The disclosed invention pertains to a rain deflector apparatus designed to minimize water intrusion into sliding glass door tracks or similar structures. The deflector, with an innovative geometry, attaches securely to the door track, creating a sealing pressure against the floor and door. Its substantially flat sheet body incorporates a bottom seal portion and a top sealing surface, ensuring effective water diversion. The deflector can be part of a configurable system or a kit for customized assembly. The objectives include reducing water intrusion during severe weather, easy installation and removal, rigidity for shape maintenance, compliance for sealing force, and accessibility for regular door use. This rain deflector system presents a practical solution for varied structures, enhancing protection and user convenience.

The utility model discloses a kind of power transmission line monitoring devices suitable for severe weather, comprising: mounting bracket, solar panel assembled in the top of mounting bracket by mounting unit and camera assembled in the bottom of mounting bracket, mounting bracket includes vertical first installation pipe, the mounting unit includes the mounting frame fixedly connected with solar panel, the mounting sleeve that can be set in the top of first installation pipe with mounting frame fixedly connected and clamp mechanism assembled on the lower end of mounting sleeve and can hold first installation pipe, the top end outer wall of first installation pipe is coaxially recessed with annular groove, at least one limiting bolt passing through annular groove is assembled on the mounting sleeve, by annular groove and limiting bolt cooperation, it can prevent mounting sleeve from falling, to adapt to strong wind environment, also convenient to adjust the direction of solar panel, the clamping force provided by clamp mechanism is greater than the clamping force of commonly used bolt lock, further mentioned wind resistance.

This application relates to a spatial downscaling method for meteorological element fields based on a retrieval and diffusion generation model. This method generates corresponding high-resolution meteorological element fields from low-resolution meteorological element field sequence samples. By constructing a retrieval mechanism, a high-resolution reference meteorological element field related to the current input sample is obtained from a historical high-resolution meteorological element field database. The target high-resolution meteorological element field is then progressively reconstructed using a diffusion generation process. Simultaneously, physical consistency constraints are introduced to achieve spatial downscaling of the meteorological element field while balancing generation quality and physical plausibility, thus improving the refinement, stability, and physical plausibility of the spatial downscaling results. This method is applicable to various meteorological element fields, multi-source meteorological data, and various complex regional scenarios. It has strong scalability and application value, and can be used for refined weather forecasting, meteorological analysis of complex terrain, monitoring and early warning of severe weather, aviation meteorological support, and related intelligent meteorological operational scenarios.

The application discloses a method for calculating input wind speed of a unit in a sea wind farm considering the influence of sea waves, belongs to the technical field of wind speed calculation, and is used for calculating input wind speed of a unit in a sea wind farm. The method comprises the following steps: reading position coordinate parameters of wind turbines in the wind farm, reading input wind speed and wind direction of the wind farm, performing coordinate transformation on the wind farm according to the wind direction, and calculating a shielding coefficient between the wind turbines; obtaining sea surface roughness and friction velocity, and calculating wind speed of each region in combination with an AV wake model; calculating input speed of each wind turbine, judging whether a wind parameter sequence is ended, and if yes, ending, and if not, returning to reading input wind speed and wind direction of the wind farm. The wind farm wake model established by considering the influence of sea surface roughness caused by large waves and huge waves in severe weather can more accurately calculate the input wind speed of the unit in the wind farm, and proves that the application has strong rationality and provides strong support for subsequent wind farm power prediction.

Optical images in remote sensing are contaminated by cloud cover and bad weather conditions and are only available during the daytime. Whereas SAR images are completely cloud free, independent of weather conditions and can be acquired both during the day and at night. However, due to the speckle effect and side looking imaging mechanism of SAR images, they are not easily interpretable by untrained people. To address this issue, the present disclosure provides a method and system for LULC guided SAR visualization, wherein a GAN is trained to translate SAR images to optical images for visualization. A given SAR image is fed into a first generator of the GAN to obtain LULC map which is then concatenated with the SAR image and fed into a second generator of the GAN to generate an optical image. The LULC map provides semantic information required for generation of more realistic optical image.

This utility model discloses a nested optical cable distribution box, including a box sleeve with a receiving cavity. A door panel is installed on the front of the box sleeve, and the back of the box sleeve is hollowed out to form an open structure communicating with the receiving cavity. The box sleeve has a cable inlet hole and an optical cable clearance notch communicating with the cable inlet hole. When the original optical cable distribution box becomes damaged due to human error or environmental reasons, it is not necessary to dismantle the entire box structure. The box sleeve of this utility model can be directly nested over the original box. The box sleeve has stronger protective capabilities, resisting external threats such as severe weather, animal bites, and human damage. When the door panel is closed, the box sleeve presents the same appearance as a new box, improving the overall aesthetics. Installation and use are convenient, and the installation process does not affect the original box's business functions.