738 results about "Remote area" patented technology

The invention discloses a photovoltaic panel defect detection method, system and device and a medium, and relates to the technical field of photovoltaic defect detection.The method comprises the steps that an infrared image and a visible light image of a photovoltaic module are obtained; visual features are extracted and fused; marking defect areas in the fused image data set, storing marking information of the defect areas, and constructing a training data set; inputting the training data set into a CLIP model for processing, and generating embedded representation; adopting the embedded expression to initialize the layer weight of the YOLOv11 model, and performing fine adjustment on the YOLOv11 model; inputting image data of a to-be-detected photovoltaic module into the trained photovoltaic defect detection model, and detecting to obtain a defective area in the image data; according to the method, the problem that a large amount of data for photovoltaic detection cannot be obtained in a remote area, so that model training is difficult is solved.

The invention is suitable for the technical field of database management, and provides a distributed database management method and system based on artificial intelligence. The system comprises a database content analysis module, a storage layout adjustment module, an anomaly detection module, an unmanned aerial vehicle storage communication module, an access request guide module and an unmanned aerial vehicle node recovery module. The scheme that an unmanned aerial vehicle is adopted as a storage and communication node brings remarkable innovation and multiple advantages to a distributed database management method. Firstly, the mobility of the unmanned aerial vehicle enables the unmanned aerial vehicle to quickly take over a data storage task when a network is interrupted or a node fails, so that the integrity and availability of data are ensured, and the response capability in a traditional architecture is relatively limited. In complex scenes such as disaster recovery or remote area deployment, the unmanned aerial vehicle can break through network limitation through off-line transmission, and data safety and storage continuity are effectively guaranteed.

The invention discloses an intelligent scheduling method for video equipment based on solar power supply, and relates to the technical field of energy management and video. Through multi-dimensional data acquisition, intelligent prediction and dynamic scheduling technologies, the energy management challenge faced by solar power supply video equipment in remote areas is effectively solved, the power generation amount, equipment power consumption and environmental change data are acquired in real time by using an Internet of Things sensor, and the energy management efficiency is improved by combining time sequence analysis and a machine learning algorithm. The power generation amount and power consumption fluctuation are accurately predicted, an energy supply and demand matching model is established based on a dynamic planning algorithm, a power distribution strategy is optimized, operation of high-priority equipment is guaranteed preferentially when the power generation amount is insufficient, meanwhile, the working mode of the equipment is dynamically adjusted through a reinforcement learning algorithm, and energy consumption optimization and self-adaptive matching are achieved. The energy utilization efficiency and the system stability are improved, the adaptive capacity to dynamic environment changes is enhanced, and continuous and stable operation of video equipment under complex conditions is ensured.

The invention relates to the technical field of unmanned aerial vehicle geological survey, and discloses a path planning method and system for unmanned aerial vehicle geological survey, and the method comprises the steps: obtaining the image, spectrum and topographic data of a remote mountainous area through a multispectral sensor and a laser radar, and recognizing potential vein abnormal points through data fusion and geological feature analysis; and constructing a geological interestingness weight map and planning a flight path. Dense sampling flights are performed in a high interestingness region, high resolution data are processed in real-time to identify key reconnaissance targets, a weight map is updated, and a flight trajectory is dynamically adjusted. Through the closed-loop self-adaptive exploration process, accurate positioning and feature description of the hidden vein are realized, the mineral exploration efficiency is improved, the labor cost and the safety risk are reduced, and an innovative solution is provided for mineral resource exploration in remote areas.

The invention discloses a reservoir capacity curve rechecking method based on satellite altimetry and remote sensing imaging technology, which belongs to the field of water conservancy and hydropower engineering and hydrology and water resource management, and comprises the following steps of: inverting and correcting the water level elevation of a reservoir by adopting altimetry data monitored by satellite remote sensing; recognizing a reservoir water body range based on a remote sensing image, and counting an area sequence; constructing a reservoir capacity calculation model based on the synchronous remote sensing water level and area sequence of the reservoir; remote sensing water level-area and water level-storage capacity curves are fitted, the precision is evaluated, and the process that the same satellite task is adopted to invert the same-period water level and area to reconstruct the storage capacity curve is achieved. By adopting the method, the defect that the water level and the area of the reservoir characteristic curve reconstructed by using satellite remote sensing data in the prior art are not synchronous can be avoided, the defects that the traditional height measurement satellite based on laser or synthetic aperture radar can only obtain the sub-satellite point cloud elevation and the step length is relatively long are overcome, and the precision of the reconstructed characteristic curve can be remarkably improved; the method has remarkable advantages in reconstructing characteristic curves of small reservoirs in remote areas and large ranges.

The invention relates to the technical field of new energy, and discloses an independent energy supply system suitable for a high-altitude area and a control method thereof, electric power is generated through photovoltaic power generation, part of the electric power is stored in a storage battery, and the residual electric power is used for electrolyzing water to prepare hydrogen and oxygen, and the hydrogen and the oxygen are respectively stored. The oxygen content in the air is increased by mixing the oxygen, the oxygen and the hydrogen jointly enter the fuel cell for chemical reaction, and stable electric power and hot water are output. In order to ensure the stability of the system, a low-temperature air source heat pump is configured to serve as standby heat supply equipment, and accurate adjustment and storage of electric power are achieved through cooperative work of a load tracking module and an efficient storage battery. According to the system, photovoltaic power generation, hydrogen energy storage and fuel cell technologies are combined, continuous and reliable power and heat combined supply can be achieved in high-altitude areas lack of power grid support, and an efficient and environment-friendly solution is provided for energy supply in remote areas.

The invention belongs to the technical field of lake remote sensing monitoring, discloses a lake water level and water reserve dynamic monitoring method based on satellite-borne active and passive remote sensing information fusion, and effectively solves the problem that lake information in remote areas is difficult to efficiently and accurately obtain. Comprising the following steps: S1, preprocessing laser data; s2, preprocessing the multispectral data; s3, taking the ICESat-2 data as a core, combining with a multispectral image covering a corresponding region, and constructing a lake bottom DEM inversion data set based on neighborhood features; s4, constructing and training an elevation inversion convolutional neural network model; s5, predicting and generating a lake bottom DEM by using the trained elevation inversion convolutional neural network model; and S6, calculating the absolute water volume of the lake according to the DEM at the bottom of the lake, and carrying out lake water level-water reserve monitoring. According to the invention, long-time-sequence hydrological observation of remote region lakes can be effectively realized with low cost.

The invention provides a plasmodium real-time detection method based on a lightweight neural network model. The plasmodium real-time detection method comprises the steps of obtaining a blood smear image data set and performing preprocessing; establishing a lightweight plasmodium detection model based on a deep learning algorithm; inputting the preprocessed blood smear image data set into a plasmodium detection model for iterative training; performing plasmodium detection on a to-be-detected blood smear image by using the trained plasmodium detection model; according to the method, a lightweight detection model is constructed based on a deep learning algorithm, so that high-precision plasmodium detection is realized, and the real-time performance of detection is effectively improved; meanwhile, the lightweight model design can adapt to a low-resource environment, so that the model can efficiently run on low-power-consumption equipment, and automatic real-time malaria detection requirements in remote areas and low-resource areas are met; in addition, various forms and life cycle stages of the plasmodium can be accurately identified, and the detection comprehensiveness is improved.

The invention relates to the technical field of farm irrigation, in particular to a multi-source fusion and V2X networked vehicle high-precision positioning system and method, and the system comprises a vehicle-mounted terminal which integrates the following modules: a multi-source sensor group which comprises a laser radar (LiDAR), a binocular vision camera (BVC), a global positioning system (GPS), an inertial measurement unit (IMU) and a wheel speed sensor; the V2X communication module supports vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication and is used for receiving positioning data of an adjacent vehicle and roadside equipment; the system effectively solves the problems that in the prior art, a traditional RTK technology depends on a ground base station, a positioning blind area exists in a signal shielding area, data conflicts are easily caused by independent work of multiple sensors, RTK needs to be covered and supported by dense base stations, and the positioning accuracy is poor. And high-precision positioning cannot be realized in signal shielding scenes such as remote areas, tunnels and mountainous areas, so that an automatic driving function fails.

The invention discloses an operation method and system for distributed organic solid waste centralized treatment and quality improvement and application, and relates to the field of chemical engineering, the operation method comprises the following steps: respectively carrying out pyrolysis treatment on organic solid waste distributed in different areas to obtain combustible gas and solid combustible materials and / or pyrolysis oil, using the combustible gas as fuel for pyrolysis treatment, and using the solid combustible materials and / or pyrolysis oil for pyrolysis treatment; the solid combustible comprises carbon powder and / or pyrolysis residues; concentrating and gasifying the solid combustibles and / or pyrolytic oil obtained in different areas to obtain mixed gas, dedusting the mixed gas, and converting the dedusted mixed gas by using water vapor to obtain a hydrogen crude product; purifying the hydrogen crude product to obtain a hydrogen product; packaging, storing or conveying the hydrogen product; the method solves the problem that large-scale industrial treatment and economic benefit improvement are difficult to realize due to the fact that the organic solid waste in a distributed area or a remote area has the characteristics of multiple types, small quantity, dispersive distribution, high transportation, recovery and treatment cost and the like.

The invention relates to the technical field of environment detection, and discloses an extensible underground water and soil in-situ online observation system, which comprises an underground water and soil automatic online monitoring management platform, an underground water control module, a soil control module and an auxiliary module, the underground water and soil automatic on-line monitoring management platform can check the state of the detection module and the detected data. The problems that when an existing underground water and soil on-line monitoring device monitors underground water and soil through an on-line sensor, the sensor may have drifting or errors in a complex environment, and the data accuracy is affected are solved; in remote areas and complex terrains, data transmission interruption can be caused by network instability; the problems that underground water and soil equipment are managed separately, data output is not synchronous, the data analysis difficulty is increased, and complex data analysis and modeling are difficult to achieve are solved.

The invention belongs to the technical field of hydraulic engineering, and provides a river reach form recognition method and system, a storage medium and electronic equipment, and the method comprises the steps: collecting and processing remote sensing image data of a river channel in a research region; extracting a waterline and a center line from the remote sensing image data, and determining a maximum waterline, a minimum waterline, an average waterline and a center line corresponding to the minimum waterline; and calculating a moving distance proportion value of the waterline based on the maximum waterline, the minimum waterline, the average waterline and the center line corresponding to the minimum waterline, and identifying the river reach form based on the moving distance proportion value. The remote sensing image of a remote area or an area not easy to enter is obtained through the remote sensing technology, the change characteristics of the river reach form are captured under the non-contact condition, large-scale and continuous monitoring is achieved, data support is provided for multilevel analysis of the river reach, and reliable technical support is provided for flood control and disaster reduction, ecological protection and drainage basin management.

The invention discloses a remote area video monitoring automatic anomaly detection method based on deep learning. The method comprises the following steps: S1, collecting remote area video data and completing preprocessing; s2, adjacent frame difference is executed in the transverse direction, channel fusion is executed in the longitudinal direction, and a composite frame set is generated; s3, performing bidirectional mask modeling and disturbance reconstruction on the composite frame set to obtain a regional feature matrix; s4, mapping the regional feature vectors into nodes, constructing a weighted adjacent matrix, and generating graph structure representation; s5, performing Laplace characteristic decomposition on the graph structure representation, and judging that the nodes are abnormal; s6, according to the abnormal node set, sub-graphs are divided according to topological neighborhoods, abnormal scores are calculated, and an abnormal region set is obtained; and S7, mapping the abnormal region set into the video data, and outputting an abnormal position, starting and ending frame numbers and an abnormal scoring result. According to the method, efficient and automatic anomaly detection of videos in remote areas is realized, the false alarm rate is remarkably reduced, and the anomaly positioning precision is improved.

The invention discloses an independent micro-grid optimal scheduling method based on multi-time scale source-load-storage coordination, and belongs to the technical field of power system optimal scheduling. The output volatility of renewable energy sources (such as wind energy and solar energy), the randomness of load demands and the adjusting capacity of an energy storage system and demand response resources are comprehensively considered, and the economical efficiency, reliability and renewable energy source consumption rate of the system are comprehensively improved through multi-level optimization scheduling. The method is suitable for an independent micro-grid system in remote areas (such as industrial and mining areas, islands or frontier sentries), aims to solve the technical problem that traditional single-time-scale scheduling cannot adapt to variable working conditions, and provides an innovative solution for low-carbon, efficient and reliable energy supply.

The invention discloses a radar station lightning protection device online monitoring method and system based on the Internet of Things, and relates to the technical field of equipment online monitoring. According to the invention, sensors are deployed in each component of the lightning protection device, real-time transmission and integration of monitoring data are realized by using the Internet of Things technology, a health degree evaluation model based on artificial intelligence is constructed, and remote automatic monitoring and health degree prediction of the lightning protection device of the radar station in a remote area are realized; according to the invention, the health degree evaluation model is combined with the correction coefficient to analyze the assembly evaluation data, and the health degree of each component is accurately predicted, so that the lightning protection effect of the lightning protection device is determined; according to the technical scheme, the space-time limitation of traditional manual inspection is broken through, the problem that a lightning protection device of a radar station in a remote area is difficult to monitor is solved, and conversion from passive maintenance to active prediction is achieved; through real-time data acquisition and intelligent analysis, potential hidden dangers of components can be found in advance, so that workers can take measures in time, and the lightning stroke risk is reduced.

The invention discloses an educational resource recommendation method and system based on artificial intelligence. The method comprises the following steps: acquiring audio data, interaction data and task data acquired by a user terminal; performing feature extraction on the audio data, the interaction data and the task data to obtain an emotion feature vector, a learning rhythm vector and a content feature vector; inputting the emotion feature vector and the learning rhythm vector into a pre-constructed emotion recognition model to obtain a psychological state vector; the cognitive load is calculated based on the learning rhythm vector and the content feature vector, and then the cognitive load is corrected through the psychological state vector; matching a state interval of the corrected cognitive load according to a preset threshold interval; and according to the state interval, adjusting a difficulty coefficient of the recommended course, rearranging a course content sequence and an auxiliary learning prompt, generating structured data, and outputting the structured data as an intelligent auxiliary learning recommendation result. According to the invention, online learning interactivity and teaching quality in rural and remote areas are effectively improved.

The invention relates to the technical field of dam safety monitoring, in particular to a low-power-consumption dam termite monitoring system and method based on intelligent image recognition. According to the technical scheme, the low-power-consumption dam termite monitoring system and method based on intelligent image recognition comprises a data analysis module; compared with a traditional termite monitoring system and a manual patrol mode which are applied for a long time, the termite monitoring system has the obvious defects of high system power consumption, difficulty in stable operation in remote areas such as dams and the like for a long time, poor environmental adaptability, great reduction of the recognition effect especially when light is insufficient or weather conditions are poor, and the like. The termite monitoring system can continuously collect high-quality images under the condition that power consumption is limited, and is particularly suitable for long-time unattended environment monitoring of dams and the like. The system is ensured to realize precise monitoring and real-time early warning of termite activities under the condition of low energy consumption, and meanwhile, a termite image recognition model of deep learning and small target detection is constructed, so that accurate and efficient extraction of termite information is realized.

The invention discloses application of privacy matrix decomposition on medical recommendation service based on a large language model. The system comprises a data acquisition module; a privacy matrix decomposition module; a large language model processing module; a recommendation decision module; the user interface module breaks through the restrictions of regions, time and professional resources through personalized online medical recommendation services, can obtain high-quality medical consultation and health recommendation services for social vulnerable groups such as remote areas, rural areas, old people and patients with mobility difficulties, promotes fair distribution of medical resources, enhances user trust, and improves the user experience. Particularly, due to the application of a privacy matrix decomposition technology, worries of a user on personal health data safety are eliminated, the trust degree of the user on a medical platform is improved, health consultation service popularization is promoted, the overall health management consciousness and the self-health-care ability of the society are improved, medical knowledge and health management concepts are popularized by means of a convenient online platform, and the health management system has a wide application prospect. Misdiagnosis and treatment caused by asymmetry of medical information are reduced, and the health quality of the whole society is improved.

The invention discloses a monocular image depth estimation method based on multi-scale information fusion, and the method comprises the steps: outputting a first feature map representing local information through a CNN branch, and outputting each second feature map representing global feature correlation at a Transform branch; enhancing the input first feature map and each second feature map from three dimensions of channel, space and cross-scale by using an adaptive fine-grained channel space collaborative gating module to obtain each third feature map; using attention mechanism decoders constructed based on an up-sampling module to sequentially process the input third feature maps to obtain a monocular image depth estimation feature map; according to the invention, the problem that the processing capability of a model on a remote area in a monocular depth estimation scene cannot be improved because local features and global features cannot be effectively combined in the prior art can be solved.

The invention discloses a kit for simultaneously detecting listeria monocytogenes and a drug-resistant gene fosX, and belongs to the technical field of bacterial molecular diagnosis. In order to solve the technical problems that in the prior art, a traditional method for detecting the listeria monocytogenes and the drug-resistant genes fosX of the listeria monocytogenes is low in efficiency and high in equipment dependence degree, the invention provides a kit for simultaneously detecting the listeria monocytogenes and the drug-resistant genes fosX of the listeria monocytogenes, and the kit comprises an EmDEA specific primer pair and an RNA probe, and a nucleic acid amplification group enzyme system and a signal amplification group enzyme system. The kit for simultaneously detecting the listeria monocytogenes and the drug-resistant gene fosX of the listeria monocytogenes, provided by the invention, has relatively strong specificity, repeatability, stability and reliability, and the sensitivity can be as low as 500 copies / mu L. The kit provided by the invention is simple in operation process, can be carried to rural sites, remote areas or any other scenes needing instant detection for detection, and has a wide application prospect.

The invention discloses a scenic spot intelligent management and control system and method based on Internet of Things and big data analysis, and particularly relates to the technical field of scenic spot intelligent management and control. The real-time performance of data transmission between devices in a scenic spot is predicted and modeled through a big data analysis algorithm, the data transmission rate between the devices is adjusted according to a prediction result, and meanwhile, the working state of the devices is dynamically scheduled in combination with an energy management system, the energy efficiency of the devices is optimized, and tourist flow data is recollected. The flow fluctuation is analyzed by using a machine learning algorithm, so that accurate personnel dispersion and resource scheduling optimization decision are realized, the problems of insufficient network bandwidth, data transmission delay and packet loss in a scenic spot are effectively solved, the real-time performance and accuracy of data transmission are improved, and especially in a remote area, the real-time performance of the scenic spot is improved. The intelligent management and control system of the scenic area can reflect dynamic conditions in real time, and the management efficiency and tourist experience are improved.

The invention discloses an all-network public network communication network networking fusion method and system based on satellite communication. The method and system are suitable for emergency communication guarantee, remote area communication coverage and other scenes. The system comprises a communication access module, a data convergence module, a three-network convergence gateway, an operator core network and a unified management and scheduling module, wherein the unified management and scheduling module is used for subdividing a core network link monitoring subsystem and a convergence site management subsystem. According to the system, by means of a three-network integration gateway, a single pico-base station device can provide signal coverage of three operators at the same time, a communication link is connected through a private network and encrypted, and safety is guaranteed. The method is based on the system and comprises the steps of communication access, data aggregation, data processing and management, service processing, management and scheduling and the like. The multi-operator network selection requirement can be met, the network security and stability are enhanced, resource centralized management and monitoring scheduling are achieved, and the method has important application value in emergency rescue, remote area communication coverage, large-scale activity communication guarantee and other scenes.

The invention relates to the technical field of sewage treatment, in particular to a distributed sewage treatment process management and control system, which adopts a distributed architecture to replace traditional centralized management and control, breaks geographical space and scale limitations, supports flexible access of sewage treatment stations of different areas and sizes, reduces system deployment cost and complexity, and improves system deployment efficiency. All the units realize data sharing and cooperative processing through interconnection and intercommunication, remote areas or small sites can also obtain efficient management and control, balanced development of urban and rural sewage treatment is promoted, the system supports butt joint with energy-saving and consumption-reducing sewage treatment technologies such as SBR and MBBR and an ozone catalytic oxidation intelligent disinfection technology, technological parameters are collected in real time to assist in optimization management and control, and the system is suitable for large-scale popularization and application. Data support and function verification are provided for technology research and development, conversion of new technology achievements is accelerated, meanwhile, on the premise that the sewage treatment requirement is met, system operation energy consumption is reduced through an energy consumption optimization strategy, the goal of carbon emission reduction is assisted to be achieved, and green and low-carbon conversion of the sewage treatment industry is promoted.

The embodiment of the invention provides a remote area-oriented electric energy quality comprehensive treatment method and system, and the method comprises the steps: collecting the operation parameters of a power grid through a detection module; calculating an electric energy quality index based on the power grid operation parameters, carrying out standardization processing on the electric energy quality index, and constructing a state vector; inputting the state vector into energy management software based on an improved DQN algorithm model, and generating a charging and discharging power instruction corresponding to the hybrid energy storage unit; and receiving the charging and discharging power instruction through the power conversion module, and controlling the hybrid energy storage unit and the power grid to perform energy exchange so as to realize electric energy quality treatment. According to the technical scheme provided by the invention, adaptation to a complex power grid in a remote region can be realized, a multi-dimensional power quality problem can be synergistically treated, the response speed and the system safety are improved, the power quality comprehensive index and the system operation efficiency are finally improved, and a support is provided for safe, stable and efficient operation of the power grid in the remote region.

Solar panels in a solar farm may suffer damage from severe hail damage during operation. Damaged solar panels need to be repaired or replaced. Given that a solar farm is typically located in remote areas, service or replacement will inevitably take extra time and effort, resulting in additional costs. The present invention discloses systems and methods for solar module protection using protective screens covering the back sides of the solar panels to avoid or minimize severe environmental impacts. Solar panels may be rotated to a protective position with their backsides and protective screens oriented upward. Such implementation provides a practical solution to protect the solar panels from hail damage, and thus, the need for costly repairs or replacement may be avoided or minimized. As a result, the economic efficiency of solar farm operations may be improved significantly.

This invention discloses a primer and probe set, a kit, and their applications for detecting Staphylococcus aureus L based on real-time fluorescence MIRA technology. The primer and probe set consists of single-stranded DNA sequences 1-3. Based on the aforementioned primer and probe set, this invention establishes and optimizes a real-time fluorescence MIRA detection method for Staphylococcus aureus L. Furthermore, the optimized real-time fluorescence MIRA method is innovatively combined with a simplified nucleic acid extraction method and a portable fluorescence detection device, significantly reducing extraction and time costs while enabling rapid on-site detection of the virus, making it particularly suitable for grassroots units and remote areas. In addition, the real-time fluorescence MIRA detection method for Staphylococcus aureus L established in this invention has advantages such as high specificity, high sensitivity, and simple operation. Moreover, the detection process does not require opening the lid, effectively avoiding aerosol contamination, providing an effective technical means for the differential diagnosis and rapid detection of Staphylococcus aureus L.

The invention discloses a cooperative control method for a core power supply and a 5G communication module of a new energy automobile, relates to the technical field of new energy automobiles, and aims to solve the technical problem that effective data collaboration between the core power supply and the 5G communication module is difficult to ensure due to the fact that a data link adopted by a current control method is single. Comprising the following steps: establishing a data link while a core power supply is started; according to the cooperative control method, firstly, when the core power supply is started, a wired or wireless data link is synchronously established, and the design has the advantage that data communication between the core power supply and the 5G electronic module can be ensured no matter in a complex urban environment or a remote area. According to the cooperative control method for the new energy vehicle core power supply and the 5G communication module, cooperative work between the vehicle core power supply system and the 5G communication module is guaranteed through wired or wireless data link connection, and basic guarantee is provided for intelligent operation of the vehicle.

The invention provides a special high-throughput satellite communication terminal for electric power, and relates to the technical field of electric power communication, and the special high-throughput satellite communication terminal comprises a baseband processing module which is used for carrying out differential encryption processing on different types of electric power data; the high-throughput satellite radio frequency module is used for suppressing sidelobe interference while realizing automatic satellite beam tracking through a beam forming algorithm during satellite communication, and calculating the optimal transmitting power through a self-adaptive power regulation algorithm; the communication transmission module is used for presetting a data priority based on a priority mapping table during data transmission and preempting satellite beam resources according to the data priority; the electric power Internet of Things protocol adaptation layer is used for realizing conversion between an electric power dedicated protocol and a satellite IP protocol, differential coding compression of electric power data and interrupted transmission in a link; and the beam optimization module is used for dynamically optimizing the beam pointing angle based on the satellite orbit parameters and the terminal geographic position. According to the scheme, the coverage degree of electric power communication in remote areas can be improved, and the safety and reliability of data transmission are improved.

The invention relates to the technical field of power transmission line self-energy-taking, and discloses a power transmission line self-energy-taking device and a state detection system, and the device comprises a housing structure, a motion structure, an electromagnetic power generation structure, and a friction power generation structure. Wherein the moving structure is composed of a permanent magnet, a spring and a fixing groove, the vertical shell and the fixing groove are connected through the spring, and a spring mass vibration system is constructed; the electromagnetic power generation structure generates power through relative movement of a permanent magnet and a coil. The friction power generation structure generates power through sliding separation of sliding electrodes on the side faces of the fixing grooves and electrodes in the side shells. The invention further discloses a state detection system, vibration energy is collected through the device and stored in an energy storage battery through an energy management circuit to supply power to a sensor detection circuit, and data are sent to an upper computer through a wireless transmission module. The power transmission line state real-time detection without external energy supply can be realized, and the problem of power supply of monitoring equipment in remote areas is solved.

The invention relates to the field of semantic communication and Beidou satellite communication, and particularly discloses an image semantic communication method based on a Beidou satellite in an intelligent power grid, and the method comprises the steps: enabling the image data of the intelligent power grid in a remote region to serve as the input of a system, inputting the data into a semantic encoder network, and extracting the semantic features of the data; after semantic features of data are obtained, the semantic features are transmitted at a transmitting end, shaping operation is performed on the semantic features before actual transmission, after a receiving end receives the data, the transmitted data need to be recovered, an end-to-end training mode of a combined satellite channel is adopted, a trained system is utilized, and transmission of the image data of the intelligent power grid is completed. The robustness of a communication system is improved, the performance of image transmission is ensured, and lower bandwidth resource occupation is achieved.