544 results about "Bad weather" patented technology

The invention relates to the field of channel management, in particular to an intelligent channel management method and system based on multi-source data fusion. The invention discloses an intelligent navigation channel management system based on multi-source data fusion. The system comprises a combined ship identification module, a positioning frequency updating module, a collision risk assessment module and an intervention management module. According to the invention, the system can sense multi-dimensional environmental parameters such as illumination intensity, visibility, AIS signal quality, radar echo signal-to-noise ratio and the like in real time by constructing a combined ship identification model containing AIS, radar, vision and infrared, and dynamically adjust the fusion weight of each sensor to compensate for the deficiency of a single sensor; according to the method, the robustness of ship dynamic monitoring is improved, high-precision tracking can be kept in severe weather, the data redundancy contradiction of a traditional multi-sensor system is avoided, and therefore continuous and stable target state input is provided for follow-up risk analysis.

The invention discloses an oil field power distribution network operation safety violation behavior deep learning recognition system. The system comprises a video acquisition module, a data preprocessing module, an improved YOLO model module, a violation behavior judgment module and a result output module. The video acquisition equipment is distributed in a key area of an oil field site and transmits video data to the server through a wireless network; the data preprocessing module adopts histogram equalization and sharpening operation to enhance the image contrast. The improved YOLO algorithm model is subjected to customized training, and behavior actions of operators and equipment can be accurately recognized. And the illegal behavior judgment module performs matching judgment on the result output by the model in combination with the safety specification of the oil field operation. According to the method, the difficult case mining technology and the multi-stage training strategy are adopted, the judgment capability of the model on illegal behaviors under complex conditions is improved, the OpenCV technology is combined, the capability of the system for coping with light changes and severe weather conditions is enhanced, and the recognition accuracy under different illumination intensities is ensured.

The method focuses on the technical field of communication, and the communication connection problem under the cooperative operation scene of the unmanned vehicle and the unmanned aerial vehicle is accurately positioned. In practical application, communication connection is troubled by a complex environment, signals are prone to strong interference, the transmission distance is obviously limited, and double requirements of real-time performance and accuracy are difficult to consider in the aspect of data transmission characteristics during cooperative operation of the two. According to the invention, ZigBee, 5G, satellite communication modules and multi-mode communication modules are integrated, an adaptive protocol is optimized, channels are sensed in real time, the channels are selected and switched through an intelligent algorithm, signals are enhanced through directional antennas and beam forming, interference resistance is realized through adaptive filtering and error correction coding, and stability is guaranteed by means of link monitoring and a self-healing mechanism. According to the method, reliable interaction of data between the unmanned vehicle and the unmanned aerial vehicle in a complex environment can be ensured, and real-time and accurate transmission of monitoring data can be ensured even in case of strong electromagnetic interference or severe weather.

The invention, which relates to the technical field of highway traffic safety monitoring, discloses an expressway pavement ice condensation monitoring system comprising a data acquisition module for acquiring environmental data and pavement icing state information on an expressway pavement; and the self-calibration module is connected with the data acquisition module, performs self-calibration on the data acquisition module according to the environment data acquired in real time and the road surface icing state information, and corrects sensor errors caused by external environment factors. According to the highway pavement ice condensation monitoring system, a self-calibration function is added in monitoring equipment and an intelligent algorithm is introduced, so that the monitoring system can automatically correct measurement errors caused by external environment changes in real time, and a machine learning model is combined to predict pavement conditions more accurately; the working stability of the system in severe weather can be improved, and the risk of icing of the road surface can be found earlier, so that more accurate early warning information is provided for a traffic management department, and the probability of traffic accidents is reduced.

The invention provides a road inspection method and device in severe weather, electronic equipment and a storage medium, and the method comprises the steps: carrying out the recognition processing of a scene image through a road inspection model, and obtaining a road inspection result of a target road; the training process of the road inspection model comprises the following steps: acquiring a data set, wherein the data set comprises a severe weather image; performing feature extraction on the data set by adopting a pyramid network to obtain a plurality of levels of first feature extraction results; when information fusion is carried out on the first feature extraction results of the multiple levels, feature adaptation processing is carried out according to the first feature extraction results, and a second feature extraction result is obtained; performing feature enhancement modulation on the second feature extraction result by adopting double branches, and merging feature enhancement modulation results to obtain a modulation feature map; and predicting the modulation feature map to obtain a prediction result. The method has the beneficial effect that the vehicle type identification accuracy during road inspection in severe weather is improved.

The invention discloses a road traffic information monitoring system and method, and the method comprises the steps: deploying a video monitor, a sensor, an unmanned plane and a satellite device to collect real-time road traffic data, and protecting the data safety through encryption transmission and multilayer identity authentication; the flow is monitored in real time by combining image recognition and sensor data, congestion is analyzed, traffic violation is recognized, and an alarm is given; future flow is predicted through machine learning and big data analysis, and the signal lamp period is intelligently adjusted; through combination of real-time and historical data, accident risk points are identified and early warning is carried out, and early warning is automatically issued and adjustment and control are carried out for severe weather. The AI technology automatically identifies accidents and notifies a management center, dispatches emergency resources, optimizes signal lamps and lane traffic, and dynamically adjusts surrounding flow; according to the road traffic information monitoring system and method, an automatic emergency processing system is established, accidents are automatically detected and alarms are triggered under the conditions of traffic accidents and emergencies, and emergency resources are quickly dispatched.

The invention discloses a one-stage severe weather fruit detection method based on dynamic coding, and the method comprises the steps: collecting fruit image data on site in an agricultural scene, carrying out the data preprocessing of the collected image data, setting the hyper-parameters of a to-be-constructed one-stage severe weather fruit detection model based on dynamic coding, and carrying out the calculation of the hyper-parameters of the to-be-constructed one-stage severe weather fruit detection model. Constructing and training a first-stage severe weather fruit detection model based on dynamic coding; detecting fruits in the test set image, outputting a detection result mask, and comprehensively evaluating the model; the method solves the problems of poor generalization and applicability, tedious steps of a monitoring method and low real-time performance in the prior art, and has the characteristics that accurate detection can be carried out without pre-processing the image, and the training time and tedious steps of image pre-processing are reduced.

The invention discloses a wind power generation device with a heat dissipation mechanism, and relates to the technical field of renewable energy sources, the wind power generation device comprises a box body, a power generator is arranged in the box body, a gear box is arranged on the inner wall of the box body, after fan blades are driven by wind power, the power generator converts high-speed rotating mechanical energy transmitted by the gear box into electric energy, and the electric energy is transmitted to the heat dissipation mechanism. The heat dissipation nets need to be cleaned after being used for a long time, manual cleaning work cannot be carried out under the severe weather condition, the heat dissipation nets are possibly not cleaned in time, normal operation of the wind power generation device is affected, the heat dissipation nets are cleaned through the scraper blades through wind power, and the heat dissipation efficiency of the three heat dissipation nets is further improved. After the scraping plate is used for a long time, a large number of impurities can be attached to the surface of the brush, the brush can vibrate through striking of the striking rod, and therefore dust and the impurities on the brush are shaken off and prevented from polluting the heat dissipation net again.

The invention discloses a low-speed unmanned vehicle artificial intelligence decision and performance evaluation system, and belongs to the technical field of low-speed unmanned vehicle scheduling, and the system comprises a generation module which is used for generating a scene novelty index through monitoring the instantaneous offset of an environment parameter; the topology module is used for constructing a dynamic scene topology according to the scene novelty index, and the dynamic scene topology comprises nodes and edge weights generated based on the scene novelty index; the decision-making module is used for converting the edge weight into a decision-making rule according to the dynamic scene topology and generating a decision-making strategy; the performance calculation module is used for tracking the deviation between the vehicle motion parameter and the control instruction during the execution of the decision strategy to calculate a performance disturbance coefficient; and a topology calibration module. The method can effectively adapt to unrecorded edge scenes such as sudden congestion and severe weather superposition, improves the generalization ability of a system to complex scenes exceeding a pre-training range, and reduces decision errors caused by insufficient scene adaptation.

The invention relates to the technical field of photovoltaic panels, and discloses a photovoltaic panel assembly with wind pressure resistance, which comprises a protection frame, one side of the protection frame is fixedly connected with a protection plate, the inner wall of the protection plate is fixedly provided with a wind speed sensor, two sides of the protection frame are both provided with a plurality of ventilation slots, and the protection frame is internally provided with a protection assembly; the protection assembly comprises two first sliding grooves, the two first sliding grooves are formed in the two sides of the inner wall of the protection frame correspondingly, first sliding blocks are slidably connected into the first sliding grooves, and telescopic frames are rotatably connected to one sides of the first sliding blocks. According to the invention, the photovoltaic panel assembly can automatically retract into the protection frame in strong wind severe weather, the phenomenon that the photovoltaic panel is unstable due to the loosening and falling of parts is reduced, the service life is prolonged, the pressure generated by strong wind is conveniently buffered, the strong impact and damage to the photovoltaic panel assembly and the parts thereof are reduced, and the service life of the photovoltaic panel assembly is prolonged. Therefore, the maintenance cost is reduced.

The utility model relates to a submarine cable state on-line monitoring system, which belongs to the technical field of cable protection equipment and comprises a submarine cable temperature monitoring module, a submarine cable breakdown fault response module, a submarine cable surrounding environment monitoring module, a marine monitoring ship body, a submarine cable environment display module and a submarine cable GIS module. Two supports are fixedly installed at the top end of the marine monitoring ship body, and a wireless signal transceiver is fixedly installed at the top of the marine monitoring ship body. The device has the beneficial effects that the two U-shaped frames can be driven to move in the same direction or opposite directions through the rotation of the two-way screw rod, and then the canopy outside the U-shaped frames can be driven to unfold, so that each part on the marine monitoring ship body is prevented from being eroded by rainwater or severe weather, and the service life of the marine monitoring ship body is prolonged. And therefore, protection can be provided for components on the marine monitoring ship body, and the service life of the components on the marine monitoring ship body can be prolonged.

The intelligent robot comprises a ship body, a garbage can used for storing garbage and a power module used for driving the ship body to advance, a material collecting opening is formed in the front portion of the ship body in the advancing direction, and the power module is arranged on the rear portion of the ship body in the advancing direction; a mounting opening is formed in the top of the ship body, the garbage can is detachably mounted on the ship body through a quick release mechanism, and the garbage can is provided with a feeding opening opposite to the collecting opening; a battery module for supplying power to the power module is arranged at the bottom of the ship body, and a water-cooling heat dissipation mechanism is further arranged on the battery module. The robot can work for a long time, the maintenance and operation cost is far lower than the cost of employment of cleaning personnel for a long time, meanwhile, the cleaning risk of manual work in a deep water area or in severe weather is effectively reduced, the cleaning efficiency of lake surface garbage is improved, and the safety is also improved.

The invention relates to the technical field of public electronic screens, in particular to a public electronic screen protection device capable of adapting to complex weather. Comprising a base and a lower support fixed to the upper surface of the base, and a controller is installed in the base. Through the cooperative design of the electronic screen shell, the sun shield, a transmission mechanism, an electromagnetic adsorption mechanism, a meshing mechanism, a reset mechanism and a limiting mechanism, the sun shield can be rotated to be attached to the electronic screen shell by controlling a second motor and a first motor to rotate forwards in extreme weather such as hail or strong wind; the electronic screen shell is attached to the lower support, then the electronic screen body and the solar panel can be rotated to the position of the lower support, the electronic screen shell and the air deflector are exposed outside, the electronic screen body and the solar panel can be protected, the situation that the electronic screen body is smashed by heavy sundries carried by hail or strong wind is avoided, and the service life of the electronic screen is prolonged. And the safety of the electronic screen body in severe weather is greatly improved.

The invention discloses an automobile laser radar point cloud semantic intelligent completion method in rainy and foggy weather, and particularly relates to the technical field of automatic driving perception. The method comprises the following steps: firstly, collecting time sequence point cloud data and inertial navigation information of a vehicle under rain and fog conditions, and constructing a sparse point cloud sequence; then constructing a sparse-semantic tensor graph based on point cloud density drift, echo energy anomaly and a semantic graph, extracting context structure features through a time sequence graph neural network, and generating an affine complement containing affine transformation parameters; further realizing consistent alignment of boundaries by using a semantic drift compensation mechanism, reconstructing a false point cloud complementation frame and fusing the false point cloud complementation frame with the original point cloud, and outputting a semantic complementation enhancement frame; according to the method, the point cloud integrity and semantic precision in severe weather can be improved, the stability of obstacle detection and path planning is enhanced, and the method is suitable for a complex environment sensing scene in an intelligent driving system.

The invention relates to the field of photovoltaic technology, in particular to a photovoltaic power generation device. The technical scheme is provided. Comprising a base, a photovoltaic structure, a driving structure, a reset structure, a protection structure and a cleaning structure; the photovoltaic structure comprises a photovoltaic support and a photovoltaic panel in the upper end of the photovoltaic support. The driving structure comprises a guide wheel, a side lug at the upper end of the photovoltaic bracket, a pull rope on the outer wall of the guide wheel, a bearing bracket I and a bearing bracket II at the upper end of the base, a mounting shaft in the bearing bracket I, a worm gear on the outer side of the mounting shaft, a motor above the base and a worm at the output end of the motor; the reset structure comprises a rotating seat, a mounting rack, a rotating shaft at the lower end of the photovoltaic support, a connecting sleeve connected with the mounting rack, a ring pipe fixedly connected with the connecting sleeve, a guide ring outside the ring pipe, and an annular spring between the guide ring and the connecting sleeve. According to the invention, by arranging the driving structure and the reset structure, the photovoltaic panel is protected by turning over the photovoltaic support in severe weather such as hail, and the problem of damage to the photovoltaic module is reduced.

The invention relates to the technical field of pipeline supports, and discloses a pressure vessel pipeline supporting device. During working, firstly, one end, deviating from a guide piece, of a guide rod penetrates through a supporting plate and then is fixed through a locking piece, the fixing position of the locking piece is adjusted, and then an adjusting elastic piece is adjusted; the adjusting elastic piece applies pre-tightening force between the guiding piece and the supporting plate, and then the adjusting sleeve is installed on the adjusting rod in a matched mode. The guiding piece is installed on the outer wall of the pressure container in an abutting mode, so that a pipeline on the pressure container is arranged in the inner ring buckle, then the outer ring buckle is installed on the inner ring buckle in a buckled mode and fixed, and auxiliary supporting and stabilizing of the pipeline are completed. By adjusting the position of the locking piece, the compression degree of the adjusting elastic piece can be changed, and therefore the supporting force of the supporting and guiding assembly on the pressure container is adjusted. The supporting device can be dynamically adjusted in severe weather, supporting looseness is prevented, and the stability of pipelines of a top-heavy structure such as a pressure guiding pipe fitting on the pressure container is improved.

The invention discloses a pipeline for a thermal power plant, and relates to the field of pipelines, the pipeline comprises a first pipeline, a second pipeline and a plurality of support bases, the first pipeline and the second pipeline are welded with each other, and the joint of the first pipeline and the second pipeline is sleeved with a joint shield. It needs to be explained that in the embodiment of the invention, when collapse occurs, the extension support moves on the first pipeline or the second pipeline through the supporting frame, the fulcrum of the first pipeline or the second pipeline is extended, and then effective supporting of the first pipeline or the second pipeline is guaranteed; in severe weather, the rotating sleeve drives the rotating scraping strip to scrape the first pipeline or the second pipeline, so that the first pipeline or the second pipeline is prevented from bearing too large; besides, when leakage occurs at the joint of the pipelines, the plugging frame drives the sealing ring to seal the joint of the pipelines, the purpose of active sealing is achieved, further expansion of the notch can be effectively avoided, and continuous operation of the thermal power plant is guaranteed.

A flying vehicle with folding wings that drives well on the ground and flies well in the air; controlled from inside, it changes from automotive to aircraft configuration without the operator needing to get out of the vehicle. The balance point of the vehicle is located midway between the front and back wheels, providing good handling on the road. In the aircraft configuration with wings unfolded, there is a front wing and a back wing. The incidence of the front wing is controllable, enabling the craft to rotate and take off with a center of gravity located well ahead of the rear wheels. The back wing is fitted with foldable vertical stabilizers near its wing tips. In automobile configuration the wings are folded on top of the body; the wings resemble a roof rack with large surfboards on it. Driven wheels provide motive power on the ground; ducted fans provide thrust for air travel. An autopilot system provides stability and navigation aid, particularly in bad weather or poor visibility. In the roadable configuration, filling water ballast tanks provides additional crosswind stability and crash protection. Also in a roadable configuration, the present invention may be licensed as a three-wheeled motorcycle towing a two-wheeled trailer. In its flying configuration, the invention can be licensed as a Light Sport Aircraft.

The utility model discloses a total station bracket with a protection mechanism, belonging to the technical field of total station brackets, comprising: a mounting base and a total station body, a fixed block is fixedly mounted on the top of the mounting base, two sliding frames are slidably mounted in the fixed block, a sliding board is fixedly mounted between the two sliding frames, the total station body is fixedly mounted on the top of the sliding board, a plurality of fixed columns are fixedly mounted on the top of the sliding board, a same fixed top board is fixedly mounted on the top of the plurality of fixed columns, a motor is fixedly mounted in the mounting base, a worm is fixedly mounted on the output end of the motor, and a worm wheel is meshed on one side of the worm wheel. The utility model drives the gears to rotate through the worm wheel, controls the sliding frame and the sliding board to move through a plurality of gear transmissions, thereby moving the total station body out, and allows it to be returned to the fixed block when not in use, so that the bottom end of the fixed top board abuts against the top end of the fixed block, so that it can face relatively severe weather for better protection.

The invention discloses a one-stage multi-modal bad weather fruit detection method, which solves the problems of low real-time performance, poor generalization and the like during bad weather fruit detection by constructing a complete convolutional neural network framework, and comprises the following steps: firstly, carrying out multi-scale coding on an image and constructing a multi-scale receptive field; the method ensures that the detection method can detect targets of different sizes in an agricultural scene, encodes severe weather features in multiple scales, designs a multi-modal feature fusion module, highlights fruit-related parts in image features by using point cloud through an attention mechanism, and performs feature fusion after feature fusion. The decoder specially used for severe weather is designed to explore the features of the target under low visibility locally and fully and adaptively adjust the model, so that more attention is paid to the features of the target; accurate detection can be carried out without pre-processing the image, the training time and tedious steps are reduced, a good result is achieved in the aspects of precision and speed, and a reliable scheme is provided for agricultural scene fruit detection in severe weather.

The invention belongs to the technical field of photovoltaic equipment, and provides a roof adjustable photovoltaic module for an energy-saving building, which comprises an outer shell, the top of the outer shell is open, a lifting platform is arranged in the outer shell through a lifting assembly, an inclined frame is arranged at the top of the lifting platform through a rotary table, and a plurality of photovoltaic panels are rotatably connected in the inclined frame. A horizontal sliding assembly is arranged at the top of the rotary table and hinged to one edge of the inclined frame, and a pitching adjusting assembly is further arranged between the rotary table and the side wall of the inclined frame. And the control assembly comprises a control unit arranged in the outer shell and a sunlight tracking sensing device arranged on the inclined frame. The problem of projection shielding between the photovoltaic modules can be reduced, and meanwhile the capability of resisting severe weather such as strong wind can be improved.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle adaptive shooting method and system based on multiple sensors and AI, and the method comprises the steps: multi-sensor data collection, deep learning fusion processing, multi-modal exception processing, decision-making layer path planning reinforcement, adaptive shooting precision improvement, and a re-planning mechanism. Compared with the defects that environmental perception is incomplete and the shooting quality is suddenly reduced under complex illumination or severe weather due to dependence on a single sensor in the prior art, according to the scheme of the invention, a multi-mode sensor array (laser radar / millimeter wave radar / illumination sensor and the like) and Transform-GNN deep learning fusion architecture is adopted; joint modeling of obstacle positions, dynamic tracks and illumination distribution is realized; therefore, the dimensionality and precision of environmental perception are remarkably improved, and the unmanned aerial vehicle can still output clear and stable high-quality pictures under extreme conditions of strong light, rain and fog and the like.

The invention discloses a barrel type unmanned aerial vehicle recycling device and a recycling method thereof. The barrel type unmanned aerial vehicle recycling device comprises a main body frame and a barrel. The top of the barrel is wider than the bottom of the barrel, the bottom wall of the top of the barrel is connected with the main frame, and the bottom of the barrel extends into the main frame; a buffer net is arranged at the bottom of the barrel; and a positioning module is arranged at the bottom of the main body frame and is in communication connection with the cylindrical unmanned aerial vehicle. Landing recovery is effectively performed on the barrel type unmanned aerial vehicle, it is guaranteed that a long and thin vehicle body at the bottom of the barrel type unmanned aerial vehicle penetrates through the barrel, it can also be guaranteed that the bottoms of rotor wings of the barrel type unmanned aerial vehicle can stably fall on the upper portion of the barrel, recovery accuracy and success rate are improved, and the landing recovery problem of the barrel type unmanned aerial vehicle without the undercarriage is solved; the repeated utilization rate of the barrel type unmanned aerial vehicle is increased, the service life of the barrel type unmanned aerial vehicle is prolonged, the maintenance frequency and the part replacement cost are reduced, and safe recycling of the barrel type unmanned aerial vehicle in various environments or severe weather is met.

The present invention relates to a method for realizing degradation processing of an automatic driving function in severe weather and environment, the method comprising: identifying the state of the surrounding environment through a perception system module provided on the driving vehicle, obtaining the risks of the currently affected sensors and the risks of the weather conditions; inputting the judgment result into a degradation state management module to evaluate the severity of the external environment, and obtaining the risk level of the current vehicle environment; implementing a corresponding degradation strategy according to the degradation level result output by the degradation state management module, and performing corresponding automatic driving decision execution. The present invention also relates to a corresponding device, processor and storage medium thereof. The method, device, processor and storage medium thereof for realizing degradation processing of an automatic driving function in severe weather and environment of the present invention can identify different types of weather and environment that are not conducive to driving, and can freely match and combine different degradation strategies according to different environments.

To solve the problem that the stability is insufficient when used under bad weather or unstable ground conditions, and the operability and accuracy are reduced especially in the measurement work involving frequent movement, and to provide a holder for a portable hand-held laser distance meter that is easy to operate and reduces the work intensity. 【Solution means】The holder for a portable hand-held laser distance meter of the present invention includes a support mechanism 100 and a fixing mechanism 200. The support mechanism includes a support plate 110, a distance meter 120 provided at the top of the support plate, a plurality of support legs 130 hinge-connected to the bottom of the support plate, a support box 140 fixedly attached to the end of the support legs, an adjustment rod 150 hinge-connected to the surface of the support legs, and a screw sleeve 160 fixedly attached between the plurality of adjustment rods. The fixing mechanism includes an insertion fixing member 210 inserted and fixed into the support box to improve the stability of the support plate, and a moving member 220 for facilitating the movement of the support box.

The invention discloses integrated photovoltaic energy storage equipment, and relates to the technical field of photovoltaic energy storage equipment, the integrated photovoltaic energy storage equipment comprises two angle-adjustable photovoltaic panels, a positioning support is arranged below the two photovoltaic panels, and the positioning support can move synchronously along with the change of the angles of the photovoltaic panels. When the photovoltaic panel is perpendicular to the horizontal plane, the positioning support moves to the position under the photovoltaic panel. Two guide frames capable of moving up and down are arranged on the positioning support, and cleaning soft cushion layers are arranged on the sides, right opposite to the photovoltaic panel, of the guide frames. In the ascending process of the guide frame, the cleaning soft cushion layer can be moved out to the position above the positioning support, and the surface of the photovoltaic panel is cleaned in the vertical direction. According to the invention, the distribution angle of the photovoltaic panel can be adjusted according to the working ring, and the photovoltaic panel can be changed from an inclined state to a vertical state in severe weather. And the exposed area and the wind area of the photovoltaic panel are reduced, so that the damage risk of the photovoltaic panel is reduced. And the photovoltaic panel can be protected.

To provide a ribbon shuttle that can be selectively used by beginners and basic-level players, or intermediate players and advanced players, and a flawless in-home badminton practice facility.SOLUTION: There is provided a ribbon shuttle for badminton practice, the ribbon shuttles have three types of feather sizes to accommodate users ranging from beginners to advanced players, a return-ball board for an in-home badminton practice facility employs a gently curved frame section, and is provided with a safety device for preventing the return-ball board from the bad weather such as strong winds, typhoons, or earthquakes in which the internal corners of the joints of nine inclined wall surfaces arranged in upper, middle, and lower, as well as left, center, and right zones are adjusted.SELECTED DRAWING: Figure 5

The invention provides an outdoor cross-modal robust positioning and navigation method for extreme severe weather, and relates to the field of online positioning and navigation of mobile robots. The method comprises the following steps: acquiring and preprocessing data; generating a path point set based on a CMR network, perfecting the path point set through local trajectory fitting and error optimization, and constructing a path point relative pose measurement-topology hybrid map; motion prior estimation is carried out based on Doppler velocity, effective matching prior estimation is generated in combination with LiDAR odometer information, cross-modal pose estimation is carried out through a CMR network, and a pure tracking strategy and PD controller path point tracking are adopted; and geometric and intensity alignment is carried out on the forward 4D millimeter wave radar point cloud and the omnidirectional 3D laser radar point cloud through a CMR network, a rotation matrix and a translation vector are output, and accurate positioning is completed. According to the invention, the sensing and positioning defects in extreme weather in the prior art are overcome, and the positioning precision and robustness are improved.

The invention belongs to the technical field of air conditioners, and relates to a defrosting control method and device, a medium and electronic equipment. The method comprises the steps that environment parameters of air conditioner operation are obtained, and the environment parameters reflect the environment load of the air conditioner; and according to the environment parameters, target defrosting modes of the air conditioner are determined for defrosting, wherein the target defrosting modes comprise the reverse circulation defrosting mode and the shock cooling prevention defrosting mode. The corresponding target defrosting mode is selected for defrosting on the basis of the environment parameters reflecting the environment load. The reverse circulation defrosting mode can be selected under the condition that the requirement for defrosting is high, the reliability of the defrosting effect is improved so that the reverse circulation defrosting mode can be suitable for application scenes with severe weather or serious heat leakage conditions, the shock cooling prevention defrosting mode can be selected under the condition that the requirement for indoor comfort is high, the influence of slow temperature rising caused by defrosting is reduced, and the defrosting effect is improved. And the indoor temperature rising efficiency and the user experience in the defrosting period are improved.

The invention discloses a power transmission line insulator severe weather defect detection method based on a YOLOv10-MPM algorithm, and the method comprises the steps: designing different image enhancement strategies to simulate a natural scene based on an original visible light image, and constructing a synthetic data set containing three typical complex weather scenes, namely fog, rain and snow; sequentially dividing the synthetic data set into a training set, a verification set and a test set according to a proportion, and dividing data set labels into flashover, defect and insulator according to defect types; a designed multi-shape coordination attention mechanism MSSA is used for replacing an original point mode space attention module PSA in the YOLOv10n model; a C2f module is improved by using an MOCAA module; pIOU2 is adopted to replace a traditional loss function; carrying out lightweight design on the model by using LAMP pruning; therefore, a YOLOv10-MPM model is constructed; and training the YOLOv10-MPM model based on the training set, and detecting the model by the verification set. According to the method, the detection precision is improved, and the size of the algorithm model is greatly compressed, so that the algorithm model can be conveniently deployed on edge equipment such as an unmanned aerial vehicle.