191results about How to "Accurate data support" patented technology

The invention discloses a multi-source data fusion transformer substation digital twinning model construction method and system, and belongs to the technical field of intelligent power grid digital twinning, and the method comprises the steps: carrying out the multi-source data collection to obtain the related data of a transformer substation, and constructing a three-dimensional entity model; deploying a multi-physical field monitoring device, constructing a real-time data acquisition network, and dynamically fusing multi-source data and a three-dimensional entity model; performing feature extraction and weighted fusion on the dynamically fused multi-source data; a multi-physics field coupling analysis model is constructed based on a deep learning network, and dynamic simulation and visualization of multiple physics fields are realized by using fusion feature data; system function modularization is achieved through a micro-service architecture, real-time updating, cross-platform deployment and multi-user interaction of a multi-physics coupling analysis model are supported, and a transformer substation digital twinborn model is obtained. According to the method, data of multiple physical quantities can be fused, multi-physical field coupling analysis is carried out, the overall layout and actual errors are optimized, and the precision and accuracy of the model are improved.

The invention belongs to the technical field of optical signal collection and imaging, and particularly relates to a multi-path nonlinear optical signal collection device. The adjusting table is used for bearing a to-be-detected sample and adjusting the spatial pose of the to-be-detected sample, the laser emitting module is used for emitting laser, the to-be-detected sample is excited by the laser to obtain a nonlinear optical signal, the nonlinear optical signal is incident to the overturning mirror through the reflection transmission unit or the transmission transmission unit, and the overturning mirror is used for adjusting the spatial pose of the to-be-detected sample through angle adjustment. The nonlinear optical signal is reflected to a first signal processing module or a second signal processing module, and the first signal processing module processes the nonlinear optical signal from the reflection transmission unit or the transmission transmission unit to obtain a spectral analysis processing result; and the second signal processing module processes the nonlinear optical signal from the reflection transmission unit or the transmission transmission unit to obtain an electric signal processing result. The device is used for collecting non-linear optical signals of far-end detection optical paths of reflection, transmission, oblique incidence and the like.

The invention relates to the technical field of thermoelectric Internet of Things security, in particular to a thermoelectric Internet of Things terminal data credible situation awareness and protection platform, which comprises an integrated architecture for constructing a distributed probe acquisition layer, a behavior modeling and knowledge base, a dynamic trust evaluation engine, a situation awareness and decision center and a credible traceability module. Multi-dimensional trust evaluation is realized by fusing terminal behavior consistency analysis, service logic compliance verification and group behavior correlation detection, a self-adaptive weight adjustment mechanism is introduced to adapt to scene change, a hierarchical protection strategy is executed based on a dynamic credibility score, and non-interruption of network disconnection protection is guaranteed by relying on edge calculation. According to the method, the data credible sensing precision is improved, dynamic differential protection is realized, the operation and maintenance cost is reduced, multiple thermoelectric scenes are adapted, and a safety guarantee is provided for stable operation of a thermoelectric Internet of Things system.

The invention provides a Bayesian-based aviation equipment residual life uncertainty prediction method and system. The method comprises the following steps: S1, constructing an observation function equation and a state parameter description equation of residual life of key or important systems, modules and parts of aviation equipment; s2, constructing an agent model; s3, solving joint posterior probability distribution and performing residual life prediction; and S4, according to the prediction probability distribution of the remaining life of the aviation equipment, generating an optimization control instruction or a maintenance instruction for the aviation equipment, and acting the optimization control instruction or the maintenance instruction on the aviation equipment. The method provided by the invention not only provides a theoretical basis for solving the problem of prediction, analysis and prediction of the service life of the aviation equipment, but also clearly defines how information and uncertainty thereof flow and convert between a physical world and a digital world, and provides a brand new thought for prediction of the uncertainty of the residual service life of the aviation equipment.

The application provides an unmanned earthwork process simulation method and system based on a dynamic three-dimensional model, basic terrain data of a work area, earthwork setting parameters and unmanned equipment attribute parameters are collected; an initial three-dimensional terrain model is constructed according to the basic terrain data, and the earthwork setting parameters and the unmanned equipment attribute parameters are mapped into the initial three-dimensional terrain model; real-time operation data of the unmanned equipment and real-time environment state data of the work area are periodically acquired, the initial three-dimensional terrain model is corrected, and a dynamic three-dimensional work model is generated; the dynamic three-dimensional work model is used to execute the unmanned earthwork process simulation, work planning and monitoring data are generated; the simulation result is output, whether the simulation result meets a preset work requirement standard is judged, when the simulation result does not meet the preset work requirement standard, the work parameters are adjusted and a re-simulation process is triggered.

This invention designs a multi-scale star surface impact crater detection method, system, and medium. The method includes the following steps: S1: Acquire star surface images and segment them into image patches of different scales; S2: Construct multiple impact crater detection sub-models; S3: Train each sub-model using star surface image patches of different scales; S4: Input the segmented star surface image to be detected into each pre-trained sub-model to obtain the detection results; S5: Select the bounding boxes with high confidence and large area among all candidate bounding boxes of each impact crater as the final detection result for that impact crater. This invention can simultaneously identify impact craters of different scales in star surface images with high accuracy, especially improving the accuracy and efficiency of identifying small impact craters, providing more accurate and comprehensive data support for lunar science research, and promoting the in-depth development of lunar exploration and geological research.

The invention provides a device and a method for on-line measurement of boron concentration in a boron trifluoride complex system, and relates to the technical field of boron-10 acid production. The device comprises a neutron emission part, a fluid circulation part, a neutron detection part and a data processing part. The neutron emission part is used for emitting thermal neutron beams, the fluid circulation part is communicated with a fluid pipeline at the bottom of an exchange rectifying tower of the boron trifluoride-anisole complex production process, and the fluid circulation part is of a neutron penetrable structure; the neutron detection part is arranged on the side, away from the neutron emission part, of the fluid circulation part and used for receiving thermal neutron beams penetrating through the boron trifluoride-anisole complex and converting neutron intensity signals into electric signals, and the data processing part is electrically connected with the neutron detection part and used for receiving the electric signals and sending the electric signals to the fluid circulation part. And inverting the concentration of boron-10 in the boron trifluoride-anisole complex according to the attenuation degree of the thermal neutron beam to obtain the total concentration of boron. The device can output the total boron concentration measurement result in real time, and sampling can be carried out without interrupting the production process.

The invention provides a teaching method and system for progressive AI ethic scene simulation in different learning segments, and the method comprises the steps: constructing a progressive AI ethic scene library in different learning segments according to different scene grades and corresponding task requirements; configuring a scene simulation platform and an AI ethic guidance module; based on the AI ethical scene library, the scene simulation platform and the AI ethical guidance module, progressive scene simulation and real-time task guidance are executed; in the process of executing scene simulation and real-time task guidance, collecting and analyzing multi-modal teaching data in real time; and based on an analysis result, generating a teaching evaluation and personalized promotion scheme. According to the AI ethical teaching system, the practicability and immersion of ethical teaching are improved, large-scale personalized teaching is realized, a scientific and comprehensive literacy evaluation standard is established, a data-driven teaching optimization closed loop is formed, and the AI ethical teaching system based on branch learning, scene simulation and intelligent guidance is constructed.

The application discloses a kind of arch bridge steel truss section cantilever assembly posture multi-eye real-time monitoring method and system, belong to construction monitoring technical field, solve the problem that traditional precision level and total station rely on professional personnel operation and data processing, cannot monitor the dynamic posture change of cable crane tower and other structures under dynamic load, the method includes segment manufacturing form record, segment assembly posture photogrammetry, segment assembly posture is measured, based on segment assembly posture solution result real-time calculation current pose and design pose error, and complete segment main pipe splicing deviation correction;In the application, the spatial coordinates of all key points can be fed back in real time, and the posture of the hoisted segment is monitored in real time. Thus, accurate data support is provided for rapid correction. A 3-eye or more industrial camera array is used to ensure unobstructed imaging of at least three non-collinear targets under complex cantilever assembly conditions, significantly improving work efficiency and reducing construction cost.

The present application relates to the technical field of coal mining simulation experiment equipment, in particular to a mine coal mining working face support simulation experiment device, which comprises an experiment box made of transparent glass material, a plurality of support plates are supported by a plurality of hydraulic cylinders at the bottom of the experiment box, a rock mass collapse simulation mechanism is arranged above the support plates, the rock mass collapse simulation mechanism is used for simulating the pressure of the support plates when the rock mass above the coal mining roadway working face breaks and collapses, so as to adjust the support strength of the support plates in the coal mining roadway, a discharge control assembly is arranged in the experiment box, the discharge control assembly is used for discharging the rock blocks above the support plates in a controlled amount, which facilitates the pressure simulation experiment of the rock mass collapse simulation mechanism on the support plates, so that the support safety and stability of the support plates in the coal mining working face on the goaf can be simulated, and more accurate data support can be provided for the construction personnel when supporting the support plates in the coal mining working face.

The invention discloses a biopsy needle assisting in positioning, and relates to the technical field related to biomedicine, the biopsy needle comprises an arranged biopsy cylinder, a handheld groove is formed in the surface of the biopsy cylinder, a needle head is connected to the side end of the biopsy cylinder through a clamping table, a limiting block is installed in the biopsy cylinder, an arc groove matched with the needle head is formed in the limiting block, and the needle head is connected with the handheld groove. An auxiliary assembly is arranged in the biopsy cylinder, a positioning lamp is installed at the side end of the biopsy cylinder, and a switch is installed at the top of the biopsy cylinder. According to the biopsy needle capable of assisting in positioning, after the biopsy needle is turned on, the positioning lamp can project light rays to assist in determining the puncture position, the positioning accuracy is improved, tissue damage caused by positioning deviation is reduced, the scale and the notch on the outer side of the needle head facilitate judgment of the length of puncturing into a human body, a tissue sample is obtained in a mechanical moving mode, and the needle head is pulled out after obtaining is completed. The driving assembly drives the moving seat to move leftwards, and the inner core is pushed back to cut off and push out the tissue sample.

The invention relates to the technical field of logistics intelligent management, and particularly discloses a large logistics cognitive collaborative management system which is constructed based on AI and an industrial internet platform and is provided with an edge layer, a platform layer, an engine layer and an application layer. The edge layer is constructed based on an IT system, OT equipment and manual filling of the logistics transportation industry, and corresponding data acquisition capability is activated according to a received data request; the platform layer starts a corresponding data processing flow according to the received task instruction; the engine layer performs analysis, identification and task planning processing on the received request, and performs intelligent analysis processing on the received data; and the application layer analyzes the received user request and outputs the received data result. According to the invention, the IT system and the OT equipment in the logistics transportation industry are integrated, intuitive and efficient cognitive collaborative management can be formed for large logistics, and a timely, comprehensive and accurate data support basis is provided for business and technical decisions of enterprises.

The present application relates to a kind of detection method and system for air bag bag production, it is related to the field of automobile passive safety technology, it includes obtaining current process number;Determine current tool number;Call in report record;Call in tool use information;Analysis report record and tool use information, to output abnormal reason;Real-time acquisition global overhead view and air bag fabric side view;Determine air bag fabric fluctuation point;Frame select air bag fabric fluctuation point corresponding fluctuation area;Determine fluctuation area height feature;Determine fluctuation area texture feature;Determine coating thickness anomaly, and output defect air bag bag signal;When there is no coating thickness anomaly, determine wrinkle area;When there is wrinkle area, execute flattening operation, and re-execute step 9 to step 12;When there is still wrinkle area after flattening operation, determine permanent wrinkle and output defect air bag bag signal.The present application has the effect of timely maintenance to tool and accurate traceability abnormal point in production process.

This invention belongs to the field of rail vehicle technology. It proposes a method and system for adjusting the alignment of workpieces during the intermediate stage of bogie welding. Based on the design 3D model of the bogie workpiece and the process scaling requirements, key dimensions are selected and adjusted to construct a virtual intermediate model. Feature points are collected from the key feature surfaces of the virtual intermediate model to obtain reference values ​​for each feature point. A 3D scan of the actual bogie workpiece during the intermediate welding stage is performed to acquire point cloud data. Feature points are collected and processed from the corresponding key feature surfaces of the point cloud data to obtain the actual values ​​of each feature point. By comparing the reference values ​​and actual values ​​of each feature point, the deviation of each feature point is obtained. For the key dimensions of the bogie workpiece, a scribing weight mechanism is introduced to assign weight priorities to each key dimension. Based on the deviation of each feature point and the weight priorities, the position of the baseline of the key feature surface is adjusted. This invention achieves a closed-loop process from model adaptation and data comparison to baseline adjustment.

The application relates to a driving behavior evaluation method, a computer program product, equipment and a storage medium, comprising: obtaining time-labeled driving data of a target vehicle; dividing the driving data into multiple segments according to a preset time period, and respectively counting road condition characteristic data and driving style characteristic data of each segment according to the driving data; respectively determining a corresponding road condition, a frequency weight of the road condition and an evaluation weight of the road condition of each segment according to the road condition characteristic data; respectively determining a corresponding driving style of each segment according to the driving style characteristic data; and obtaining a driving behavior evaluation result of the target vehicle based on a preset basic score corresponding to each driving style, in combination with the corresponding road condition of each segment, the evaluation weight and the frequency weight of each road condition. The application realizes accurate evaluation of continuous, long-time and complex driving behavior, measures the risk of the driving behavior of a driver, and improves the objectivity and accuracy of driving behavior evaluation.

The invention relates to a method for detecting the infiltration state of a lithium ion battery, which comprises the following steps of: performing in-situ electrochemical impedance spectroscopy test on the lithium ion battery in a liquid injection infiltration process to obtain impedance spectroscopy data changing along with infiltration time; performing fitting processing on the impedance spectrum data by using a preset equivalent circuit model; wherein the equivalent circuit model comprises a transmission line model element used for representing the impedance characteristic of the porous electrode; extracting a capacitance value corresponding to the transmission line model element from the fitting result; determining the infiltration state of the lithium ion battery according to the variation trend of the capacitance value along with the infiltration time; wherein the increasing rate of the capacitance value is positively correlated with the infiltration rate of the electrolyte in the lithium ion battery. The invention also relates to equipment for detecting the infiltration state of the lithium ion battery, a medium and a computer program product.

This invention provides a low-pressure SiC MOSFET lifetime prediction method that integrates wavelet singular entropy and deep learning. By conducting a full-cycle aging test on a sample SiC MOSFET, the voltage drop signal between the drain and source terminals of the SiC MOSFET in the on-state is obtained. Wavelet decomposition is then performed to effectively separate interference signals from valid signals. Furthermore, the feature signal is extracted from the matrix formed by the coefficients after wavelet decomposition, fully reflecting the complexity and cumulative degradation amplitude of the voltage drop signal in the time-frequency domain. This feature signal is then used to train a deep learning model, effectively ensuring the accuracy of the remaining lifetime prediction of the SiC MOSFET under test and providing accurate data support for the stability of the SiC MOSFET system.

The invention relates to the technical field of tunnel engineering, in particular to a cold region operation tunnel lining frost heaving influence test device and method.The device comprises a walk-in test box used for providing a uniform and controllable low-temperature environment, and a model box is arranged in the walk-in test box; a surrounding rock similar material, a tunnel lining model and a ponding simulation mechanism for simulating a ponding structure are arranged in the model box, the tunnel lining model and the ponding simulation mechanism are surrounded by the surrounding rock similar material, stress loading mechanisms are arranged on the top and the side wall of the model box, and a detection mechanism for detecting stress deformation displacement of the tunnel lining model is further included. According to the test device and the test method adopting the test device, the whole model is uniformly and controllably cooled through the step-in test box, a real temperature field where the tunnel in the cold region is located is accurately simulated, and the problems of uneven temperature and frost heaving simulation distortion caused by local refrigeration in the prior art are solved.

The application discloses a workpiece surface profile line concave-convex anomaly detection and quantification method, and belongs to the technical field of precision measurement. The method comprises the following steps: S1, data acquisition; S2, parameter setting; S3, iterative anomaly segment identification; S4, anomaly segment refinement and type judgment; S5, point-level and segment-level quantification of the refined anomaly segment; S6, anomaly quantification result output and visualization; and S7, workpiece surface profile qualification judgment. The workpiece surface profile line concave-convex anomaly detection and quantification method has stronger adaptability to free surfaces and complex structures of non-standard parts, significantly improves detection precision and efficiency, and is significantly superior to traditional threshold methods and template matching methods in terms of precision and noise resistance, is suitable for complex environments in industrial sites, and meets the development needs of intelligent manufacturing for detection technology in terms of multi-scene coverage, high-precision quantification, high-efficiency response and flexible adaptation.

The application provides an AI-based eye health management and lens fitting recommendation method and system, which captures eye state information through a collection device, synchronously acquires optometry data and eye detection data and pre-processes; inputs the data into an AI analysis model, identifies eye features and analyzes eye health conditions, and generates a health assessment report; based on the report, matches correction and protection schemes and screens adaptive contact lenses in combination with eye use requirements; through the linkage of intelligent wearable devices and special function contact lenses, eye data is monitored and health management suggestions are generated, visual expansion effect is realized, and the evaluation results and recommended schemes are continuously iterated and optimized, realizing the individualization and intelligentization of eye health management and lens fitting recommendation.

This invention provides a method and system for collaborative environmental monitoring and pollution source tracing using UAV swarms in complex terrain, relating to the fields of UAV environmental monitoring and pollution source tracing. The method includes: a ground control center planning layered and altitude-based tasks for the target area and sending them to each group containing master and sub-UAVs; the master UAV decomposing and encoding the sub-tasks and transmitting the results back; the ground-based optimization of flight paths being distributed; the sub-UAVs collecting pollution source data, which is then preprocessed by the master UAV and uploaded; ground-based analysis results being fed back; and the master UAV calculating the contribution value C using a source tracing model. en Once the source tracing is complete, the results are uploaded to the server, and the drone returns to base. The system includes a ground control center and at least one drone swarm; each swarm consists of a master drone and sub-drones. This invention can plan flight paths based on the geographical environment of the monitored target area, avoiding detection blind spots and conflicts, and coordinate actions based on the flight path, thus improving the convenience and accuracy of environmental monitoring and pollution source tracing.

This invention relates to the field of sealing performance testing technology, specifically to a heat-sealing sealing performance testing device for aseptic paper-plastic-aluminum packaging materials. The device includes a testing machine base equipped with a heat-sealing unit, a feeding unit, and a high-voltage discharge testing unit. The high-voltage discharge testing unit is integrated at the bottom of the upper heat-sealing component and located around the heat-sealing electrodes of the heat-sealing unit. This unit is used to perform sealing performance testing on the heat-sealed edge after heat sealing. The high-voltage discharge testing unit includes multiple independent partitioned electrodes arranged along the extension direction of the heat-sealed edge, used to locate the defect on the sealing edge when a discharge signal is detected. This invention integrates the high-voltage discharge testing unit around the heat-sealing electrodes at the bottom of the upper heat-sealing component, allowing for in-situ sealing performance testing without transferring the packaging material after heat sealing. This completely solves the problems of cumbersome procedures and missed or false detections caused by secondary positioning deviations in traditional split-type equipment, significantly improving testing efficiency and accuracy.

The application discloses a kind of water body nitrogen pollution isotope and biological tracer combined tracing method and system, the method includes the type and position of irrigation and drainage ditch of irrigation area to be researched to determine different pollution source area;Surface water sample and groundwater sample are collected in irrigation and drainage ditch, the sample is analyzed, the fluorescence peak intensity, nitrate nitrogen isotope abundance, nitrate oxygen isotope abundance and coprostanol concentration are determined;Based on sample analysis result, the contribution ratio of point source pollution source and non-point source pollution source of surface water and its load are determined;The contribution of groundwater non-point source pollution source and its load are determined.The present application comprehensively collects surface water and groundwater, and uses multi-technology nesting method to analyze the pollution source contribution and load of surface water and groundwater.By distinguishing point source and non-point source, and using nitrogen and oxygen double isotope technology to identify non-point source pollution, combined with biological marker coprostanol to distinguish livestock manure and domestic sewage, the specific contribution and load of each pollution source are effectively quantified.

The application relates to the technical field of foundation engineering construction, and discloses a device for detecting the thickness of deposited sediment in foundation engineering construction, which comprises a deposited sediment thickness detector installed on a foundation. The device is characterized in that the rolling assembly, the steel wire rope, the rotating disc and the turnover frame are cooperatively operated, the detection of different positions in a pile hole can be completed without repeated disassembly, and the detection efficiency is greatly improved; the positioning plate increases the contact area, the extrusion arm firmly clamps the side wall of the pile hole, stable support is provided for the probe puncture, the detection data is ensured to be accurate and reliable; the output end for adjusting the probe position acts on the steel wire rope, damage caused by the probe being stuck is avoided, and the service life of the device is effectively prolonged; meanwhile, the turnover frame, the rotating disc and other structures are matched, the flexible movement and multi-angle detection of the probe in the pile hole are realized, the detection range is significantly expanded, and more comprehensive and accurate data support is provided for the quality evaluation of foundation engineering construction.

The invention discloses a workshop-oriented traffic vibration load influence rapid evaluation method, which comprises the following steps of: arranging an instantaneous synchronous measurement array comprising a plurality of measurement points on one side, adjacent to a traffic road, of a workshop area along the direction vertical to the road; performing 1 / 3 octave analysis on the vibration data of each measuring point to obtain a vibration speed effective value of each measuring point under each 1 / 3 octave center frequency; for each 1 / 3 octave center frequency, performing power function fitting on the vibration velocity effective value of each measuring point under the frequency and the distance from the measuring point to the road, and establishing a frequency-space attenuation model; and determining a vibration velocity frequency spectrum of the target position caused by traffic vibration by using a frequency-space attenuation model, and calculating a traffic vibration dominance index TVDI of the target process equipment in combination with vibration sensitive characteristics of the target process equipment so as to quantitatively evaluate the influence degree of the traffic vibration on the target process equipment. According to the invention, traffic vibration influence evaluation is realized through one-time short-time synchronous measurement.

The invention discloses a tobacco shred width online sampling detection device and a detection method, and aims to solve the problems of low detection efficiency, insufficient real-time performance, high tobacco shred clustering lap joint rate, transparent pressing plate pollution and the like in the prior art. According to the technical scheme, the tobacco shred width online sampling detection device is arranged on a tobacco shred conveying line, the core of the tobacco shred width online sampling detection device comprises a material receiving and conveying mechanism, a material scattering device of a vibration scattering device, a tobacco shred flattening and conveying mechanism and a visual detection mechanism; the vibration shaking device is used for loosening and raking the clustered and lapped tobacco shreds, so that the lapping rate and the agglomeration rate are reduced, full preparation is made for flattening the tobacco shreds, and the single tobacco shred rate is increased. According to the detection method, detection is completed through differential conveying and primary spreading, four-layer progressive vibration material scattering, conveying, clamping and flattening and visual acquisition of high-flattening-rate tobacco shred images. According to the scheme, the uniformity of tobacco shred bulk materials is greatly improved, the clustering lap joint rate is reduced, pressing plate pollution is avoided, real-time online detection is achieved, the detection efficiency and continuity are improved, the detection efficiency is improved, and guarantee is provided for stable cigarette quality.

This invention discloses a weakly supervised open-pit mining site identification method based on adaptive SAM and automatic knowledge learning. The method includes: S1, collecting images of the study area and extracting three-band images using an input spectral adapter; extracting depth features using the feature extractor of the MobileSAM model; constructing a multi-scale perception and geometric adaptation module and obtaining image features by applying N² dilated convolutional units with different dilation rates to the depth features; S2, a scene classifier using predefined prototype features to guide image features in scene classification; then, a cue generator using class activation mapping to obtain a heatmap for scene classification and selecting a set of high-confidence cue points; and a pseudo-label generator constructing triplet contrast constraints; S3, the mask decoder of the MobileSAM model combining cue information and image features to perform cue decoding and obtain the open-pit mining site identification result. This invention combines a set of high-confidence cue points with image features for cue decoding to obtain efficient and high-precision open-pit mining site identification results.

The invention relates to the technical field of image processing, and discloses a landslide surface crack three-dimensional evolution unmanned aerial vehicle image extraction and quantification method and system, and the method comprises the steps: carrying out the bundle adjustment of an ultrahigh overlapping degree aerial image of a landslide surface, and obtaining an image shooting position, an image attitude parameter and a sparse three-dimensional point cloud; constructing a high-precision digital earth surface model; performing digital mosaic on the aerial image with the ultrahigh overlapping degree to obtain an orthoimage; performing semantic segmentation on the orthoimage to obtain a crack binary segmentation map of the orthoimage so as to identify a main crack and a secondary crack; performing three-dimensional geometric parameter analysis on the main crack and the secondary crack to obtain a crack three-dimensional space attribute parameter; carrying out evolution trajectory tracking on the crack three-dimensional space attribute parameters to obtain evolution data so as to construct a visual map of the landslide surface; according to the invention, the efficiency of extracting and quantifying the three-dimensional evolution unmanned aerial vehicle image of the landslide surface crack can be improved.

The invention discloses a visual monitoring and shooting and intelligent identification external damage early warning method and system, and relates to the field of power transmission line safety monitoring. The method comprises the following steps: acquiring external damage accident information; reversely tracing from the power grid topology database based on the accident occurrence position to determine an affected user list; constructing a causal inference model, and carrying out anti-factual estimation on the power consumption of the affected user when no external damage is assumed to occur in the accident influence time period based on the power consumption characteristic data of the affected user in the historical accident-free time period; acquiring actual electricity consumption of a user; determining an electric quantity loss causal effect value according to a difference value between the actual electricity consumption and the anti-factual electricity consumption; and according to the effect value and user electricity price information obtained from the marketing system, generating an external damage follow-up loss list containing the electricity loss cost. According to the method, accurate accounting of the electric quantity loss is realized through a causal inference technology, and a full-link closed-loop system from pre-event early warning to post-event follow-up is constructed in combination with power grid topology analysis and multi-system data fusion.

This invention relates to the field of machining and intelligent control technology, and discloses a multi-process collaborative control system for machining equipment based on multi-source data. The system includes a spatial modeling module, a multi-source sensing and feature mapping subsystem, a reference calibration module, and a collaborative execution module. The spatial modeling module constructs a hierarchical partitioned spatial mesh model enveloping the workpiece and drives dynamic node growth. The multi-source sensing and feature mapping subsystem synchronously acquires operating status data, converts it into spatial attribute values, and stores them in voxel units. After the workpiece is transferred to a new process, the reference calibration module constructs a cross-process coordinate transformation matrix and performs pose transformation on the spatial attribute values ​​stored in the model. The collaborative execution module generates machining compensation increments based on the transformed spatial attribute values ​​and injects them into the CNC system. This invention solves the problem of physical feature discontinuity in multi-process flow, realizing spatial mapping and adaptive compensation from previous physical states to the current process.