158results about How to "Achieve precision" patented technology

The invention relates to the technical field of visual health management, in particular to a ciliary muscle adjustment training system and method based on eye movement tracking, and the method comprises the steps: collecting eye movement data of a fixation point track, an adjustment amplitude change rate and pupil response time in real time, and combining personalized parameters such as the age of a user, diopter and a training target; inputting a ciliary muscle training dynamic planning algorithm module, dynamically generating a stage scheme containing a training action type, a single-group duration, a stimulation interval and a focal length adjustment strategy, and adaptively adjusting the strategy according to real-time adjustment stability and a historical ability curve; through multi-dimensional matching analysis of a pre-stored standard eye movement template, a training specification score is calculated from the track goodness of fit, speed uniformity, amplitude standard-reaching rate and binocular coordination, visual fatigue parameters are obtained based on continuous training duration, pupil fluctuation and retina reflex change, a scoring result is dynamically corrected, and a visual fatigue evaluation result is obtained. Personalized, self-adaptive and quantitative safety control of the training process is realized.

The invention provides a firmware online upgrading method, embedded equipment, a medium and a product, and relates to the technical field of intelligent terminals. The method comprises the following steps: after the embedded equipment is powered on, running a primary bootstrap program, and checking a first mark state: if the state is a state of updating a secondary bootstrap program, executing online updating of the program and resetting a system; and if the state is the default state, loading and running the secondary bootstrap program. Checking a second mark state; if the second mark state is an updating mirror image state, executing firmware mirror image online updating and resetting; and if the state is the default state, determining a target mirror image, copying the target mirror image from the nonvolatile memory to the random access memory, and skipping to run. And the equipment simultaneously monitors the running state of the target mirror image in real time, and executes successful confirmation or abnormal recovery operation according to the state. In this way, quick response of faults is achieved through running state feedback, the stability and reliability of firmware upgrading of the embedded device are effectively improved, and the risk of device paralysis in the upgrading process is reduced.

The invention discloses a depth map super-resolution method based on blind degradation. The method comprises the following steps: forming an initial RGB-D sample pair by using a high-resolution RGB image and a corresponding high-resolution synthetic depth map; screening out a high-quality RGB-D sample pair from the initial RGB-D sample pair; inputting the high-quality RGB-D sample pair into a learnable degradation network, converting the high-quality RGB-D sample pair into a low-resolution training sample, and constructing an RGB-D training data set by using the low-resolution training sample and the high-resolution RGB image corresponding to the low-resolution training sample; using the RGB-D training data set to train the multi-modal super-resolution reconstruction network to obtain a depth map super-resolution model; inputting the low-resolution depth map and the corresponding high-resolution RGB image into a depth map super-resolution model to output a high-resolution depth map; the method solves the problems that an existing depth map super-resolution method mostly depends on a fixed degradation hypothesis, a real sensor and complex degradation distribution of compression transmission are ignored, and accordingly generalization ability is insufficient, edges are fuzzy and artifacts are increased in an actual scene.

The utility model discloses a welding H-shaped steel beam positioning and drilling device which comprises a bottom plate, a stopping plate is fixed to one end of the top of the bottom plate, two mounting plates are fixed to the other end of the top of the bottom plate, transverse grooves are formed in the two sides of the top of a fixing plate, and inclined grooves are formed in the two sides of one end of the top of the fixing plate. First rolling wheels are arranged in the transverse grooves in a rolling mode, connecting rods are rotatably connected to the tops of the first rolling wheels, second rolling wheels are rotatably connected to the tops of the two connecting rods, and moving plates are arranged at the ends, close to the stopping plate, of the two mounting plates; clamping plates are fixed to the faces, close to each other, of the two movable plates. According to the H-shaped steel beam drilling device, the effect of clamping and fixing the H-shaped steel beam in the drilling process of the H-shaped steel beam is achieved, through linkage of the mounting frame and the connecting rod, the cost of additionally needing a driving device to fix the H-shaped steel beam is saved, and the energy-saving and environment-friendly effects are achieved.

According to the general chronic disease patient dynamic monitoring and intervention management system, early recognition, early intervention and continuous management of chronic disease risks are achieved through fusion of multi-source physiological signals and behavior events, self-adaptive modeling of individual baselines, segmented judgment of risk evolution trajectories, self-adaptive generation of intervention strategies and closed-loop optimization of execution feedback. The system takes a whole-process closed loop of'monitoring-evaluation-intervention-feedback-optimization 'as a core, emphasizes individualization, time sequence and interpretability, and avoids dependence of static rules and a single model, so that the management accuracy and timeliness are remarkably improved.

The invention discloses a hydroelectric generating set upper guide shoe temperature intelligent prediction method based on multi-source data fusion, and relates to the technical field of hydroelectric generating set state monitoring and intelligent early warning, and the method comprises the steps: collecting and preprocessing multi-source operation data of a hydroelectric generating set, and constructing a unified time sequence data set; according to a preset working condition zoning rule, the operation working condition type of the current hydroelectric generating set is judged, and a working condition label corresponding to the thermal state of the upper guide shoe is obtained; performing feature importance sorting on the multi-source fusion feature set to obtain an optimal feature subset; on the basis of the optimal feature subset, an upper guide shoe temperature integrated prediction model is established and trained; and predicting an upper guide shoe temperature prediction value, and judging whether a temperature abnormal rise risk exists or not. According to the method, high-precision prediction and real-time abnormal trend identification of the temperature of the guide shoe on the hydroelectric generating set are realized through working condition classification, feature optimization and integrated prediction strategies, and meanwhile, reliable data support and decision basis are provided for intelligent operation and maintenance.

The invention relates to the technical field of data management, and discloses a medical data secure transmission method and a big data digital signature system, and the method comprises a hierarchical processing step, a privacy enhancement step, a key negotiation step, a segmented transmission step and an audit tracking step. The system comprises a signature preprocessing module, a hierarchical signature module, a privacy purification module, a verification module and a tracing module. According to the method, a risk association map is constructed through hierarchical processing, and accurate identification of data association risks is realized; privacy and availability are balanced through differentiated privacy enhancement, authorization controllability is enhanced in combination with block chain key management, large file transmission integrity and non-repudiation are guaranteed, and whole-course audit is controllable. According to the system, the relevance between the signature and the privacy feature is improved through module design, the integrity and relevance of the signature chain are guaranteed, privacy protection and verifiability are compatible, efficient verification is achieved, the dispute traceability is provided, and pediatric medical data safety is guaranteed in cooperation with the method.

This invention discloses a method, system, and medium for data mapping between a solid geometric model and an unstructured mesh, relating to the field of nuclear reactor core coupling programming technology. By converting the CSG geometric entity into a coupling intermediate mesh (unstructured mesh), and using the coupling intermediate mesh as an intermediary between the CSG geometric entity and other professional unstructured meshes, high-precision coupled data transmission and coupled calculation between the CSG geometric entity and other professional unstructured meshes can be achieved through mesh mapping and other methods, based on the geometric correspondence between the CSG geometric entity and the coupling intermediate mesh.

The application relates to the technical field of sewage treatment, in particular to a pressure dosing method and system for sewage treatment. The application first establishes a stable gas pressure environment in a dosing device, and uses a high-precision pressure sensor to collect pressure data in real time; based on Bernoulli equation, a total pressure-dosing flow relationship model and a dosing pipe static pressure-dosing flow relationship model of the dosing device are constructed, and the applicable flow intervals of the two models are determined; after a target flow value is input, the corresponding model is selected according to the interval to calculate the target total pressure or static pressure value; the system adopts a hierarchical PID control strategy, a primary PID is responsible for total pressure adjustment, and a secondary PID is responsible for static pressure fine adjustment, so that the rapidity and accuracy of pressure control are cooperatively ensured; meanwhile, the actual dosing amount is continuously monitored through a flow measurement unit, and when the flow deviation exceeds the set range, a calibration program is automatically started, and the pressure-flow model parameters are optimized in real time; finally, through closed-loop control of pressure and flow, high-precision adjustment of the dosing flow is realized.

The invention discloses a dynamic evaluation and intelligent compensation system and method for contact rigidity of a machine tool joint part. The system comprises a digital twin and multi-source data interface module, a contact interface multi-scale morphology acquisition and characterization module, a joint part contact mechanical state online simulation module, a contact rigidity dynamic calculation model library, a performance evaluation and intelligent compensation decision-making unit and a compensation strategy execution and feedback module. According to the method, dynamic and high-precision contact stiffness analysis is achieved, the problem that a traditional static model is insufficient in precision is solved by deeply fusing microstructure measured data, a macrostructure model and a dynamic working condition load, and the time-varying characteristic of the joint part under the complex working condition can be reflected more truly. A perception-evaluation-compensation active control closed loop is constructed, and the digitization level of machine tool design and operation is improved. According to the method, the contact state of the joint part is actively optimized, so that the dynamic and static performance and machining quality of the machine tool are improved.

The embodiment of the application provides a kind of integrated circuit high temperature aging station test box thermal runaway self-healing control method and device, its method includes: using the health state parameter of the key component obtained by history temperature sequence and a plurality, obtain the degradation prediction sequence information of high temperature aging station test box health index in future period and temperature drift amount prediction value;The actual temperature of high temperature aging station test box is acquired, and by comparing the actual temperature with the set temperature set by user, real-time error is obtained;By inputting the real-time error and the degradation prediction sequence information into the model predictive control (MPC) controller based on the first-order inertia-hysteresis transfer function, the anti-drift optimization control amount for actively inhibiting the temperature drift amount about to occur is obtained;According to the anti-drift optimization control amount, the integrated circuit high temperature aging station test box thermal runaway is self-healing controlled.

This disclosure provides an ammonia injection method and apparatus based on a denitrification system. The method includes: acquiring current boiler parameters of a coal-fired boiler; collecting nitrogen oxide (NOx) parameters at the denitrification inlet of the denitrification system as a first NOx parameter; collecting NOx parameters at the denitrification outlet of the denitrification system as a second NOx parameter; collecting NOx parameters at the total exhaust outlet of the denitrification system as a third NOx parameter; preprocessing the current boiler parameters, the first NOx parameter, the second NOx parameter, and the third NOx parameter respectively; determining the current required ammonia quantity for the denitrification system based on at least one of the preprocessed current boiler parameters, the first NOx parameter, the second NOx parameter, and the third NOx parameter; and injecting ammonia into the denitrification system according to the current required ammonia quantity. This method ensures that the calculated ammonia injection quantity is significantly more accurate.

The application discloses a river cross section shape identification method coupling artificial intelligence and river bed geomorphology, and comprises the following steps: unmanned aerial vehicle complete river channel topography measurement; river cross section type knowledge graph construction; cross section shape characteristic parameter construction; double-encoder framework construction based on artificial intelligence; most similar cross section searching; satellite remote sensing river width and elevation acquisition and water surface elevation correction; unknown cross section geometric shape adjustment. The application couples artificial intelligence and river bed geomorphology, solves the problem that a purely data-driven artificial intelligence model lacks understanding of physical causality, and deduces unreasonable black box results in a physically unreasonable way when the result is generalized to rivers or extreme hydrological events outside the training set; and realizes river cross section parameter acquisition under non-contact measurement conditions. The application breaks through the problem of accurate measurement of river cross section parameters under severe conditions such as flood disaster water damage, major geological disasters, unreachable boundaries and overseas key rivers.

This invention discloses an intelligent embroidery stitch optimization and energy-saving control method and system, belonging to the field of intelligent manufacturing technology. The method includes the following steps: collecting the power level switching signal, drive current change curve, and image acquisition time record of the embroidery machine; generating an electromagnetic interference distribution map based on the collected data; extracting the interference concentration area from the electromagnetic interference distribution map; establishing an interference scale table; and outputting the interference scale results. This invention achieves temporal isolation and synchronous coordination between power switching and image acquisition through interference scale modeling and dynamic matching of the power quiet zone, eliminating the impact of electromagnetic interference on image acquisition and ensuring stable stitch recognition. Through the linkage update of illumination sampling and the interference control list, adaptive control of power, exposure, and illumination is achieved, effectively reducing energy consumption while improving embroidery accuracy.

This utility model relates to the field of shipbuilding and provides a giant cover plate structure and support assembly for VLEC gas carriers. The cover plate structure includes a cover plate section and a support section. The support assembly includes ground supports that cooperate with the two support sections respectively and support frames that cooperate with the cover plate section. By placing a pair of channel steels on the ground in the construction area and fixing the pair of channel steels with flat steel, the stability and accuracy of the support are ensured. The pair of channel steels clamp the two bottom sides of the support section of the cover plate structure to achieve positioning and limitation, preventing deformation during placement. Two rows of symmetrical support frames support the cover plate section of the cover plate structure, preventing deformation of the pot-shaped cover plate structure during placement, ensuring the precision control of the giant section. The ground supports and support frames can be reused, saving construction costs.

This invention belongs to the technical field of power equipment operation and maintenance, power distribution line construction, and high-altitude operation machinery. A pole-mounted transformer replacement device based on a truck-mounted crane is characterized by comprising a main frame and support system, a translational load-bearing system, a chain drive system, and a vertical lifting and centering system. The main frame and support system includes a main load-bearing frame, stabilizing legs, and lifting lugs. The translational load-bearing system includes a translational load-bearing platform and a linear guide rail slider assembly. The chain drive system mainly consists of a geared motor, a drive gear, a driven gear, a short transmission chain, a drive sprocket shaft, a bearing support seat, a long transmission chain, and a reducer mounting support. The vertical lifting and centering system includes a centering mechanism, a vertical lifting mechanism, and a vertical lifting support plate. The centering mechanism includes a horizontal drive motor, a horizontal push rod mechanism, and a guide bracket. This device can be transported by truck, deployed quickly, and is suitable for operation in confined and electrified environments.

The invention discloses a method and system for detecting the internal quality of a polyethylene pipeline hot-melt welding joint, and belongs to the technical field of pipeline quality detection.The method comprises the following steps that before a tensile test is carried out, ultrasonic quality detection is carried out on a casual inspection joint of a polyethylene pipeline set to be detected; dynamically determining an initial tensile rate based on the material grade and the material attribute parameter of the to-be-tested polyethylene pipeline group, and executing a first tensile test at the initial tensile rate; iteratively and dynamically adjusting the tensile rate of the tensile test of the next casual inspection joint based on the tensile test result of the previous casual inspection joint until the tensile test of each casual inspection joint is completed; dynamically executing fracture quality detection based on the fracture position and the fracture characteristic parameter of each spot check joint to obtain a fracture quality detection result of each first joint; and executing internal quality comprehensive detection based on the ultrasonic quality detection result, the fracture quality detection result and the tensile test result of each first joint.

The present application relates to a kind of low-carbon park integrated energy system multi-agent collaborative carbon responsibility allocation method, steps include: the multi-source data of park is collected, with the minimum integrated energy system total operating cost as goal to carry out multi-energy flow optimization scheduling;With the dynamic correction model of two-way carbon flow considering the carbon flow transfer caused by energy storage charging and discharging process, dynamic carbon flow distribution matrix is constructed;Using load carbon responsibility decoupling allocation model, total load is decoupled into multiple sub-load categories, and different carbon responsibility allocation coefficients are given for each type of sub-load;With each interest party in park as the participant of game, Nash bargaining as collaborative optimization framework, maximum all participant utility gain as objective function, Shapley value as the basis for carbon responsibility allocation, multi-agent collaborative optimization is carried out, and the carbon responsibility allocation scheme of each subject is obtained in combination with user carbon responsibility allocation coefficient.Compared with prior art, the present application ensures the fairness, efficiency and operability of carbon responsibility allocation scheme.

The invention relates to the field of intelligent power grids and intelligent fusion terminals, in particular to a transformer health monitoring system based on an intelligent fusion terminal TTU, and the system comprises a waveform data collection module which is used for collecting the waveform data of a transformer; the environment data acquisition module is used for acquiring operation environment data of the transformer; the denoising and reconstruction module is used for carrying out denoising elimination and waveform reconstruction on the waveform data of the transformer; the feature extraction module is used for performing feature extraction, enhancement and fusion on the preprocessed waveform data and the operation environment data of the transformer to obtain a fusion feature vector; the state analysis module is used for inputting the fusion feature vector into a mixed regression model for health state prediction to obtain a transformer health index prediction value; and the TTU decision module is used for matching the control decision scheme and controlling the working state of the transformer. According to the invention, the accuracy and reliability of transformer health prediction and the reliability of overall operation of a power grid can be improved.

The invention discloses a sheet metal processing intelligent control method and system based on multi-source data feedback, and relates to the technical field of industrial digital control, and the method comprises the steps: obtaining the data of a to-be-processed sheet metal part, and according to the data of the to-be-processed sheet metal part, based on the geometric characteristics and deviation sensitive characteristics of a sheet metal part processing path, calculating the processing path of the sheet metal part; differentiated machining areas are divided, and a partition machining map is generated. According to the method, differentiated classified management and control of the processing areas are realized through the partitioned processing map, a regional basis is provided for subsequent differentiated process parameter configuration, accurate distribution of acquired resources is realized through configuring data acquisition frequency and precision parameters based on the regional deviation sensitivity level, deviation causes are quantified through a data model, and the accuracy of the data model is improved. And the technological parameter adjustment amount is deduced in combination with the equipment constraint range and the parameter sensitivity, so that the scientificity and accuracy of parameter adjustment are realized, the problems of insufficient blindness and adaptability of traditional manual experience adjustment are solved, and the precision consistency of sheet metal processing is improved.

The application relates to the technical field of computers, in particular to a power-off test method and system based on Jenkins and SecureCRT, computer equipment and a medium; the method comprises the following steps: in response to configuring power-off test parameters for a test task through a Jenkins platform, triggering the test task and distributing the test task to a test control host; establishing a connection with a device under test and a programmable power supply according to the power-off test parameters; executing an automatic script through a SecureCRT terminal on the test control host, controlling the programmable power supply to perform power-on and power-off operations on the device under test; in the process, monitoring the running state of the device under test, and based on the monitoring result, verifying the state of the device under test by applying a string matching rule, and generating a power-off test result. In this way, the technical problem that the existing automatic power-off test technology is difficult to synchronize with the internal state of the device is solved, and the automation level, repeatability and fusion degree with a modern research and development system of the test process are improved.

The utility model relates to the technical field of robots, in particular to a wheeled robot control device which comprises a transmission body, a carrier, a rubber ball wheel and a transmission assembly, the carrier is provided with the transmission body, the transmission assembly is used for driving the rubber ball wheel to axially rotate, and the rubber ball wheel is arranged on the side face of the carrier. The transmission assembly is arranged in the carrier. The motor transmits power to the rubber ball wheel, simplification and high efficiency of the robot structure are achieved, the elastic characteristic of the rubber ball wheel is beneficial to impact absorption, damage to the internal structure of the robot is reduced, the service life of equipment is prolonged, the transmission body is finely adjusted through the micrometer, and the service life of the equipment is prolonged. The controllability and accuracy of contact between the ball control part and the football are achieved, and the adjusting process of the ball control strength of the ball control structure is greatly simplified through the application of the spring.

The invention relates to the field of computer-aided diagnosis, discloses a system for judging and recognizing the intestinal tract cleanliness level of an enteroscope patient, and aims to solve the problems that existing intestinal tract cleanliness evaluation is high in subjectivity, low in evaluation efficiency and lack of quantitative standards. The method comprises the following steps: acquiring and preprocessing enteroscopy image sequence data, and extracting multi-scale features; and the intestinal tract cleanliness is identified through a deep learning model, and a quantitative scoring report is generated. The system comprises an image data acquisition module, a preprocessing module, a multi-scale feature extraction module, a cleanliness identification and classification module and a report generation module. According to the technical scheme, evaluation objectivity, accuracy and efficiency can be improved, automation, standardization and high-precision quantification are achieved, and dependence on doctor experience is reduced.

The invention provides a lateral buckling detection device for a steel belt of a flexible connecting piece and a detection method of the lateral buckling detection device, and relates to the technical field of lateral buckling detection of steel belts. The steel belt is wound on the outer wall of the inner cylinder and limited in the annular space between the inner cylinder and the outer cylinder, the first end of the steel belt is fixed to the bottom plate, the second end of the steel belt is fixed to the driving assembly, and the driving assembly enables the steel belt to bend laterally; the monitoring assembly is used for acquiring first image information, second image information, first data information and second data information of the steel belt in real time, and the calculation unit is used for determining the buckling form of the steel belt according to the first image information and the second image information and determining the buckling critical load of the steel belt according to the first data information and the second data information. According to the technical scheme, the lateral buckling behavior of the steel belt can be accurately reproduced, miniaturization and precision of the detection device are achieved, and a visual whole-process dynamic monitoring means is provided for revealing the lateral buckling evolution mechanism of the steel belt in the limited space.

This invention discloses a method and system for acquiring corrosion damage points in metallic materials based on machine vision technology. The method includes: acquiring image sequences of corrosion regions under different spectral bands to generate an original image set containing spectral features and spatial information; performing semantic segmentation of the corrosion regions on the original image set based on deep learning to generate a binary mask image of corrosion damage points; using a 3D reconstruction algorithm to recover depth information of the corrosion regions based on the binary mask image to generate a set of corrosion damage points with quantified attributes; and using a density clustering algorithm to identify the spatial distribution pattern of discrete corrosion points based on the corrosion damage point set to generate an analysis report including corrosion level assessment and distribution heatmap. Using this invention, high-precision acquisition and 3D quantitative analysis of metal corrosion damage points can be achieved, improving the automation level and assessment accuracy of corrosion detection.

The invention relates to the technical field of agricultural intelligent equipment, and discloses an intelligent driving system and method applied to an orchard, and the system comprises a four-wheel independent hub motor drive chassis, a terrain sensing module, a dynamic torque distribution module, a multi-sensor fusion positioning module, a path rapid detection module, a transverse tracking control module, and an emergency obstacle avoidance module. According to the intelligent driving system and method applied to the orchard, a four-wheel independent hub motor driving chassis, a terrain sensing module, a dynamic torque distribution module, a multi-sensor fusion positioning module, a rapid path detection module, a transverse tracking control module and an emergency obstacle avoidance module are fused; all-terrain self-adaptive driving and obstacle avoidance of the unmanned transport vehicle, high-precision and anti-interference positioning in a complex environment and rapid detection and navigation of an inter-ridge road advancing path can be realized, so that mechanical intelligent transportation is realized, the labor intensity can be effectively reduced, and the operation efficiency and safety of an orchard can be improved.

The invention relates to the technical field of chemical water treatment, in particular to a cloud side-end cooperative intelligent control method and platform for a chemical water treatment black light factory, and the method comprises the steps: constructing a digital twin model fusing equipment topology and operation parameters, and simulating and optimizing the optimal operation state of a system in an unattended and multi-unit cooperative scene; the edge sensing terminal is used for collecting water quality, energy consumption and equipment operation parameters of each process unit under dynamic working condition disturbance in real time, and the actual operation state of the system is accurately recognized through feature extraction and data fusion analysis; by comparing actual and optimal operation states, extracting deviation parameters, performing multi-dimensional analysis, identifying an operation instability mode and key influence factors, generating a self-adaptive cloud side-end cooperative control strategy and driving an intelligent execution device to realize closed-loop regulation, the response capability, the operation stability and the energy efficiency level of the system to complex disturbance are improved, and the energy efficiency of the system is improved. And unmanned, intelligent and collaborative optimization operation of the chemical water treatment process is effectively supported.

The application discloses a no-bending moment multi-hoisting point static-to-dynamic hoisting method and system, and belongs to the technical field of large structure hoisting. The method combines static mechanical planning before hoisting with dynamic closed-loop control during hoisting. Firstly, the hoisting points are calculated and adjusted to initial optimal positions according to module parameters. After hoisting, the force of each hoisting point and the module posture are monitored in real time, and the crane action and the hoisting point position are dynamically adjusted through a cooperative control system to realize force balance and posture correction, and finally the module is shifted, turned over and precisely positioned. The system comprises a servo-controlled crane, an adaptive sling with an adjustable hoisting point unit, a real-time monitoring system and a multi-hoisting point cooperative control system. The application actively suppresses the bending moment of the module during the whole hoisting process, and significantly improves the operation safety, precision and automation level.

The invention relates to the technical field of modeling and simulation, in particular to a digital modeling and simulation analysis method and system for petroleum and natural gas engineering, and the method comprises the following steps: obtaining elevation coordinate points, screening jump points, repositioning a path line network to recognize an abnormal section, and executing simulation to generate an analysis result. According to the method, geometric sudden change points are recognized by establishing an elevation change anomaly map, deviation point positions are corrected by combining direction vector analysis, the spatial modeling precision is improved, the running state of a target point is dynamically recognized by extracting pressure and temperature change rates in continuous time periods, the response capability of a model to running state anomaly is enhanced, and the accuracy of spatial modeling is improved. The dynamic selection and boundary loading process of the simulation unit is driven through the judgment result of the interference section area, the space accuracy and boundary adaptability of simulation task configuration are achieved, the simulation process is presented in a unified mode in a node track change mode, and the analysis result is archived. And the visuality, the dynamism and the data integrity of digital modeling of the petroleum and natural gas pipeline are ensured.

The application provides a graphite ore flotation intelligent optimization method and system based on AI visual identification, and relates to the technical field of mineral processing. The method comprises the following steps: acquiring a flotation foam image in real time through an image acquisition module, extracting multi-dimensional features such as foam size distribution, stability, color depth, texture and flow rate after improved bilateral filtering denoising and adaptive histogram equalization enhancement, predicting the graphite grade, recovery rate and foam state category according to the features by an attention-enhanced ResNet50 model, dynamically generating an optimal reagent scheme by combining a safety constraint and a reward function through a reinforcement learning agent based on a deep deterministic policy gradient, and finally automatically adjusting a reagent feeding device by a control execution module to realize closed-loop optimization control. The application can accurately predict the indicators of the foam and dynamically optimize the reagent feeding scheme according to the indicators, and significantly improves the production efficiency.