46results about How to "Accurate perception" patented technology

The invention discloses a dynamic obstacle avoidance method and system for a substation inspection robot. The position of the robot is positioned based on laser point cloud data, and static and dynamic obstacle features are extracted at the same time. An environment association graph is constructed through perception information in the advancing process, and feature information of each node serves as an attribute of the environment association graph; calculating the distance, the relative speed and the relative angle between the edge weights of the nodes according to the nodes; on the basis of the environment association graph, aggregating all-graph obstacle node information to generate real-time feature representation for robot nodes, and correcting a calculation mode of attention weight according to edge weight between the nodes; and finally outputting a real-time feature vector of the robot node. And defining a reinforcement learning framework and executing path planning. According to the invention, through combination of GAT and dynamic planning, efficient obstacle avoidance and path planning of the robot in a substation environment are realized, and the decision and execution capability of the robot in a dynamic complex scene can be improved.

This invention relates to a navigation method for underwater unmanned vehicles (UUVs), comprising the following steps: acquiring data from multiple sensors and performing spatiotemporal synchronization, feature extraction, and data fusion preprocessing; defining the underwater operating area as a directed graph, with edge weights determined based on terrain complexity, obstacle risk, and water flow influence; based on the directed graph, employing an improved A* algorithm for global path planning and a fast exploratory random tree algorithm for local path planning and dynamic obstacle avoidance; assessing the environmental state considering aquatic environmental parameters, water flow characteristics, and topographic changes; and adjusting the navigation strategy using a deep reinforcement learning algorithm, with the navigation strategy adjustment objective function as the optimization goal, based on the environmental assessment results and the UUV's own state. Compared with existing technologies, this invention offers advantages such as improved navigation accuracy, reliability, and adaptability of underwater UUVs in complex underwater environments.

This invention discloses a multi-scale icing detection method and system for transmission line insulators under extreme weather conditions. The method includes: dividing a visible light image into pixel blocks and converting them into feature vectors with position encoding; inputting these vectors into an improved Swin Transformer integrating a Dynamic Deep Sample Generation (DDSGM) module; applying DDSGM to enhance features in a four-stage feature extraction phase; additionally fusing polarized light features in the first two stages; and outputting a multi-scale feature map. The multi-scale feature map is then input into a deformable attention unit containing DDSGM, undergoing secondary enhancement and adaptive sampling (fusing physical field information to correct for offset) to obtain enhanced features. A prediction head predicts the icing category, bounding box, and thickness; Hungarian matching is used to associate the target; and an early warning system outputs the results and a warning. This invention is the first to integrate DDSGM, optimize sampling, and combine a multi-physical quantity strategy to improve robustness to low-quality images and transparent ice layers, achieving accurate detection and early warning under extreme weather conditions.

This disclosure relates to the technical field of gas pipeline condition monitoring devices. It provides a collision alarm device for overhead natural gas pipelines, used to monitor the columns supporting overhead natural gas pipeline sections. The device includes a swing arm, a sliding member, a pressure sensor, and an elastic member. The swing arm is oscillatingly mounted on the column. The sliding member is slidably mounted on the column and contacts the swing arm, configured such that after the swing arm oscillates, the swing arm pushes the sliding member to slide. The pressure sensor is mounted on the column and is used to transmit data to an external controller. The two ends of the elastic member act on the sliding member and the pressure sensor, respectively, to absorb the force between the swing arm and the sliding member and transmit the force to the pressure sensor. This technical solution solves the problem in related technologies where collisions or scrapes between external objects cause pipeline leaks in overhead sections of natural gas pipelines or columns, leading to untimely detection, natural gas loss, and increased on-site safety hazards.

This invention discloses a target recognition and localization method based on self-switching of a multi-view vision system. The method uses a target recognition algorithm to identify and perceive the target object, and acquires local depth information based on the binocular imaging principle. Based on this local depth information, three indicators are calculated to evaluate localization accuracy: single-pixel deviation influence factor σ, depth information error rate ε, and depth dispersion ξ. Two evaluation indicators, Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity-to-Simple (SSIM), are obtained based on the local image information of the target. A target localization evaluation model is established to quantify the localization accuracy. According to the autonomous switching logic, the target recognition result and the localization accuracy evaluation score are compared sequentially to achieve autonomous switching between multiple binocular cameras with different focal lengths. This satisfies the requirements for both near-range and far-range target recognition and localization, overcoming the problems of low localization accuracy of low-focal-length binocular cameras for distant targets and small field of view of high-focal-length binocular cameras.

The invention discloses a self-adaptive multi-path redundant data transmission method and device based on multi-strategy configuration. The method comprises the following steps of: pre-configuring a logic table for defining a service type and transmission logic; obtaining service data, querying the logic table according to the service type identifier to determine the data copy number and the optimal port combination, and copying the data according to the data copy number and the optimal port combination; a multi-port connection state is maintained by a double-frequency dynamic mechanism, and the mechanism is switched to high-frequency keep-alive when service data exists and is recovered to low-frequency keep-alive when no service exists; and selecting an available port for data replication and sending the available port based on a preferred port combination and a real-time port connection state in the logic. According to the invention, differentiated redundancy transmission can be carried out according to service importance, the real-time performance and signaling overhead of link state detection are balanced through a double-frequency keep-alive mechanism, and the data transmission reliability and the resource utilization rate in a heterogeneous network environment are improved.

The embodiment of the invention provides a mode memory enhanced dynamic graph convolution traffic flow prediction method and related equipment, and belongs to the field of intelligent traffic and spatio-temporal data prediction. According to the method, a two-state driven dynamic graph generation mechanism is constructed, and the method comprises the following steps: extracting dynamic mode embedding of traffic data through a mode memory network to capture unsteady disturbance characteristics; time period embedding is extracted through an independent period embedding unit so as to encode a steady state rule; and fusing the two to generate a dynamic graph structure at each moment. According to the method, a dynamic graph generation module is further integrated at a decoding end of an encoder-decoder architecture, so that an adaptive dynamic graph can be regenerated according to time information of a target moment when each future moment is predicted, and graph structure dynamic evolution of a whole training and prediction process is realized. According to the invention, the traffic flow prediction precision, especially the accuracy of long-term prediction, is effectively improved, and the generalization ability of the model to unexperienced scenes is enhanced.

The application discloses a kind of light storage fills integrated equipment charging protection device, including charging pile body, the charging pile body both sides are connected with plug-in mouth, two The plug-in mouth inside is inserted with charging head, the charging pile body both sides correspond two charging head below It is connected with wire collecting box, two The wire collecting box lower end is respectively connected with the upper end both sides of base, the charging pile body both sides lower part It is connected with electric cable, two The electric cable is respectively penetrated corresponding wire collecting box and extends to corresponding wire collecting box side, the present application is realized active anti-collision early warning by sensing positioning strip and light alarm equipment, with the automatic regularity of wire collecting mechanism It is realized that cable is protected, and relies on broken line mechanism to execute physical cut-off in fire time, so as to realize early warning, protection and isolation integration's charging safety protection.

The utility model provides a trajectory environment collection mechanism, including shell, reading board part, collection module group and detection circuit group, reading board part collection module group along the axial direction of shell from top to bottom sets gradually, reading board part collection module group and detection circuit group are fixedly connected through the terminal strip and screw, when reading board part collection module group and detection circuit group assemble in place, will make the turn and screw cap and install in the shell, and use electronic pouring sealant to pour seal the space between reading board part collection module group and detection circuit group. The utility model discloses a trajectory environment collection mechanism, through the integrated structure design, waterproof performance is excellent, and the anti -interference ability is strong, safe, and the reliability is high.

The application provides a kind of multi-dimensional behavior situation awareness and intelligent decision-making method, system and electronic equipment, belongs to behavior situation awareness decision-making technical field.Method includes: constructing dynamic behavior relationship diagram, collecting behavior data and mapping therein;Generate behavior semantic vector, mine causal dependence and construct behavior causal graph;Establish probability benchmark model based on historical normal behavior, calculate current behavior deviation and locate abnormal source, generate situation assessment results;Risk evolution path and propagation range are deduced using causal time series prediction model;Through hierarchical decision engine, generate differentiated disposal instructions, and iteratively optimize the model according to the execution effect.The application improves the accuracy of anomaly detection and risk prediction ability through deep fusion of multi-source data and accurate positioning of abnormal source, solves the problems of insufficient data fusion, low detection accuracy and delayed decision response of traditional methods, realizes real-time perception of system behavior situation, and provides intelligent decision support for network security and system operation.

The application relates to the technical field of intelligent interaction systems and automobile customer service marketing, and discloses a traffic automobile customer service marketing method and system based on a large language model, wherein the traffic automobile customer service marketing method based on the large language model comprises the following steps: collecting driver fixation point data by using an eye movement tracking algorithm to generate eye movement trajectory data sets; constructing a visual attention heat map to form a user attention distribution model; calculating multi-medium characteristic parameters to establish a medium characteristic model; using the large language model to generate and adapt personalized marketing content and output multi-medium compatible marketing information; realizing intelligent attention guidance according to the user attention distribution model, the medium characteristic model and the multi-medium compatible marketing information; and realizing accurate perception and quantitative analysis of the visual attention of the driver through the eye movement tracking technology, so that the marketing system can master the user focus points in real time, and the technical problem that a traditional interface cannot perceive actual user focus points is solved.

This invention discloses a green and ecological planting method for daylilies, belonging to the field of agricultural planting technology. It addresses the technical problems of excessive reliance on chemical fertilizers and traditional mulching in current daylily cultivation, leading to soil ecological imbalance and low fertilizer utilization. The method includes: applying organic fertilizer made from cow and sheep manure and Asteraceae plant residues through aerobic composting, using a layered strip application method. First, fully decomposed organic fertilizer is applied as a base fertilizer layer in the planting furrow, followed by semi-decomposed organic fertilizer that has completed the main fermentation stage but not the later aging stage as a middle layer fertilizer; after land preparation and ridging, wood ash is spread on the ridge surface, followed by the laying of black fully biodegradable mulch film; finally, holes are made in the mulch film for daylily seedling planting. This method is mainly used for sustainable ecological planting of daylilies, improving soil fertility and structure, regulating soil pH and providing potassium, conserving moisture and suppressing weeds while avoiding residual pollution, thereby increasing daylily yield and quality while reducing environmental impact.

The present application belongs to the technical field of networked converter control, and discloses a networked converter control method, system, device and medium based on network side information feedback to solve the problem of subsynchronous oscillation. The method comprises: collecting voltage signals of a grid side point of common connection and voltage signals and current signals of a converter side; calculating steady-state active power and steady-state reactive power based on the voltage signals of the grid side point of common connection and line impedance parameters; calculating transient active power and transient reactive power based on the voltage signals and current signals of the converter side; introducing a composite factor to fuse the steady-state active power and the transient active power to obtain composite active and reactive power; and inputting the composite active and reactive power to a power outer loop controller of the networked converter to generate a reference signal for inner loop control. The present application improves system damping and the ability to suppress subsynchronous oscillation.

The application belongs to the technical field of robot control, and particularly relates to a master-slave operating arm with electromagnetic force feedback for precision assembly and a bidirectional transparent control method, which comprises a master-slave robot unit, an information transmission unit, a master-slave control unit, an electromagnetic force feedback unit, a bidirectional transparent control unit, a singular point processing unit, an adaptive path planning unit and a master-slave proportion matching unit. The electromagnetic force feedback unit obtains environmental force information through a magnetic coupling component and transmits the information to the master control unit; the bidirectional transparent control unit constructs a master-slave control closed loop, balances the system transparency and stability under communication delay, detects and avoids joint singular points through a Jacobian matrix, and constructs a potential field function to generate an optimal motion path. The application realizes high-precision control and force feedback under a communication delay environment, and improves the accuracy and safety of remote operation.

This invention discloses a method, apparatus, device, and medium for morphological operations based on local density maps, relating to the field of image processing technology. The method includes: calculating a local density map based on a target image; using the local density map to characterize the local grayscale distribution features of each pixel; assigning structural element parameters of different sizes to different regions based on the local density map; performing morphological operations on the target image using structural element parameters of different sizes to obtain multiple morphological operation results; and fusing the multiple morphological operation results based on the local density map to obtain the final morphological operation result. This invention accurately perceives local image features through local density maps, adaptively assigns structural element parameters of different sizes to different regions, and organically combines the processing advantages of different parameters through a fusion strategy. While maintaining high computational efficiency, it effectively balances detail preservation and noise suppression, significantly improving the processing quality of morphological operations.

The invention relates to the technical field of intelligent park digital operation and maintenance, in particular to a multi-node collaborative intelligent park digital operation and maintenance system and a control method, and the method comprises the following steps: collecting multi-source operation data, and executing protocol conversion, time synchronization and local jitter removal processing at a gateway end; sending the processed collected data to a central access layer, carrying out authentication and flow limiting on the data, and writing the data into message middleware; mapping data accessed by the message-oriented middleware to a unified asset model and performing unit and semantic standardization; writing the time sequence data into a time sequence database, and writing the event and the audit information into an event and audit library; and performing missing interpolation, quality labeling and preliminary filtering on the data. According to the invention, through a hierarchical alarm and strategy scheduling mode, the accuracy of abnormity identification and the timeliness of operation and maintenance processing are improved, the frequency of manual intervention is reduced, and the stability and reliability of system operation and the overall efficiency of intelligent park digital operation and maintenance are improved.

The application discloses an automatic material distribution control method and system based on radar and visual three-dimensional reconstruction and a pump truck, and belongs to the field of intelligent manufacturing of pump trucks. In order to solve the problems of high risk of manual operation, inaccurate single sensor sensing and inability to automatically distribute materials, the application adopts a radar and visual fusion scheme: sensors are arranged on the boom, images and point clouds are synchronously collected, a three-dimensional model of a construction scene is reconstructed after being processed and fused, and is mapped to a boom coordinate system; obstacle detection and real-time collision warning are carried out based on the model, a collision-free motion trajectory is planned through inverse kinematics, and adaptive closed-loop material distribution control is realized according to drop point information fed back by vision. The system integrates data acquisition, processing and reconstruction, scene recognition and control modules. The pump truck applying the application has high-precision environment sensing and real-time obstacle avoidance capability, can realize full-automatic and accurate material distribution, and significantly improves operation safety and efficiency.

The application discloses a kind of training map element mining network model method, device and readable storage medium.Map element mining network model is used to perceive map element in photo, method includes obtaining initial photo for marking high-precision map element;Initial photo is segmented into multiple picture blocks;According to preset proportion, multiple picture blocks are randomly occluded to obtain occlusion area and visible area;According to visible area, occlusion area is completed to obtain completed picture;When the pixel value of the same position of completed picture and initial photo exists difference value, difference value is used to adjust map element mining network model, and the difference value of the pixel value of the same position of the picture completed by the map element mining network model after adjustment and initial photo is less than set value, can save the cost of manual labeling map element, and make the map element mining network model after training can accurately perceive the new and unusual map element in photo.

The application relates to the technical field of automatic driving and provides an automatic driving assistance method and system, which comprises the following steps: acquiring point cloud data, wherein the point cloud data is data information acquired by a detection signal emitted by a laser radar installed on a first vehicle; generating a two-dimensional image according to the point cloud data, wherein the two-dimensional image is a two-dimensional image of the surrounding environment of the first vehicle perceived by the laser radar installed on the first vehicle; performing feature extraction on the two-dimensional image by using a neural network model to obtain feature information, wherein the feature information comprises feature information of each foreground point in the two-dimensional image; performing clustering on each foreground point in the two-dimensional image based on the feature information to obtain an instance segmented two-dimensional image; and assisting a user in taking over the first vehicle according to the instance segmented two-dimensional image, so that the automatic driving vehicle can accurately and quickly perceive the surrounding environment, the driving personnel can take over the vehicle in the automatic driving according to the perception result, and the safety of the automatic driving is improved.

The application relates to the technical field of audio processing, and discloses a vibration compensation audio processing system, which comprises a vibration sensing module connected with an audio signal processor, is used for collecting vibration signals between a vehicle body and a sound equipment in real time and transmitting the vibration signals to the audio signal processor; the audio signal processor is connected with the vibration sensing module, a loudspeaker and a control unit respectively, is used for receiving vibration-related signals and original audio signals, generating vibration compensation signals, superimposing the vibration compensation signals on the original audio signals and transmitting the superimposed signals to the loudspeaker; and the loudspeaker is used for converting electric signals into sound waves by receiving the superimposed audio signals and outputting the superimposed audio signals. The vibration sensing module is used for collecting multi-modal signals and extracting vibration features, so that the problem that audio signals are prone to distortion and sound quality is reduced in vehicle driving caused by the fact that most traditional vehicle-mounted audio systems adopt hardware isolation and software filtering to reduce the influence of vibration on audio signals is solved.

The invention discloses an environment-based adaptive braking method and device, a storage medium and equipment, and belongs to the technical field of deep learning. Collecting vehicle state data, vehicle exterior environment data, surrounding vehicle data and user behavior data; processing the vehicle state data and the vehicle exterior environment data by using LSTM to obtain environment change trend characteristics; carrying out fusion processing on the environment change trend characteristics, the vehicle exterior environment data, the surrounding vehicle data and the user behavior data by utilizing Random Forest to obtain a structured rainy day scene label; a basic braking parameter matched with the rainy day scene label is searched in a dynamic rule base, the optimization model is used for optimizing the rainy day scene label and the basic braking parameter, and a braking control instruction is obtained; and the braking control instruction is sent to the vehicle, so that a braking system in the vehicle executes braking operation based on the braking control instruction. According to the invention, self-adaptive braking can be carried out in a rainy day scene, and the safety is improved.

The invention relates to the technical field of compressed air energy storage power station inspection, and provides a compressed air energy storage power station multi-sensing cooperative inspection method and system, and the method comprises the steps: arranging a plurality of sensors in each core monitoring region of a compressed air energy storage power station to form a sensor network for cooperative monitoring; performing feature extraction on the sensor monitoring data, fusing the sensor features of the same equipment, calculating the equipment state credibility based on the fused features, and when the credibility exceeds the state early warning threshold range, performing early warning; packaging the historical monitoring data, the feature fusion result and the credibility calculation result of the equipment in a preset duration range to form an enhanced data packet; and constructing a three-dimensional digital twinborn model, mapping the real-time sensor data and the enhanced data packet of the related equipment into the three-dimensional digital twinborn model, and carrying out analysis and calculation based on the real-time sensor data and the enhanced data packet to obtain an equipment data analysis and calculation result. The safety and reliability of the power station can be remarkably improved.

This invention discloses a grouped point cloud-driven arm-hand operating system. The arm-hand operating system includes a VR-based teleoperation data acquisition module, an environmental perception and encoding unit, and a two-layer feature fusion diffusion denoising model. Specifically: the VR-based teleoperation data acquisition module consists of a posture recognizer, a posture mapper, and a data storage module; the environmental perception and encoding unit consists of a point cloud grouper, a point cloud encoding module, and a state integrator; and the two-layer feature fusion diffusion denoising model consists of a two-layer feature fusion module and a diffusion denoising network. This arm-hand operating system can respond to environmental changes in real time, achieving comprehensive scene perception while quickly formulating task execution plans. This data acquisition-algorithm deployment collaborative framework effectively solves the challenge of balancing cost, speed, and accuracy in intelligent arm-hand operation, providing a cost-effective solution for embodied intelligence, robotic operations, and other fields.

Embodiments of the present application provide a camera calibration method, a device with an automatic driving function, and a computer storage medium, wherein the camera calibration method comprises: acquiring three-dimensional point cloud data and two-dimensional image data of an environment in which a device with an automatic driving function is located, which are collected by the device in a straight driving state; determining a first ground normal of the device in an IMU coordinate system according to the three-dimensional point cloud data; determining a second ground normal of the device in a camera coordinate system according to the two-dimensional image data; determining a corresponding roll angle of the device according to the first ground normal and the second ground normal; and performing camera calibration on the device according to at least the roll angle. Through the embodiments of the present application, camera calibration can be effectively performed.

The application relates to the technical field of temperature control of crystal growth equipment, in particular to an intelligent temperature control system and method of a crystal growth furnace. The system comprises a data acquisition module, a calculation module, a control module and an optimization module; wherein the data acquisition module acquires physical parameters in the furnace and crystal quality parameters in real time; the calculation module dynamically determines a temperature control precision level and a temperature deviation threshold value by calculating thermal resistance values of non-uniform grid nodes, and outputs a control instruction; the control module adjusts the temperature in response to the control instruction; and the optimization module establishes a correlation model of defect density and temperature fluctuation, and corrects the thermal resistance values of the grid nodes. The application realizes accurate temperature control in the whole cycle of crystal growth, improves temperature regulation precision and control strategy adaptability, and improves crystal quality and yield.

This application provides a vehicle-mounted equipment cabin and system for dike hazard inspection based on multi-source sensing, belonging to the field of water conservancy engineering safety monitoring technology. The vehicle-mounted equipment cabin includes an operation command center, a drone and its nest module, an unmanned surface vessel and its cabin module, and a vehicle-mounted meteorological instrument module. The drone and its nest module is equipped with a lidar camera for aerial three-dimensional measurement and a thermal imager for dike thermal anomaly detection. The unmanned surface vessel and its cabin module is equipped with a multi-beam echo sounder for underwater three-dimensional measurement. The vehicle-mounted meteorological instrument module is fixed to the upper surface of the vehicle-mounted equipment cabin and is used to collect environmental meteorological parameters. The operation command center houses a water conservancy drone inspection cockpit system, which receives multi-source data from the drone and its nest module, the unmanned surface vessel and its cabin module, and the vehicle-mounted meteorological instrument module for multi-source data fusion. This solution achieves the location and identification of dike safety hazards through integrated air-ground-water collaborative detection.

The utility model relates to a temperature sensor structure which comprises a temperature sensing shell, a limiting frame, a single-end output temperature sensing device and an elastic piece. The temperature sensing shell is provided with a containing groove, and the limiting frame is connected with the temperature sensing shell and partially extends into the containing groove to form an abutting table. The single-ended output temperature sensing device comprises a sensing head and two transmission lines, one end of the sensing head abuts against the containing groove, and the transmission lines are arranged on the limiting frame in a penetrating mode. The elastic piece is arranged between the inductive head and the abutting table and provides abutting force towards the direction of the containing groove for the inductive head. In the structure, the limiting frame and the temperature sensing shell provide stable supporting and positioning for the temperature sensing device, and the correct position of the temperature sensing device is ensured; the elastic piece enables the sensing head to be in close contact with the temperature sensing shell all the time. The problem of poor contact caused by change of the type of the sensor is solved, no matter how the type of the sensor changes, as long as the inductive head can be placed in the containing groove, the elastic piece can tightly abut against the inductive head through elastic force, and therefore good heat conduction efficiency and accurate temperature reading are guaranteed.

The application discloses a representative monitoring data-driven water diversion project check gate over-flow formula partition construction method, which comprises representative monitoring data set construction, over-flow state division, partition over-flow formula description, flow state transition interval segmentation point optimization model, each flow state partition over-flow formula coefficient calibration, partition over-flow formula result model verification and evaluation, check gate over-flow dynamic prediction and the like. Advantages are that different flow states are partitioned and fitted, and corresponding function expressions are constructed to improve over-flow simulation precision. The method provides a reference for water delivery scheduling work condition pre-play and scientific scheduling plan making, and further provides technical support for open channel water diversion project water supply safety.

This invention discloses an adaptive router and its routing method based on a three-dimensional on-chip network with irregular inter-layer interconnections. It utilizes the vertically connected topology of the three-dimensional on-chip network, a healthy TSV (Through Silicon Via) location mechanism, and a congestion propagation network to adaptively reconstruct routing paths based on congestion level, injection rate, and TSV availability. By designing healthy TSV information tables, healthy TSV distance information tables, healthy TSV congestion information tables, a routing decision module, and healthy TSV propagation and congestion awareness mechanisms, it achieves collaborative operation between distance-based and congestion-based routing algorithms to reduce performance losses caused by congestion and failures. This invention uses relatively low hardware overhead, enhances the reliability and adaptability of three-dimensional on-chip network routing, and effectively reduces the average packet latency in the presence of irregular vertical interconnections and dynamic network traffic changes, significantly improving the overall performance and robustness of the system under fault and congestion environments.

This invention discloses a smart maintenance method, equipment, and computer storage medium for highway electromechanical equipment, relating to the field of highway electromechanical equipment maintenance technology. The method includes: collecting equipment operation data, cleaning and extracting features from the data to obtain a standardized multimodal feature set; calculating the current health index of the equipment based on the multimodal feature set through weighted fusion, and classifying the equipment health level according to the health index; when the health level reaches a preset trigger condition, inputting real-time and historical multimodal feature sequences into a pre-trained long short-term memory network model, and outputting a predicted value of the equipment's remaining service life; automatically generating maintenance work orders based on the health index and the predicted value of the remaining service life, and dynamically scheduling maintenance resources in conjunction with maintenance personnel location, spare parts inventory, and traffic flow information. This invention solves the technical problems of slow response, incomplete status perception, and high maintenance costs existing in the prior art.