3923 results about "Wireless transmission" patented technology

The invention belongs to the technical field of aquaculture automation control, and particularly discloses an aquaculture environment intelligent disease early warning system and a storage medium, the system comprises a data acquisition layer, a data transmission layer, a processing platform layer and an application service layer; the data acquisition layer comprises an environment monitoring unit, a water quality sensor group, portable detection equipment and a data acquisition module; the data transmission layer comprises a wireless transmission module and an edge computing node; the processing platform layer comprises a machine learning prediction model and an environment factor correlation analysis model; the application service layer comprises an early warning information push module and a prevention and control scheme generation module. According to the intelligent disease early warning system for the aquaculture environment and the storage medium, a correlation model of environmental factors and disease occurrence is innovatively established, the early warning accuracy is 85% or above by adopting a machine learning technology, comprehensive monitoring and real-time early warning in the aquaculture process can be achieved, and accurate and efficient disease prevention and control are supported.

The invention relates to the technical field of fire early warning, and discloses a tunnel fire early warning method and system based on deep learning, and the method comprises the steps: deploying a sensor, constructing a wireless transmission network, and obtaining multi-modal data; carrying out preprocessing, feature extraction and feature fusion on the multi-modal data; constructing a tunnel fire early warning model adapted to the construction environment and designing a dynamic threshold mechanism; and designing a multi-level early warning response mechanism and carrying out early warning. According to the invention, the dust-proof smoke sensor is arranged to overcome the problem of susceptibility to dust interference; sampling frequency and communication frequency are automatically adjusted according to monitoring requirements during data transmission, so that the monitoring effect is ensured and the service life of a battery is prolonged; a tunnel fire early warning model based on TCNN is constructed, and a large-scale fire data set is constructed through FDS digital simulation to train the model; a dynamic threshold value capable of being automatically adjusted according to the environment is designed, and the problem that a fixed threshold value system does not adapt to the changing environment is solved.

The invention discloses a plant disease and insect pest early warning method and system based on plant monitoring, and belongs to the field of plant disease and insect pest early warning, and the method comprises the steps: extracting the contour of a lesion region through an edge detection algorithm, carrying out the smoothing of the contour through the combination of morphological operation, and obtaining a more precise lesion region boundary; according to an image segmentation result and a disease type identification result, a plant health condition evaluation model is established, and the plant damage degree is quantified; environmental data and image data are acquired from a plurality of sensor nodes distributed in a field, and the data are gathered to a regional gateway through wireless transmission; carrying out preprocessing and feature extraction on the converged heterogeneous data in a regional gateway, removing noise data and redundant information, and extracting key features; and carrying out pest detection and counting on the preprocessed image by using a deep learning model, carrying out modeling on a pest number change trend, predicting population density change in a period of time in the future in combination with environmental factors, and generating a detection result.

The present invention provides an unmanned aerial vehicle-based electric power patrol inspection control method and system. The method comprises: creating a flight path on the basis of an electric power patrol inspection area, and collecting images and position information of electric power devices by means of various types of devices carried by an unmanned aerial vehicle, the images and the position information being transmitted to a receiving terminal at a ground station in a wireless transmission mode; the ground station receiving the images and the position information that are collected in real time, processing and analyzing the images to obtain analytic status, such as defects, damage and corrosion, of the electric power devices; and, on the basis of the analytic status from the ground station, using the position information as distinguishing features to generate an electronic patrol inspection report, providing service lives, maintenance costs and maintenance measures of the electric power devices on the basis of the electronic patrol inspection report, and notifying maintenance staff of the position information of the electric power devices. The system comprises an unmanned aerial vehicle control module, an image processing and analysis module and an electronic patrol inspection report generation module. The present invention is of great significance to maintenance and management of electric power devices.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an intelligent dynamic pilot frequency networking system and method for an image transmission module MESH ad hoc network. The method is based on spectrum fingerprint features, combines a real-time interference topological graph constructed by interaction of neighborhood nodes, identifies a conflict frequency set needing to be evaded through multi-dimensional weighted evaluation, and dynamically generates a pilot frequency strategy table containing main and standby frequencies and a switching threshold value by using a frequency hopping decision engine according to the conflict frequency set and a preset legal frequency pool. Synchronizing the pilot frequency strategy table to an associated relay node, generating a link stability evaluation matrix and feeding back the link stability evaluation matrix to a frequency hopping decision engine; and correcting a frequency switching threshold value and an alternative frequency weight in the pilot frequency strategy table based on the link stability evaluation matrix. According to the invention, the spectrum utilization efficiency of the unmanned aerial vehicle image transmission system can be improved, the stability and reliability of a multi-hop link are ensured, the networking time delay is reduced through a distributed decision-making mechanism, and an effective solution is provided for high-quality wireless transmission in a dynamic topology environment.

The invention relates to the technical field of booster station monitoring systems, and discloses a booster station operation and maintenance work video auxiliary monitoring system comprising a three-dimensional perception interaction layer used for collecting equipment state data and providing a man-machine interaction interface and connected with an edge intelligent fusion layer through a wired or wireless transmission channel; and the edge intelligent fusion layer is used for locally analyzing and caching the state data. Through standardized interface interconnection of the three-dimensional perception interaction layer, the edge intelligent fusion layer and the cloud collaborative management layer, a collaborative working mode of data acquisition, local analysis and cloud optimization is formed, the architecture design breaks through the dependence of a traditional scheme on cloud centralized processing, data preprocessing sinks to the edge layer, the network transmission pressure is effectively reduced, and the network performance is improved. The local intelligent analysis capability can still be maintained when the network fluctuates, and compared with the delay problem caused by full data uploading in the prior art, the system response real-time performance and the availability under the network disconnection scene are remarkably improved.

The invention discloses a method for predicting the damage of a prestressed concrete cylinder pipe in a complex environment, and relates to the technical field of pipeline structure health monitoring, and the method comprises the steps: collecting multi-physical field data through deploying multiple types of sensors, transmitting the data to a central monitoring system in a wireless manner, carrying out the standardized preprocessing, and obtaining a multi-source fusion data set; a salt migration driving index dsa, a stress disturbance induction index yry and an electrochemical activity potential index che are constructed, a comprehensive corrosion risk index SCR is obtained, and corrosion behavior evaluation is carried out. And when the corrosion behavior is evaluated as a disturbance sign, a corrosion change prediction index CAR is further calculated according to time sequence evolution forming a corrosion risk index SCR, grading evaluation and transition identification of the corrosion state are realized, an evaluation result is stored in a database, and a corrosion risk evolution trend is presented through a visual chart. The method supports early warning and emergency response decision making, and has high adaptability and engineering practicability without adding hardware.

The invention discloses a wireless transmission anchor rod multipoint stress sensor system, which relates to the technical field of intelligent monitoring of geotechnical engineering and comprises a data sensing and acquisition module, a data processing and transmission module, a data receiving and storage module, a data analysis and decision module and a user interaction and management module. The technical key points are as follows: multi-protocol adaptive communication and quantum encryption are carried out, a multi-protocol adaptive communication stack is based on an improved near-end strategy optimization algorithm, intelligent switching of communication protocols can be completed in an extremely short time according to an actual environment, and the intelligent switching of the communication protocols can be completed in scenes such as mountainous area tunnels with complex and changeable signals. The problem that transmission of a traditional single protocol is prone to being interrupted is effectively avoided, continuity of data transmission is guaranteed, meanwhile, the integrated quantum key distribution unit adopts a BB84 protocol and is combined with a two-factor encryption system, data transmission safety is remarkably improved, quantum attacks can be effectively resisted in a monitoring scene with the extremely high requirement for data safety in confidential work, and the security of data transmission is improved. And the data leakage risk is avoided.

The invention relates to the technical field of precision agriculture monitoring, and discloses a precision agriculture monitoring system based on adaptive wireless communication. The system comprises a multi-source environment acquisition module, a communication protocol adaptation module and a crop state evaluation module. The multi-source environment acquisition module acquires soil humidity data, illumination intensity data and meteorological parameter data through wireless sensor nodes deployed in a farmland area, and performs timestamp synchronization on the data to ensure the consistency of the data in time dimension. And the communication protocol adaptation module dynamically selects a wireless transmission frequency band according to the synchronous data volume, allocates communication time slots based on the data priority, and generates adaptive transmission channel parameters so as to cope with the communication requirements in the data volume fluctuation and complex environment. The crop state evaluation module receives the transmission channel parameters, analyzes the real-time environment data flow, and divides the current crop growth state into a growth standard state, a growth lag state or a growth fluctuation state. The system provides support for fine management of agricultural production.

The invention belongs to the field of intelligent rehabilitation medical instruments, and particularly relates to a brain-computer interface-based multi-modal child sensory integration training device, which comprises a brain-computer interface head ring, an intelligent touch floor and AR interactive glasses, the brain-computer interface head ring is connected with a biological signal acquisition module, the intelligent touch floor is connected with a motion trail analysis unit, the AR interactive glasses are connected with a universe scene engine, and the biological signal acquisition module, the motion trail analysis unit and the universe scene engine are connected with a digital twin generator. The digital twin generator is connected with a dynamic mode switching decision tree, and the dynamic mode switching decision tree is connected with a multi-mode feedback actuator; the brain-computer interface head ring is located on the head of the child and collects electroencephalogram, myoelectricity and electrocardiosignals through a biological signal collection module; and the biological signal acquisition module sends a signal to the digital twin generator through wireless transmission. According to the invention, the training efficiency can be improved, the evaluation dimension can be expanded, potential safety hazard early warning can be realized, and the compliance can be enhanced.

The invention discloses an electricity utilization information acquisition device of an electric energy meter metering pulse simulation system, and relates to the technical field of monitoring analysis, and the method comprises the steps: carrying out the ripple disturbance simulation of an initial pulse characteristic data set, and generating an interference pulse waveform matrix; performing multi-source interference signal separation processing on the waveform matrix with the interference pulses, constructing a three-dimensional clock error compensation network, generating a clock synchronization calibration pulse set, and extracting dynamic characteristic parameters corresponding to the clock synchronization calibration pulse set; performing multi-modal data fusion processing on the dynamic characteristic parameters to form compressed pulse characteristic data; establishing a simulation load feature matching model, outputting a simulation load adaptation parameter group, and converting the simulation load adaptation parameter group into a wireless transmission data frame; and carrying out transmission protocol self-adaptive packaging on the wireless transmission data frame, dynamically adjusting a data packaging strategy based on a channel quality evaluation index, and executing remote power utilization information acquisition and transmission. The method has the effect of improving the power utilization information acquisition efficiency.

A medical monitoring system comprises a wearable garment incorporating multiple physiological sensors for real-time patient monitoring. The garment integrates an embedded processing unit that receives sensor data and transmits it wirelessly to a base station or remote server. A multi-modal physiological signal processing unit analyses the data to generate composite physiological indices, including metabolic rate, work of breathing, and fall risk assessments. The garment includes optional monitoring features such as transcutaneous carbon dioxide measurement, electrocardiography, pulse oximetry, blood pressure monitoring, and accelerometer - gyroscope-based motion tracking. The system provides early-warning alerts for clinical deterioration, enabling proactive therapeutic interventions. A wireless communication module ensures real-time data transmission, supporting remote monitoring and integration with hospital networks. The garment's modular design allows for non-invasive physiological assessment while maintaining patient mobility, making it suitable for critical care, ambulatory monitoring, and telemedicine applications.

The invention relates to a computing power resource dynamic scheduling method, device and equipment based on deep reinforcement learning and a medium thereof, and the method comprises the steps: constructing a joint state vector through real-time fusion of a network layer channel state and computing layer node load data, and driving a strategy network to generate transmission parameters and resource allocation actions of cooperative control; the code modulation parameters of the wireless transmission module and the computing resource proportion of the target node are synchronously configured in the execution layer, and dynamic task scheduling in the channel decay environment is achieved; a multi-target reward mechanism is designed to couple transmission bit error rate penalty, resource utilization efficiency and task timeliness evaluation indexes, and a reinforcement learning agent is guided to balance communication stability and computing power demand conflicts; according to the method, strategy network parameters are optimized through time difference errors, closed-loop feedback is formed in combination with channel state prediction and node load updating, the problems of network and calculation layer splitting decision, insufficient dynamic adaptability and multi-target optimization imbalance in the prior art are effectively solved, and the task scheduling success rate in the time-varying wireless environment is improved.

Certain aspects of the present disclosure provide an architecture and method for multi-link operation (MLO) at an access point (AP). The method generally includes obtaining a packet from at least one buffer and selecting a processing path, from first and second processing paths, for a packet to be routed from the at least one buffer to at least one of a plurality of radio components for wireless transmission to at least one peer via one or more links, wherein: the first processing path is configured to bind the packet to one of the one or more links based on at least one code-implemented rule, and the second processing path is configured to bind the packet to one of the one or more links based on instantaneous channel sensing.

The invention belongs to the technical field of audio and video fusion transmission, and discloses an audio and video signal fusion transmission method and device, equipment and a medium, and the method comprises the steps: extracting 512-dimensional semantic feature vectors of an audio and a video, and generating a joint feature matrix through a cross-modal attention mechanism; calculating a fusion feature flow based on a coefficient alpha output by the scene classification model; a quantum random number generator is used for generating a session master key Kmain, the session master key Kmain is packaged into an encrypted session key Kenc through a Kyber-768 algorithm, and frame-level dynamic encryption is carried out on the fusion feature flow; and selecting a GPMI Type-B wired protocol or wireless transmission based on QUIC according to the transmission environment. According to the invention, the transmission efficiency, the anti-interference capability and the anti-quantum-attack security are improved, and multi-scene requirements are met.

The invention relates to the technical field of data analysis and control, in particular to a hydraulic climbing frame safety control method based on digital monitoring, which comprises the following steps: acquiring monitoring data in real time through a sensor group arranged on a hydraulic climbing frame, preprocessing and analog-to-digital conversion are carried out on the monitoring data, then the data are formed and sent to a remote monitoring center through a wireless transmission technology, and the preprocessed monitoring data are input into a pre-stored structure safety evaluation model and a hydraulic system performance evaluation model so as to be analyzed in real time; analyzing the hydraulic climbing frame, judging a safety characterization state of the hydraulic climbing frame according to an analysis result, determining a safety risk type based on an abnormal state of the hydraulic climbing frame, sending early warning information through a user interaction platform when a risk is judged to exist, and executing a corresponding safety control instruction; automatic real-time monitoring, intelligent early warning and active control of the safety state of the hydraulic climbing frame are achieved, and construction safety and operation reliability are remarkably improved.

The invention discloses a multi-antenna joint precoding Gbit wireless transmission system, which relates to the technical field of wireless communication and comprises a frequency spectrum channel acquisition module, a signal preprocessing module, a precoding joint optimization module, a transmission performance evaluation module and a closed-loop parameter control module. The spectrum channel acquisition module acquires signal data and evaluates a transmission bit error rate and a signal-to-noise ratio by using a spectrum analyzer; the signal preprocessing module performs denoising and normalization and constructs a channel model; the precoding joint optimization module dynamically adjusts precoding and suppresses bit error diffusion; the transmission performance evaluation module calculates a data rate and optimizes protocol design; and the closed-loop parameter control module dynamically configures system parameters to guarantee closed-loop optimization. According to the method, the transmission efficiency and the stability of a Gbit wireless transmission system are remarkably improved, a complex channel environment is effectively dealt with, the bit error rate is reduced, the data rate is improved, a transmission protocol is optimized, intelligent dynamic adjustment of system parameters is realized, and the optimal performance of a multi-antenna joint precoding technology is ensured to be exerted.

Methods, systems, and devices for wireless communications are described. A transmitter may modulate a set of bits into an on-off keying (OOK) sample sequence for wireless transmission to a receiver in a set of frequency resources. The transmitter may apply a transform (e.g., a discrete Fourier transform (DFT)) to the OOK sample sequence to generate a frequency domain representation of the OOK sample sequence. In some cases. the transmitter may, using an orthogonal frequency division multiplexing (OFDM) waveform generator, generate an OFDM waveform based on mapping the frequency domain representation of the OOK sample sequence to a set of resource elements of the set of frequency resources. In some cases. the transmitter may transmit the OFDM waveform to the receiver via the set of frequency resources.

Provided is a method for processing wireless transmission. The method includes: performing wireless transmission-related processing based on a selection or usage rule for a first hybrid automatic repeat request (HARQ) process or based on a transmission or processing mode for a first resource, wherein the first HARQ process is an HARQ process satisfying a collision condition, and the first resource is a resource corresponding to the first HARQ process.

A communication device comprising a control unit that generates low latency traffic information relating to multi-AP coordinated transmission and a wireless transmission unit that transmits the generated low latency traffic information.

The invention discloses a gear dynamic parameter in-situ testing device based on wireless power supply. The gear dynamic parameter in-situ testing device comprises a wireless power supply system, a sensor, a data processing system, a data transmission system and an upper computer, the wireless power supply system is used for providing electric energy for the sensor and the data acquisition system; the sensor is used for collecting dynamic parameters of the gear; the data processing system is used for processing the gear dynamic parameters; the data transmission system is used for transmitting the processed gear dynamic parameters to an upper computer in a wireless transmission manner; and the upper computer is used for visually displaying the processed dynamic parameters of the gear. The problem of long-time test operation and maintenance of the rotating gear in a complex narrow space is solved, and long-time in-situ test of dynamic parameters of the gear can be ensured.

The invention discloses a shield cutter cutting load real-time monitoring and adjusting method and system. The method comprises the following steps: constructing a shield cutter distributed sensing network, and collecting strain, vibration and temperature of a cutter; a wireless transmission network is established, and the collected strain, vibration and temperature of the cutter are transmitted in real time; according to the strain, vibration and temperature, received in real time, of the cutter, cutting load parameters are obtained in a multi-source data fusion mode; based on the obtained cutting load parameters, stratum parameter identification is carried out in combination with a deep learning algorithm; in combination with the stratum parameters and the cutting load parameters, a wear state evaluation model based on fuzzy reasoning is established, and the tool wear state is evaluated; and designing a multi-objective optimization function according to the wear state of the cutter and the stratum parameters, solving the multi-objective optimization function, obtaining optimal shield tunneling machine operation parameters, and performing dynamic adjustment. The cutting load of each cutter in shield construction can be monitored in real time, and the cutter parameters can be adaptively adjusted.

The invention relates to the field of power transmission line device defect detection, and discloses a strain clamp defect detection method and device based on computer vision, and the method comprises the steps: obtaining a global three-dimensional point cloud model of a strain clamp; mapping a standard detection path to the model; synchronously acquiring an internal structure image, an external surface image and an acquisition pose along the path; identifying suspected defects in the internal structure image; if the defect exists, calculating a corresponding associated influence area of the defect on the three-dimensional model by combining the pose; and performing enhanced scanning on the associated influence area to obtain high-precision information. The device comprises a ray machine; a ray machine control module; a digital ray imaging detector; a multi-dimensional information fusion probe; a wireless transmission module; and a power module. According to the method, internal and external defects can be accurately associated, the detection process is standardized, the detection accuracy and repeatability are improved, and a traceable digital file is constructed.

The invention relates to an internet-of-things monitoring and early warning system for lake water quality. The internet-of-things monitoring and early warning system comprises a multi-mode intelligent sensor acquisition system, a self-adaptive wireless transmission system, a distributed data storage system, an intelligent data analysis system, a visual interaction system, an intelligent early warning system and a remote intelligent control and repair system. The invention also relates to a monitoring method using the lake water quality Internet of Things monitoring and early warning system. Traditional and innovative sensors are cooperated to comprehensively collect water quality and ecological data, the biosensor accurately detects specific pollutants, the hyperspectral imaging sensor monitors algae distribution and water color change, rich and high-precision data are provided for lake water quality monitoring, the monitoring comprehensiveness and precision are improved, and the water quality monitoring system is suitable for being popularized and applied. The lake ecological protection work is powerfully supported.

The invention belongs to the field of intelligent monitoring, and discloses a photovoltaic flexible support load deformation monitoring system and method, and the system and method achieve the safe and precise management and control of a structure through the deep fusion of multi-source sensing, mechanism modeling and data driving. Structural deformation parameters are synchronously obtained by combining a laser displacement sensor and a double-axis tilt angle sensor, and the limitation that a traditional monitoring means is single in parameter and lack of dimensionality is broken through. After data is gathered in real time through a wireless transmission module, a physical constraint-data learning hybrid framework is adopted for processing, a physical model constructs a deformation calculation equation based on a moment balance and deflection theory, a theoretical lower limit conforming to an engineering mechanics law is provided, and an LSTM neural network captures nonlinear dynamic association such as wind load sudden change through time sequence learning. A prediction result with both theoretical compliance and data adaptability is generated, and the operation reliability and maintenance efficiency of the photovoltaic flexible support in a complex environment are improved while high real-time performance is maintained.

The invention discloses a wireless and passive carrier roller monitoring device and a using method thereof, and belongs to the technical field of online monitoring, the wireless and passive carrier roller monitoring device comprises a stator assembly fixedly arranged on the outer side of a carrier roller shaft in a sleeving mode and a rotor assembly fixed in a bearing seat of a carrier roller uterus body, an annular or semi-annular circuit board is arranged in the stator assembly, a sensor module, an inductance coil and a wireless transmission module are arranged on the circuit board, and permanent magnets are evenly arranged on the side, close to the carrier roller uterus body, of the rotor assembly. According to the stator and rotor separation type structural design, the monitoring device and a carrier roller mechanical structure are deeply fused, direct capture of energy of a rotating part and stable acquisition of signals of a static part are achieved, the problems of power supply and wiring on a rotating body in a traditional monitoring scheme are solved, and the system integration degree and reliability are improved.

The invention provides a wireless resource scheduling method and device, equipment, a medium and a program product, and relates to the field of wireless transmission, and the method comprises the steps: collecting a current network resource use condition; receiving measurement data sent by the terminal during operation of the target service, and evaluating the service quality of the target service based on the measurement data to obtain service quality information; synchronizing the service quality information and the network resource use condition to a first control unit so as to generate service quality target information through the first control unit; calling a second control unit to generate a first resource scheduling instruction based on a preset artificial intelligence model in combination with the service quality target information, the service quality information and the configuration information of the terminal; the first control unit is a non-real-time wireless access network intelligent control unit, the second control unit is a near-real-time wireless access network intelligent control unit, and the first resource scheduling instruction is used for scheduling wireless resources for the terminal. And the response speed of the base station to the wireless resource scheduling is improved.

The invention discloses an uplink subsystem complexity reduction method based on a PCMA technology, and relates to the technical field of high-capacity wireless transmission system design and complexity control, and the method comprises the following steps: collecting uplink signal parameters through spectrum analysis, bit error rate test and MIMO detection, obtaining channel characteristics through a pilot frequency and a Gray sequence, and obtaining the complexity of a high-capacity wireless transmission system; baseband data are generated, scene features are extracted, Wiener filtering and iterative soft decision feedback algorithms are adopted to optimize filtering and coding, channel and coding performance is evaluated, transmission strategies are dynamically adjusted through a gigabit network interface, clocks are unified, synchronization is optimized, and the complexity of a PCMA uplink system is reduced. The complexity of an uplink subsystem is effectively reduced through the PCMA technology, the efficiency and the stability of a high-capacity wireless transmission system are improved, efficient utilization of resources and improvement of synchronization precision are achieved by accurately collecting signal parameters, optimizing filtering and coding and dynamically adjusting a transmission strategy, and the method is suitable for large-scale popularization and application. And powerful support is provided for the development of a wireless communication system.

The invention discloses a laser wireless energy transmission system based on a vertical tracking structure and double-stage global optimization and a control method, and belongs to the technical field of photoelectric energy conversion and intelligent control. Aiming at the technical bottlenecks of high reflection loss of a photovoltaic array and MPPT failure caused by multi-peak characteristics due to non-uniform irradiation in the existing laser wireless transmission system, the invention provides three innovations: (1) designing a two-degree-of-freedom vertical tracking type photovoltaic array, and adjusting the pitch angle and azimuth angle of a photovoltaic panel in real time through a servo motor driving holder; a silicon nitride anti-reflection coating (the refractive index is smaller than or equal to 1.8) and a laser positioning sensor are combined to construct an incident angle deviation dynamic compensation model, and the reflection loss rate is reduced to be lower than 5%; (2) putting forward a global MPPT dual-stage optimization algorithm, dividing a voltage interval based on irradiation non-uniformity in a coarse positioning stage and generating an optimal candidate solution, and adopting an improved particle swarm algorithm (introducing an inertia weight dynamic adjustment mechanism and a local extreme value escape strategy) in a fine search stage to realize that the global maximum power point tracking precision reaches 99.2% in a multi-peak scene; and (3) establishing a reflection loss-power coupling control model, and solving the problems of tracking delay and energy oscillation of a traditional system through angle adjustment of the photovoltaic panel and closed-loop feedback of MPPT (Maximum Power Point Tracking) output. Compared with the prior art, the comprehensive efficiency of the system is improved by 18.6% under the dynamic irradiation condition, and the system is suitable for space laser power supply and mobile equipment wireless charging scenes.

The invention discloses a wireless relay method, system and equipment for commercial vehicle tire pressure monitoring and a medium, relates to the technical field of commercial vehicle tire pressure monitoring, and solves the problems of poor system adaptability and unreliable real-time alarm caused by the fact that existing commercial vehicle tire pressure monitoring needs trailer transformation and wireless transmission is easy to conflict. The method specifically comprises the steps that ACL connection is established between a tire pressure receiving node and a wireless relay node, and channel scheduling parameters and tire pressure sensor working parameters are issued to the wireless relay node; the wireless relay node sends a report request message to the tire pressure sensor on a specified channel according to a preset period; after each tire pressure sensor receives the message, reporting tire pressure monitoring data in the exclusive response time slot, and if the tire pressure sensor detects a tire burst early warning event, repeatedly reporting the tire pressure monitoring data in the tire burst reporting time slot; the wireless relay node packages the data and sends the data to a tire pressure receiving node for receiving and processing, and if it is judged that a tire burst early warning event exists, an alarm is given within 100 ms. The method is used for monitoring the tire pressure of the commercial vehicle.