2824 results about "Real time display" patented technology

The invention relates to a steel logistics full-process real-time dynamic management method and device, and belongs to the technical field of steel logistics control methods and devices. According to the technical scheme of the invention, data acquisition and monitoring are carried out, and transport vehicle and cargo states are tracked; demand prediction and inventory dynamic adjustment are carried out, and high-frequency cargo response emergency orders are allocated according to shipment frequency; visual management of the supply chain is carried out, shared data of all links of the supply chain is established, a 3D logistics map is constructed, and inventory, transportation states and bottleneck nodes are displayed in real time; and risk control management: quickly starting the alternative scheme when the early warning is triggered. The method has the advantages that efficiency is optimized, limitation of a traditional single transportation mode is reduced, rolling updating and emergency response of demand prediction are achieved, data transparency and credibility are improved, rapid risk response is achieved, and logistics full-life-cycle management is achieved.

The invention belongs to the technical field of data processing, and provides a multi-source data fused building settlement trend prediction method, device and medium, and the method comprises the steps: firstly collecting multi-source monitoring data of a target building, then carrying out the preprocessing and fusion, obtaining fusion feature data, inputting the fusion feature data into an AI prediction model, and obtaining a target building settlement trend prediction result; and finally, combining the real-time settlement amount, the settlement rate and the settlement trend prediction result in the fused feature data, comparing with a preset early warning threshold value, and judging whether an early warning instruction is triggered or not. If the early warning instruction is triggered, a corresponding alarm is given out, and the real-time settlement amount, the settlement rate and the settlement trend prediction result are displayed in real time. Through cooperation of multi-source data fusion and the scene adaptive AI model, accurate prediction and timely early warning of the settlement trend of the building are realized, the core is to break through the limitation of single data and a fixed model, and the precision of settlement prediction and the timeliness of risk response in a complex scene are remarkably improved.

An AI-driven centralized orchestration system (100) with MCP protocol for real-time compliance and risk data management, including: a. a centralized integration and orchestration platform configured to connect heterogeneous enterprise IT systems through standardized API connections and execute automated workflows; b. a variety of domain-specific artificial intelligence (AI) agents that interface with IT service management (ITSM), vulnerability management, and endpoint and asset management platforms for data collection, analysis, and assessment; c. a Multi-Agent Communication Protocol (MCP) layer that enables structured communication, negotiation and coordination between AI agents in real time; d. a data consolidation module configured to aggregate, standardise and align heterogeneous data into a unified repository using machine learning models; e. a compliance reporting module for dynamically generating and distributing audit-ready compliance reports based on AI-analyzed data and triggered workflows; f. an alerting module configured to deliver context-dependent predictive notifications of compliance violations or risk anomalies through various communication channels; g. a predictive dashboard module capable of displaying compliance status, risk metrics, and proactive insights in real time via AI-driven visualization tools; i.e., where the orchestration platform, AI agents, and MCP layer together enable automated, scalable, and proactive compliance and risk actions.

The invention relates to the technical field of display control, in particular to an LED screen display control method and system and an LED screen. The method comprises the following steps: acquiring multi-modal stage sensing data and LED screen real-time display data, and performing stage performance environment perception according to the multi-modal stage sensing data and the LED screen real-time display data to obtain stage environment perception data; performing flow scene coding prediction based on the stage environment perception data to obtain renderable scene factors; obtaining display content data of the LED screen, and analyzing a pre-output picture of the LED screen to obtain visual pre-output data of the LED screen; performing multi-modal stage dynamic characteristic reasoning according to the LED screen visual pre-output data and the renderable scene factors to obtain a stage visual dynamic output structure diagram; and performing real-time heterogeneous driving rendering on the stage visual dynamic output structure diagram to obtain a millisecond LED rendering diagram block data set. According to the invention, the display response precision and the picture adaptation capability of the LED screen can be improved.

The invention relates to the technical field of display, and particularly discloses a dynamic ambient light adaptive OLED display optimization method and system, and the method comprises the steps: obtaining an ambient light time sequence data set of an environment where an OLED display screen is located, and synchronously obtaining real-time display parameters and historical brightness adjustment data of the display screen; acquiring ambient light sensing features according to the ambient light time sequence data set; obtaining photo-thermal structure coverage area data of the OLED display screen according to the real-time display parameters; and acquiring preliminary optimization parameters according to the ambient light sensing characteristics and the photo-thermal structure coverage area data. According to the invention, illumination intensity, spectrum drift and contrast change are captured in real time in combination with ambient light perception characteristics, the one-sidedness of adjustment only according to brightness traditionally is solved, reflection can be reduced through photothermal structure deformation under strong light, brightness can be improved to offset interference, and human visual characteristics can be matched under weak light. And the display definition and the visual comfort in different environments are effectively improved.

The invention provides an AR intelligent shopping guide interaction method and system applied to store management, and the method comprises the steps: firstly obtaining an interaction data set of a user in a store, covering a user position movement track, a commodity attention action sequence and voice consultation content, carrying out the user intention analysis of the interaction data set, and carrying out the user intention analysis of the interaction data set; the method comprises the steps of obtaining commodity demand characteristics and interaction preference characteristics, generating AR shopping guide interaction content, including commodity three-dimensional display information and an interaction guide instruction, adaptive to a user based on the commodity demand characteristics and the interaction preference characteristics, aligning and fusing the AR shopping guide interaction content with a store physical scene space, generating an AR shopping guide interaction scene capable of being displayed in real time, and displaying the AR shopping guide interaction scene in real time. And finally, responding to user interaction operation in the AR shopping guide interaction scene, generating feedback information and updating the interaction data set to trigger interactive process iterative optimization, thereby providing personalized and immersive shopping guide experience, and improving store operation efficiency and customer satisfaction.

The invention provides a stroke patient gait walking analysis method and device. The stroke patient gait walking analysis method comprises the steps that pressure data and inertial data generated in the gait walking process of a patient are collected based on a plantar pressure sensing module and an inertial measurement module; performing data preprocessing on the pressure data and the inertial data; constructing a double-flow neural network to respectively extract pressure features and inertial features of the pressure data and the inertial data, performing feature fusion, and calculating step length, stride frequency, gait asymmetry index and gait stability index key indexes based on the fused features so as to realize gait evaluation; an evaluation result is transmitted to the flexible OLED touch screen, and gait parameters, rehabilitation progress, abnormal early warning and training guidance information are displayed in real time through the flexible OLED touch screen. According to the method, the end-to-end process from original sensor data to clinical application is realized, manual monitoring is avoided, the accuracy and clinical practicability of evaluation are improved, and the method is particularly suitable for family rehabilitation monitoring of stroke patients and precise rehabilitation evaluation of medical institutions.

The embodiment of the invention provides a half-coal rock roadway surrounding rock loose circle dynamic detection device based on three-dimensional laser scanning, and belongs to the technical field of optical measurement. According to the dynamic detection device for the loose circle of the surrounding rock of the half-coal-rock roadway based on three-dimensional laser scanning, three-dimensional point cloud data of surface characteristics of the surrounding rock of the roadway are obtained by performing three-dimensional laser scanning on the surrounding rock of the half-coal-rock roadway, and a three-dimensional surrounding rock model of the surrounding rock of the roadway is newly built based on the preprocessed three-dimensional point cloud data; and performing surrounding rock surface characteristic comparison based on the three-dimensional surrounding rock model and the surrounding rock reference model, and determining a loosening circle area where the roadway surrounding rock is loosened. And finally, a monitoring report is generated based on the newly built three-dimensional surrounding rock model of the roadway surrounding rock, and the surrounding rock surface characteristics of the three-dimensional surrounding rock model are displayed in real time, so that the spatial distribution and change conditions of the loose circle of the roadway surrounding rock can be accurately obtained in real time, dynamic monitoring can be performed, and the safety of mine engineering is ensured.

The invention provides an AR-assisted acupoint dynamic positioning method and system based on biological characteristics, and relates to the technical field of medical assistance, and the method comprises the steps: building a three-dimensional body model based on the body shape point cloud data, collected in real time, of a current user, and calculating the theoretical coordinates of acupoints in combination with a traditional Chinese medicine acupoint positioning rule; dynamically calibrating the theoretical coordinates on the basis of synchronously acquired body surface conductivity change characteristics and body surface temperature distribution characteristics of the to-be-acupunctured body area of the current user, and generating acupuncture point coordinates and corresponding needle inserting parameters; the acupuncture point coordinates are mapped to the body part of the current user, visual acupuncture point marks are displayed in real time through AR equipment, and operation guidance related to the needle inserting parameters is synchronously provided; when it is detected that the body position change of the user exceeds the preset threshold value, the above steps are executed again, and the acupoint coordinates and the operation guidance are updated, and through multi-modal biological feature fusion, dynamic calibration and AR visualization interaction, acupoint positioning is precise, dynamic and visualized.

The utility model relates to the technical field of belt conveyors, in particular to a movable high-precision intelligent belt constant feeder which comprises a conveying support, a conveying belt and a weighing assembly, the conveying belt is rotationally arranged on the conveying support, and the weighing assembly comprises a weighing roller, a weighing sensor, a speed sensor, a controller and a digital display dial plate. The weighing roller is arranged in the conveying belt and abuts against the conveying belt, the weighing sensor is connected with the weighing roller and the conveying support and used for outputting weight signals, the speed sensor is arranged in the conveying belt and used for outputting speed signals, and the controller is electrically connected with the weighing sensor, the speed sensor and the digital display dial plate. The controller responds to the weight signal and the speed signal and is used for controlling the digital display dial plate to display the weight value in real time. The bulk cargo transfer weight measuring device has the effect that the bulk cargo transfer weight can be accurately measured in the conveying process of the conveying belt.

The invention discloses an optical cable icing galloping online monitoring system based on a BOTDR, and belongs to the technical field of distributed optical fiber sensing. The system comprises an optical module, a signal processing module and a data processing module, the optical module is used for generating a detection light signal and interacting with a sensing optical fiber to obtain a Brillouin scattering signal, and then the Brillouin scattering signal is converted into an electric signal; the signal processing module is used for performing frequency down-conversion, signal filtering and digital acquisition on the electric signal to obtain multiple groups of Brillouin scattering signal data; the data processing module is used for processing the multiple groups of Brillouin scattering signal data and extracting a Brillouin frequency shift center frequency; temperature and strain distribution along the optical cable is obtained according to the frequency shift, and temperature and strain states are transmitted to a QT upper computer through PCIE for real-time display. According to the invention, high-precision and long-distance optical cable icing galloping monitoring can be realized, reliable early warning and safety guarantee are provided, and technical support is provided for maintenance and management of an electric power system.

The invention relates to the technical field of intelligent operation and maintenance management of an energy storage power station, and provides an energy storage power station efficient operation and maintenance management system fusing AI and the Internet of Things, and the system comprises an Internet of Things data collection module which is used for obtaining multi-source heterogeneous data of a battery pack, an inverter and an environment sensor in the energy storage power station in real time; the AI analysis module comprises an anomaly detection unit, a performance prediction unit and a scheduling decision unit which are respectively used for anomaly probability calculation, equipment performance degradation trend prediction and optimal charging and discharging strategy generation; the dynamic optimization control module receives an instruction of the scheduling decision-making unit and adjusts operation parameters of the energy storage power station through a dynamic load adjustment algorithm; and the visual interaction module integrates an equipment state three-dimensional mapping interface and an alarm pushing unit, and displays the decision result of the AI analysis module and the equipment health degree score in real time. The operation and maintenance management efficiency can be improved, the reliability and safety of equipment operation are enhanced, the operation and maintenance cost is reduced, and the service life of equipment is prolonged.

The invention discloses a fire extinguishing system and method for accurate positioning of thermal runaway of a container type energy storage power station. The fire extinguishing system is composed of an energy storage power station, battery packs distributed in an array mode and a fire extinguishing system body. Each battery pack is provided with a ventilation safety valve and a fire extinguishing device, a hydrogen sensor array covering the whole area is arranged on the plane of the energy storage power station, the ventilation safety valves guide out hydrogen generated in the initial stage of thermal runaway, and the sensor array monitors the concentration of the whole area in real time. The industrial personal computer receives sensor data, constructs a gas concentration distribution diagram by combining pre-stored battery pack space distribution information, and displays a thermal runaway area on the display screen in real time. The positioning program analyzes a hydrogen concentration field based on gas diffusion characteristics, and after the position of a fault battery pack is accurately recognized, the industrial personal computer immediately triggers the fire extinguishing device in the corresponding pack to implement fixed-point fire extinguishing, so that an early fire extinguishing closed loop is formed. According to the system, through multi-sensor data fusion and gas distribution mapping technologies, rapid positioning and accurate suppression of a thermal runaway source are achieved, and the safety protection level of an energy storage power station is effectively improved.

The invention discloses an intelligent pressure maintaining control method for a thin-wall product of an injection molding machine based on mold pressing feedback. The intelligent pressure maintaining control method comprises the following steps: (1) constructing a hardware layer; (2) configuring a software layer; (3) a mold cavity pressure acquisition module acquires original pressure data in the injection mold cavity in real time through a pressure sensor; (4) the data preprocessing module carries out filtering processing on pressure signals generated by the pressure data, and (5) the dynamic pressure maintaining control module dynamically adjusts pressure parameters and pressure maintaining time by receiving the real-time pressure data, product wall thickness parameters, mold structure parameters and injection molding process parameters, generates a pressure maintaining control instruction and sends the pressure maintaining control instruction to an injection molding machine control system; driving the injection molding machine to execute pressure maintaining action; (6) the dynamic pressure maintaining control module associates and stores the pressure change curve and the parameter adjustment record in the pressure maintaining process in a feedback learning module, and optimization calculation is carried out; and (7) the man-machine interaction interface displays the pressure change curve, the pressure maintaining control parameters and the forming state of the injection mold cavity in real time.

The invention discloses an underwater micropterus salmoides body length and mass measurement method, and relates to the technical field of aquaculture. Comprising the following steps: 1) target detection and key point detection: performing target detection and key point detection on underwater largemouth bass by using a YOLOv8 model to obtain key point coordinate information of a fish head and a fish tail; and 2) obtaining depth information: obtaining the depth information of the underwater image through a monocular depth estimation algorithm, and calculating the body length of the largemouth bass in combination with a key point detection result. And 3) mass estimation: based on the body length information, estimating the mass of the micropterus salmoides through a power function regression model. And 4) model deployment: deploying the model in a recirculating aquaculture monitoring system, and displaying and recording the body length and quality information of the micropterus salmoides in real time. According to the method, the body length and the body weight of the largemouth bass can be obtained in real time in a non-contact mode, the method is suitable for a factory-like circulating water culture mode, data support can be provided for culture management, and the practical value and the popularization prospect are high.

The invention discloses a new energy vehicle endurance display method and system based on a power battery SOH, electronic equipment and a vehicle. The method comprises the steps that a vehicle, a vehicle control unit, a battery management system and a display module are triggered to be started through a KL15 signal wake-up signal, and power-on initialization and self-inspection are executed; after the self-inspection is completed, reading the stored current state-of-health initial value SOH0 of the power battery and the stored current state-of-charge initial value SOC0 of the power battery from the EEPROM; performing dynamic correction on the read SOC value, performing fixed value locking on the SOH value, and sending the corrected SOC value and the locked SOH value to a CAN bus of the whole vehicle; based on the SOH0 and the SOC1 sent by the battery management system, the remaining endurance mileage S is calculated in combination with the total delivery mileage L of the new vehicle; and the instrument and large-screen display module is used for displaying the current remaining endurance mileage in real time. According to the method, the problem of display deviation caused by neglecting battery aging in a traditional method is solved, and the user driving experience and the battery management efficiency are improved.

A system for dynamic content generation for contact center interactions using artificial intelligence according to an embodiment includes determining, by a computing system and using an artificial intelligence model, an intent of an interaction between a contact center agent and a client based on a live transcript, identifying, by the computing system in real time, at least one image relevant to the determined intent in response to determining the intent of the live transcript, displaying, by the computing system in real time, the at least one image for the contact center agent on a dynamic interaction widget application executed by an agent device of the contact center agent, and sending, by the computing system, a selected image of the at least one image displayed on the dynamic interaction widget application to the client in response to selection of the selected image by the contact center agent.

This application discloses a renal puncture guidance method, system and computer device based on multi-modal fusion, the method comprises: acquiring a medical image sequence of an object to be examined, and performing three-dimensional reconstruction based on the medical image sequence to obtain a three-dimensional reconstruction model; obtaining a slice corresponding to an ultrasonic probe currently in the three-dimensional reconstruction model; displaying a fusion image obtained from a real-time ultrasound image acquired by the ultrasonic probe and the slice in a first region of a puncture guidance interface; acquiring a needle insertion angle of a puncture needle, and displaying a puncture guide line in the fusion image in real time; and displaying the ultrasonic probe model, the puncture needle model and the three-dimensional reconstruction model in real time in a second region of the puncture guidance interface.

An intelligent cooling system for dynamic monitoring, prediction and optimization of storage conditions in real time, consisting of: a refrigerator with heat-insulated walls; a sensor array in the refrigerator comprising temperature sensors, humidity sensors, pressure sensors, and pathogen detection biosensors, the sensor array being configured to continuously monitor internal environmental parameters in the refrigerator and external environmental conditions; a control dashboard configured to display real-time environmental data and enable remote monitoring and manual adjustment of the environment in the refrigerator; an Internet of Things (IoT) communication module configured to transmit the monitored internal and external environmental data to the control dashboard; a proportional-integral-derivative (PID) controller operatively connected to the IoT communication module and configured to analyze the monitored data and calculate correction factors to maintain optimal environmental conditions; a plurality of actuators within the refrigerator, the plurality of actuators comprising a temperature actuator, a humidity actuator, and a pressure actuator, the actuators being configured to independently adjust temperature, humidity, and pressure within the refrigerator based on the control instructions; a processor configured to execute machine learning algorithms to analyze historical and real-time sensor data, predict optimal environmental conditions based on the analyzed data, and generate control instructions for the actuators based on the predicted optimal environmental conditions and the calculated correction factors; and a solar power supply configured to provide energy for operating the system.

The present invention comprises a novel social media video debating web and mobile application. The platform will provide a space for users to debate uninterrupted by both the audience and the opponent whereby each participant is given a set time to express their thoughts on a subject matter. The online debate platform provides a controlled setting for the participants to have their debates viewed, voted on and subsequently ranked by the other users of the platform. The online debate platform is also monitored by a unique AI system that updates debate “winners,” flags offensive content, and moderates each debate on the platform in real time. The disclosed platform and following figures will provide a space for individuals to debate subjects in a uniformed structure and have real-time results from active user viewership. The online debate platform aims to provide an established place for constructive debating.

The invention discloses an aircraft wake flow real-time monitoring method based on laser radars, and the method comprises the steps: collecting the real-time wake flow data in a five-side approaching stage of a front aircraft through a plurality of laser radar devices, and determining the space coordinates and three-dimensional contour of the edge of a wake flow region through an edge detection algorithm; according to the coordinates of the left and right edges and the upper and lower edges of the wake flow area, the front and tail flow areas are displayed in real time; the method comprises the following steps: intercepting a two-dimensional cross section of a front aircraft tail flow area at a rear aircraft real-time flight height, calculating a rolling instability index generated by the two-dimensional cross section area to a rear aircraft wing, determining a wake flow minimum safety interval according to a preset rolling instability index threshold value, and displaying the wake flow minimum safety interval on an air traffic control system radar interface in real time, thereby realizing the purpose that in a five-side approach stage of an aircraft, the flight speed of the aircraft is increased. The front aircraft wake flow area and the rear aircraft wake flow area are displayed in real time, and the minimum safety interval of the front aircraft and the rear aircraft considering the real-time flight height is considered, so that an air traffic controller can clearly know the real-time state and the potential risk of the aircraft wake flow, and the wake flow monitoring accuracy and the flight safety are improved.

The invention discloses a mechanical arm regulation and control multi-sensor array underground structure detection system and detection method based on reinforcement learning, a vibration source module provides a sweep frequency vibration signal, a multi-sensor array collects a reflected signal, a data processing module receives and processes the reflected signal, and the data processing module receives and processes the reflected signal; the imaging module generates a three-dimensional underground structure image through a wave velocity inversion and reverse time migration imaging technology, the intelligent optimization and adaptive adjustment module adaptively adjusts vibration source signal parameters and sensor array layout through a reinforcement learning algorithm, and the display terminal displays detection data and imaging results in real time and provides parameter optimization suggestions. According to the invention, real-time and automatic adjustment of vibration source signals and sensor layout is realized through an intelligent optimization and adaptive adjustment module constructed through a reinforcement learning algorithm, and a high-resolution underground structure three-dimensional image is generated accordingly. And an efficient and accurate underground structure identification and positioning scheme can be provided.

Methods, apparatus, systems, and articles of manufacture are disclosed to display acquisition paths. An example apparatus includes a display handler to, in response to a directional condition of an autonomous vehicle satisfying a threshold, render an acquisition path for the autonomous vehicle, the acquisition path specifying a route along which the autonomous vehicle is to travel to acquire a guidance path; and a vehicle condition controller to, in response to determining that a real time display criterion is satisfied, redetermine whether the directional condition of the autonomous vehicle satisfies the threshold to cause the display handler to re-render the acquisition path.

The invention discloses a method for processing three-dimensional scanning data. The method comprises the following steps: acquiring the three-dimensional scanning data of a target object; performing fusion processing on the three-dimensional scanning data under the first resolution to obtain first point cloud data; in response to a second resolution, performing fusion processing on the three-dimensional scanning data to obtain second point cloud data, the value of the first resolution being greater than the value of the second resolution; and performing duplicate removal and fusion on the first point cloud data and the second point cloud data to obtain multi-resolution point cloud data of the target object, and finally displaying the multi-resolution point cloud data. According to the invention, the range of the point cloud displayed in real time in the scanning process is consistent with the range of the finally displayed point cloud.

The invention discloses a fire equipment management method and system based on a railway tunnel fire-fighting monitoring system, and relates to the technical field of tunnel fire fighting, and the system comprises a fire-fighting monitoring module which is used for collecting multi-dimensional state data of fire equipment in real time; the redundant data processing module adopts a hot standby redundancy mechanism and is used for analyzing and processing the multi-dimensional state data of the fire equipment in real time and generating a fire risk assessment report; an emergency scheduling plan is called based on the fire risk assessment report, and an execution instruction is generated and issued to the execution module; the execution module is used for controlling fire equipment to work according to the execution instruction; and the data display module is used for displaying the multi-dimensional state data, the fire risk assessment report and the emergency scheduling plan of the fire equipment in real time. According to the invention, potential safety hazards can be found earlier, early warning of fire risks is realized, the accuracy and timeliness of fire warning can be obviously improved, and thus precious time is won for taking effective prevention measures.

The invention belongs to the technical field of clamping, and discloses a large thin-wall shell self-adaptive floating shape follow-up clamp and a force feedback clamping method. The large thin-wall shell self-adaptive floating shape follow-up clamp has certain flexibility and can clamp a large thin-wall shell workpiece in a self-adaptive floating shape follow-up mode. The large thin-wall shell self-adaptive floating shape follow-up clamp can achieve the full-surface clamping force feedback function of a large thin-wall shell workpiece. Force sensors are arranged below the circumferential floating supporting module and the top supporting module, the clamping force can be monitored and displayed in real time through a PLC control system, the purposes of quantitatively applying the clamping force and conducting self-adaptive feedback adjustment on the clamping force are achieved, and the clamping precision is improved. The large thin-wall shell self-adaptive floating shape follow-up clamp can achieve automatic clamping and releasing of a large thin-wall shell workpiece. Based on a PLC control system, the top supporting module and the circumferential floating supporting module are controlled through air pressure and servo, the end face positioning device is driven through oil pressure, automatic clamping and releasing are achieved, manual participation is reduced, and the clamping efficiency is improved.

The invention provides a power equipment three-dimensional dynamic updating method and system for virtual reality training, and the method comprises the steps: collecting the working state data of power equipment in real time through a sensor; processing the working state data based on a preset function model, and calculating the physical state change of the power equipment; according to the physical state change, adjusting physical attributes of the three-dimensional model of the power equipment in real time so as to simulate physical effects of thermal expansion, stress concentration or structural deformation; loading the adjusted three-dimensional model into a virtual reality environment, and performing real-time display through a virtual reality rendering platform; and after the user executes the interactive operation through the virtual reality equipment, the working state of the power equipment is updated, and the influence of the operation on the three-dimensional model of the equipment is dynamically fed back, so that a virtual-real linkage closed-loop training process is formed. The virtual model can change in real time along with the collected data, and the technical verisimilitude and operability of virtual training are remarkably improved.

The invention relates to the technical field of catenary fault detection, and discloses a catenary fault detection method and system based on image recognition. According to the method, multi-spectral image acquisition equipment is deployed along a contact network, and a multi-angle image sequence of contact network components is acquired in real time; performing space-time alignment processing on the image sequence to generate a standardized image data set; constructing a catenary part segmentation model based on the data set, and identifying key parts by means of a deep semantic segmentation technology; extracting a geometric feature map and a deformation feature map, and establishing a component state feature library; analyzing a topological relation among the component characteristics through a space correlation module, and generating a fault correlation graph; updating the atlas by adopting a dynamic feature correction algorithm, and outputting a fault probability distribution matrix; comparing the matrix with a preset fault threshold set, and generating a fault positioning instruction; and after multiple rounds of correction by the iterative optimization module, a final fault detection report is output and is displayed on the human-computer interaction platform in real time, and parameter configuration is supported.

The invention discloses an unmanned aerial vehicle tilt video and vector map real-time projection sleeving method, which comprises an unmanned aerial vehicle body, and is characterized in that a video data acquisition module and a video preprocessing module for preprocessing the tilt video acquired by the video data acquisition module are arranged in the unmanned aerial vehicle body; a map data processing module is further arranged in the unmanned aerial vehicle body, an improved ORB algorithm is adopted in the feature extraction and matching module, and a posture correction and projection transformation module used in cooperation with the video data acquisition module is installed in the unmanned aerial vehicle body. And a real-time display module in the unmanned aerial vehicle body displays the sleeved video and vector map on terminal equipment in real time through a signal module arranged in the unmanned aerial vehicle body. The problems that the real-time performance is poor, the nesting precision is reduced, and long-time high-precision nesting cannot be achieved during working in an existing unmanned aerial vehicle tilt video and vector map fusion technology at present are solved.

The invention provides a multi-scene self-adaptive guide robot interaction method and system in the technical field of guide robots. The method comprises the steps that S1, a guide robot obtains interaction voice and converts the interaction voice into an interaction text; s2, analyzing the interaction text to generate a reply text, converting the reply text into a reply voice, and playing the reply voice for interaction; s3, managing the dialogue content in the interaction process; s4, the guide robot moves based on the guide path in the interaction process, and automatically plays explanation voice when arriving at the guide point; step S5, when the interaction text carries the target point, planning an advancing path to the target point through a bidirectional progressive optimal search algorithm; and S6, displacement is carried out based on the advancing path, and operation information of the robot is displayed in real time. The method has the advantages that the efficiency and accuracy of path planning, the flexibility of voice interaction and the expansibility of the system are greatly improved, and then the user experience of guide robot interaction is greatly improved.