272results about How to "For precise control" patented technology

The invention provides an unmanned aerial vehicle intelligent charging control method and system based on multi-scene adaptation, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: collecting environment data through multiple types of sensors, carrying out the scene recognition and classification through a deep learning algorithm, and generating a scene feature vector and a parameter data set; a basic strategy is called from a preset charging strategy library according to the scene type, a reinforcement learning algorithm is adopted to optimize a charging strategy, a charging power adjustment curve is generated in combination with the environmental parameters, and a charging control instruction is output; and when the charging process is executed, monitoring battery state parameters in real time, performing safety threshold comparison and protection control, calculating a battery health index to evaluate a performance state, and feeding back an evaluation result to the charging optimization model to realize closed-loop control of the charging process.

The invention relates to the technical field of digital twinning, and discloses an AGV path optimization method and system based on digital twinning, and the method comprises the steps: carrying out the data standardization processing of AGV real-time coordinate data, environment obstacle distribution data and cargo storage position data, and constructing a storage environment state matrix; aGV task time parameters are calculated, and a task evaluation matrix containing task timeliness indexes and task priority coefficients is obtained; performing multi-target parameter calculation on the AGV motion energy consumption coefficient and the task weight coefficient, and establishing an AGV path optimization target function; performing path planning analysis by adopting a path exchange operator, a path insertion operator and a path inversion operator to generate an AGV initial path set; according to the AGV optimal path planning method and system, the flexibility and the optimization effect of path planning are improved, and the convergence speed and the quality of path optimization are remarkably improved.

The invention relates to the technical field of cold-chain logistics information, and discloses a multi-mode AIGC cold-chain logistics information processing method and system, and the method comprises the steps: carrying out the feature extraction and feature enhancement of video data, temperature data and position data in a cold-chain logistics system based on a logistics information AIGC model, and obtaining an enhanced feature matrix; carrying out digital twinborn modeling to obtain a digital twinborn model of the logistics system, and constructing a state parameter space; performing deep reinforcement learning and information delay index calculation to generate a real-time data synchronization scheme; constructing a distribution network graph structure, and performing depth map network coding on the distribution network graph structure to obtain a distribution network representation vector; and performing multi-agent collaborative decision-making on the distribution network representation vector to obtain a cold chain distribution scheduling scheme, and updating the cold chain distribution scheduling scheme to the logistics system digital twinborn model. Therefore, intelligent scheduling and accurate control of the cold-chain logistics system in a complex scene are realized.

The invention relates to a control system for a water-jet loom. A data acquisition module acquires and transmits weft tension, humidity and temperature data in real time. The parameter calculation module calculates the optimal parameters of the water spraying time, the water pressure and the nozzle opening degree through a fuzzy control algorithm according to data changes and transmits the optimal parameters to a water spraying execution mechanism. The tension adjusting module adjusts the nozzle opening degree and the water spraying time according to the comparison result of the weft yarn tension and the preset threshold value. The nozzle optimization module optimizes the nozzle design by means of a computational fluid dynamics approach. The pressure adjusting module monitors pipeline pressure through a pressure sensor, and alarms and adjusts the rotating speed of a water pump and the opening degree of an electromagnetic valve if the pipeline pressure exceeds a threshold value. The state detection module monitors knitting needles and shuttles through the machine vision technology, and water spraying parameters are adjusted when abnormity occurs. The data processing module uploads data to a cloud platform, and big data and machine learning are utilized to optimize a control strategy so as to realize real-time monitoring and accurate control of various parameters of the water-jet loom and guarantee weaving quality and efficiency.

The invention provides a prediction and management method and system suitable for pollen multi-dimensional information, and the method comprises the steps: carrying out the statistics of historical item data of a display region, inputting the data into a plurality of first-stage models in an initial prediction model, carrying out the training, obtaining an intermediate prediction result, carrying out the combination, inputting the combined data into a second-stage model, and carrying out the training, and generating a pollen prediction model; receiving a plurality of allergy factors set by the user side, acquiring real-time data of the display area based on the allergy factors, inputting the real-time data into the pollen forecasting model to obtain pollen concentration data, and inputting the pollen concentration data into the pollen health influence model for calculation to obtain a pollen influence logarithm; when the pollen influence logarithm is greater than a preset influence value, generating an initial diffusion region corresponding to each planting region based on an allergen display strategy and the planting region of each allergy factor in the display region; and receiving area data of the display area, adjusting the initial diffusion area to determine an allergen area, generating early warning information based on the real-time position information of the user side and the allergen area, and sending the early warning information to the user side.

The invention discloses an intelligent numerical control machining method and system for mold manufacturing, and the method comprises the steps: obtaining a to-be-cut pattern of a mold, planning a milling cutter feeding route, dividing the to-be-cut pattern into a plurality of milling cutter feeding sub-routes, determining milling cutter control tracks composed of spline curves, carrying out the clustering of the milling cutter control tracks, and obtaining a plurality of track sets; and in the milling process, a real-time machining track is collected, a curvature deviation value is calculated, if the curvature deviation value exceeds a preset value, a milling cutter control track is corrected, the milling cutter priority is ranked according to the size of the working radius, and proper track sets are screened out in sequence for milling till all the track sets are machined. Through intelligent path planning and real-time deviation correction, the use efficiency and machining precision of the milling cutter are remarkably improved, and high quality and high stability of mold manufacturing are ensured.

The invention provides an irradiation prediction method for irradiated goods, and the method comprises the steps: optimizing irradiation parameters according to an irradiation uniformity evaluation result, including adjusting irradiation time, irradiation intensity and an irradiation mode, and obtaining an optimal irradiation parameter combination through an iterative optimization method; according to the optimized irradiation parameters, an irradiation scheme including irradiation time, irradiation intensity and an irradiation mode is made, the irradiation scheme is input into an irradiation equipment control system, and the irradiation process is automatically executed; and carrying out sampling detection on the goods after actual irradiation, measuring irradiation doses at different positions in the goods, evaluating an actual irradiation effect, verifying the accuracy of a simulation model and optimization parameters, and correcting the simulation model and an optimization algorithm according to a verification result.

The invention relates to the technical field of spiral flatcar machine control, and discloses an automatic operation control method and system for a spiral flatcar machine. The method comprises the following steps: according to a spiral motion characteristic parameter set and a working condition prediction matrix, carrying out n equal division processing on a transmission area of the spiral flatcar machine according to a spiral direction to obtain n self-adaptive data acquisition control units and a multi-dimensional state monitoring matrix; performing feature extraction processing on the multi-dimensional state monitoring matrix to obtain a working condition evaluation vector and a dynamic deviation feature set; performing iterative optimization processing on the working condition evaluation vector and the dynamic deviation feature set to obtain a real-time feedback control instruction set and a dynamic compensation parameter matrix; and according to the real-time feedback control instruction set and the dynamic compensation parameter matrix, intelligent closed-loop control is carried out on the spiral flatcar machine, and real-time control data and a process feature mapping set are obtained. According to the invention, high-precision automatic control of the spiral flatcar machine in the continuous loading operation process is realized, and the material loading uniformity and the operation efficiency are ensured.

The invention provides a constant-pressure water supply control method and system for a secondary-supply standardized pump room and a medium. The method comprises the steps that multiple historical water supply data including water supply time data, corresponding water pump water supply pressure data and user node water supply pressure data in a preset time period are obtained and processed, a water supply pressure grade and corresponding water supply pressure and water supply time are obtained, and processing is carried out in combination with the user node water supply pressure; the method comprises the steps of obtaining a pipeline pressure loss value corresponding to a water supply pressure grade, obtaining and processing real-time water supply time point data, obtaining and processing the water supply pressure grade, the corresponding water supply pressure and the pipeline pressure loss value, obtaining and processing real-time required water supply pressure of a water pump, then supplying water and obtaining and processing real-time water supply pressure data of a user node. Obtaining a real-time water supply evaluation index, finally carrying out threshold comparison, and controlling the adjustment of a water supply mode according to a comparison result. Therefore, constant-pressure water supply and accurate control of secondary water supply are achieved, and meanwhile energy consumption is reduced.

The invention relates to the technical field of mechanical arms, and discloses a self-adaptive rapid assembly system and method for a laser radar, and the system comprises an acquisition module, a mechanical arm is provided with a clamping claw and a welding head; the control module is electrically connected with the acquisition module and the mechanical arm, and the control module comprises an acquisition unit which controls the mechanical arm to place a shell on a working plane and controls the mechanical arm to press a crimping stud into a crimping hole site; the judgment unit collects the image of the crimped shell to judge whether the plane is flush or not; when it is judged that the plane is flush, the processing unit controls the mechanical arm to clamp the mainboard module, and the crimping stud penetrates through a mounting hole position of the mainboard module; determining the amount of soldering tin, and controlling the welding head to fix the mainboard module; the adjusting unit collects image data of the welding position to judge whether welding defects exist or not, and when the defects exist, the welding head is controlled to conduct repair welding. Through the acquisition module, the mechanical arm and the control module, automation of laser radar assembly is realized, and the assembly precision is improved.

The invention provides a coal mine cable automatic take-up and pay-off vehicle which comprises a vehicle frame, a winding assembly and a walking assembly, and the walking assembly is arranged at the bottom of the vehicle frame. The winding assembly comprises a first winding drum, a second winding drum and a driver, the first winding drum and the second winding drum are both rotationally connected with the frame, the first winding drum is used for winding and unwinding a cable from the frame to the power source, the second winding drum is used for winding and unwinding a cable from the frame to the excavation equipment, and the driver is used for driving the first winding drum and the second winding drum to rotate so as to achieve winding and unwinding of the cable. According to the automatic winding and unwinding vehicle for the coal mine cable, partitioned management and accurate control of the cable are achieved, the cable winding and unwinding efficiency is remarkably improved, and the integrity and safety of the cable are effectively guaranteed.

The invention relates to the technical field of humidifier control, and particularly discloses an atomization amount control method and system based on real-time space humidity, and the method comprises the steps that real-time atomization amount information of an ultrasonic nebulizer is obtained, and the real-time atomization amount information comprises an airflow speed value and an atomization speed value; real-time range information of the space where the ultrasonic nebulizer is located is obtained, a plurality of diffusion areas are obtained according to the real-time range information, and a corresponding airflow space area speed threshold interval is obtained according to the airflow speed value and each diffusion area; an atomization attenuation threshold interval is obtained according to the speed threshold interval and the atomization speed value of each airflow space area; according to the method, the corresponding atomization adjustment information is generated by judging whether the atomization amount evaluation value is larger than the preset atomization range interval or not, dynamic adjustment of the atomization amount is achieved, and uniformity and accuracy of the atomization effect are ensured.

The invention relates to the technical field of energy conservation and environmental protection, and discloses a biomass oxygen-enriched combustion optimization and pollutant intelligent control system and method.The biomass oxygen-enriched combustion optimization and pollutant intelligent control system comprises a boiler temperature and pressure prediction system, a fuel prediction regulation and control system, a primary and secondary air prediction regulation and control system, a flue gas amount prediction system, a flue gas recirculation regulation and control system and a desulfurization and denitrification intelligent control system; the fuel prediction regulation and control system comprises a fuel identification module, a fuel heat value prediction module and a fuel demand prediction module; the primary and secondary air predictive regulation and control system comprises a primary air calculation module and a secondary air calculation module; the flue gas quantity prediction system comprises an induced draft fan control module and a flue gas prediction module; the flue gas recirculation regulation and control system comprises a recirculation quantity prediction module and a supplement quantity prediction module; the desulfurization and denitrification intelligent control system comprises a pollutant prediction module, a desulfurization agent prediction module and a denitrification agent prediction module. According to the invention, dynamic optimization and accurate control of the biomass boiler under the oxygen-enriched combustion condition can be realized.

The invention discloses a switched reluctance motor for a chef machine, and particularly relates to the technical field of switched reluctance motors, the switched reluctance motor comprises a protective shell, the protective shell is provided with a regulation and control assembly, the regulation and control assembly comprises a base plate arranged in the protective shell, the top of the base plate is provided with a stator, and the bottom of the stator is rotatably connected with an extension rod; the extension rod is installed on the base plate through a bolt. According to the invention, by continuously changing the current in the stator, the reinforced rotor rod and the connecting shaft can continuously move, so that the reinforced magnetism-increasing sheets can be close to the connecting disc, and then the reinforced magnetism-increasing sheets extend between the two adjacent induction magnetic blocks, so that the magnetic field can be enhanced by the induction magnetic blocks and the reinforced magnetism-increasing sheets, and the voltage is kept unchanged; the waveform width, the peak value and the effective value of the current are changed, so that the output torque is influenced, and the torque of the rotor rod and the connecting shaft is further enhanced.

The invention relates to the technical field of explosion-proof display screens, in particular to a refreshing method and system for an explosion-proof display screen. The method comprises the following steps of collecting state parameters and basic parameters of the explosion-proof display screen, performing state feature extraction and screen feature analysis to obtain a state feature set, self-luminous characteristic data and a pixel unit group set, performing simulation screen reconstruction on pixel groups based on the self-luminous characteristic data, generating a simulation explosion-proof display screen model, and performing simulation display screen reconstruction on the explosion-proof display screen. Performing regional heat accumulation effect simulation on the simulation model to obtain simulated heat accumulation data, calculating a screen heat accumulation safety threshold value, evaluating a block buffer demand based on the heat accumulation threshold value and the simulated data, generating partition buffer demand data, formulating a buffer refreshing plan according to the data, obtaining a time zone buffer strategy, and updating the time zone buffer strategy. And generating refresh time sequence data by using a time zone buffer strategy, and performing segmented refresh control on the pixel group. According to the invention, a safer and more reliable explosion-proof display screen refreshing method is realized.

The invention provides a regional energy storage dynamic regulation and control method and system based on a simulation graph model, and the method comprises the steps: carrying out the calculation of the dynamic regulation and control of the regional energy storage based on the historical data of equipment technical parameters, the historical data and real-time data of loads, the historical data of energy storage system specifications, and the historical data and real-time data of distributed photovoltaic power generation in each region; constructing a simulation graph model according to weather historical data and real-time data; on the basis of a simulation graph model, whether reverse heavy overload occurs in each transformer area or not and whether the transformer area is currently in a distributed photovoltaic power generation peak period or not are monitored in real time, and according to the trigger condition type and the energy storage condition of each transformer area, a particle swarm optimization algorithm is utilized to correspondingly generate an optimal charging strategy of the energy storage equipment; according to the generated optimal charging strategy of the energy storage equipment, energy storage dynamic scheduling is carried out on the energy storage equipment of each transformer area, and through accurate simulation of a simulation graph model and the efficient search capability of a particle swarm optimization algorithm, the regulation and control cost is effectively saved, and the reliability of energy storage regulation and control is improved.

The invention discloses a track-controllable radial horizontal well drilling process, and relates to the field of drilling technologies and oil and gas exploitation. According to the technology, in the horizontal drilling operation process, tools needed for track control mainly comprise a steering tool and an orientation tool, in the horizontal drilling operation process, the two tools are matched and cooperatively work, precise control and adjustment of the well track are achieved, and the drilling task of the radial horizontal well can be efficiently completed. A track-controllable radial horizontal well drilling process mainly comprises the steps of borehole preparation, steering tool sitting hanging and positioning, casing windowing, directional deflecting, horizontal drilling and multi-branch horizontal well drilling, and multi-branch radial horizontal wells with different depths can be achieved through the complete process. Aiming at resources of small marginal oil reservoirs, fault block oil reservoirs, thin oil reservoirs, low-permeability oil reservoirs and the like with different depths, the oil drainage radius is greatly increased, the production capacity of oil and gas wells and the water injection efficiency of water injection wells are improved, and the method is economical, efficient and safe and is an effective means for old well transformation of oil fields, potential tapping of the oil reservoirs and stable production and yield increase.

The invention relates to a panel printing monitoring method and device based on the Internet of Things and a medium, and relates to the technical field of the Internet of Things, and the method comprises the steps: obtaining a panel printing process, recognizing a plurality of production key links according to the panel printing process, and constructing key point data according to the plurality of production key links; a current production environment is obtained, production environment data are constructed according to the production environment, and the production environment data at least comprise temperature data and humidity data; constructing an Internet of Things architecture according to the key point data and the production environment data, wherein the Internet of Things architecture at least comprises a plurality of different types of sensors which are respectively arranged in a plurality of production key links and are suitable for the current production environment; acquiring real-time parameter data uploaded by the sensor module in the panel printing process; analyzing according to the real-time parameter data and the key point data to obtain a monitoring result, and judging whether optimization is needed or not according to the monitoring result; when optimization is needed, an optimization scheme is obtained through analysis according to the real-time parameter data and the key point data, and the panel printing process is optimized through the optimization scheme. The method has the effect of achieving accurate control and optimization in the panel printing process.

An intelligent control method, equipment and medium based on a flue gas desulfurization process belong to the technical field of dry and semi-dry desulfurization, solve the problem of how to improve the working condition adaptability of dry and semi-dry desulfurization processes, and comprise the following steps: a feedforward prediction step: based on historical operation data, predicting the theoretical addition amount of a desulfurizer through a feedforward prediction model; a feedback correction step: dynamically correcting the theoretical addition amount of the desulfurizing agent based on the real-time SO2 concentration deviation, obtaining the final addition amount of the final desulfurizing agent, executing the final addition amount, and performing secondary correction according to the execution result; a model iteration step: continuously optimizing the feedforward prediction model based on incremental data generated in a system operation process; according to the method, the deviation mode is analyzed by verifying the outlet SO2 concentration data in real time, secondary correction is executed, correction strategies are customized for various complex working conditions, the working condition adaptability of dry-method and semi-dry-method desulfurization processes is effectively improved, and accurate prediction and real-time control of the SO2 emission concentration are guaranteed.

The invention relates to the technical field of smart home, and discloses a PID controller control parameter optimization method, a heating system and a control method thereof, and the method comprises the steps: generating a plurality of groups of control parameters based on a parameter optimization model; obtaining a current deviation, and calculating fitness corresponding to each group of control parameters based on the current deviation; and selecting the control parameter with the fitness closest to the target value as a new control parameter of the PID controller. According to the method, the control parameters of the PID controller are automatically generated based on the parameter optimization model, so that the optimal control parameter combination meeting the preset condition is found, the method can be used in a dynamic environment, the control parameters of the PID controller are adjusted in a self-adaptive mode, and then the PID control efficiency is improved.

The invention relates to a rotor wing tilting mechanism for the ends of wings of an electric tilting rotorcraft, and aims to provide an efficient, safe and economical solution suitable for the electric tilting rotorcraft. According to the tilting mechanism, a worm and gear transmission mode is adopted, the stable tilting and self-locking functions of the rotor wing are achieved through the precise meshing design, the structural design is simplified, and an additional tilting locking device is removed. The steering engine, the worm gear, the worm, the motor and the rotor wing are directly installed on the tilting box, the tilting box is installed on the tilting mechanism connecting shaft through a bearing, and the tilting mechanism connecting shaft is connected with the wing. The steering engine directly drives the worm to rotate, the worm drives the worm gear to rotate, and the worm gear drives the tilting box and the rotor wings to tilt together. The rotor wing tilting mechanism has the advantages of being simple and reliable in structure, high in tilting operation efficiency and the like.

The utility model is applicable to the technical field of AGVs (Automatic Guided Vehicles), and provides a heavy-load agv-based synchronous lifting rod which comprises a vehicle body, a pallet fork mechanism and a lifting main body, the lifting main body comprises a supporting table arranged beside the vehicle body; the guide columns are arranged on the two sides of the supporting table; the first transverse plate is arranged above the plurality of guide columns; the lifting holes are formed in the four corners of the first transverse plate; the plurality of lifting columns slide in the plurality of lifting holes; the top plate, the buffer piece and the radar sensor are arranged above the lifting column; lifting of the driving air cylinder is accurately adjusted, it is ensured that the lifting main body can accurately reach a designated position according to a preset path and height requirements, the height of the radar sensor can also be correspondingly adjusted, and therefore induction dead angles are avoided, safe operation of a vehicle body is ensured, and the service life of the vehicle body is prolonged. Due to the intelligent and accurate control design, the operation efficiency and reliability of the vehicle body are greatly improved, and safe operation of the vehicle body is ensured.

The invention belongs to the field of spinal cord tumor postoperative nursing, particularly relates to a spinal cord tumor postoperative turning-over assisting positioning device, and provides the following scheme aiming at the problems that a patient is difficult to turn over, the body position is difficult to stabilize and the operation risk is high: the spinal cord tumor postoperative turning-over assisting positioning device comprises a base, a supporting plate, a bed plate and a turning-over mechanism, and the bed plate is provided with a through hole matched with the turning-over mechanism; a clamping groove and buckle assembly ensures turning stability, linkage control over the protective guard and the turning plate is achieved, the protective guard and the turning plate are prevented from turning off a bed, a steel wire rope is automatically recycled to keep tidy, the height of the protective guard is flexibly adjusted through an adjusting mechanism, and the device adapts to different patients. The labor intensity of medical staff is relieved, and the applicability and flexibility of the device are improved.

The invention discloses a method for realizing precise green restoration of environmental heavy metal pollutants by coupling a heavy metal sensing module and an aerobic sulfate reduction module. The method comprises the following steps: constructing an aerobic sulfate reduction pathway by heterologous reconstruction of cysteine feedback inhibition-resistant serine acetyltransferase and cysteine desulfylase, putting the aerobic sulfate reduction pathway under the control of a sensing module composed of heavy metal sensing protein genes, so as to construct a'sensing integration 'module, and transferring the'sensing integration' module into environmental microorganisms. The heavy metal in-situ remediation engineering strain is formed. When a specific heavy metal sensing module in the engineering strain recognizes heavy metal pollution, expression of an aerobic sulfate reduction module can be effectively started, so that heavy metal ions are converted into stable metal sulfide, and in-situ green low-carbon remediation of environmental heavy metal pollutants is realized. The genetic method disclosed by the invention is simple and efficient, saves the cost, can realize accurate perception and accurate control of environmental heavy metal pollution, and has important environmental protection application value.

The present invention relates to the field of information processing technology, and discloses a power regulation method and system for parallel modules of flexible equipment. The method and system analyze and process the real-time power data of each parallel module in the flexible equipment to obtain the power regulation target value and power curve of each parallel module. The power state of the parallel module to which it belongs is evaluated based on the power curve to determine the first parallel module, and the first parallel module is controlled to generate a power regulation instruction to send to the second parallel module adjacent to it, so that each second parallel module performs power regulation according to the power regulation instruction and in combination with its own corresponding power regulation target value to obtain a power regulation amount. A power regulation strategy based on predictive control is introduced according to the historical power data of each parallel module to predict the future power change trend of each parallel module, and the power regulation amount is corrected in advance to suppress oscillation in the power climbing process, so as to realize accurate power dynamic regulation of each parallel module in the flexible equipment.

The utility model relates to the technical field of microbial agent production, and discloses a bacterium adding device for microbial agent production, which comprises a bacterium adding box, side baffles are arranged on two sides of the bacterium adding box, a material guide inclined plate is arranged in the bacterium adding box, a stepped feeding assembly is arranged at the edge of the material guide inclined plate, the stepped feeding assembly comprises a pushing air cylinder, and the pushing air cylinder is connected with the side baffles. The output end of the pushing air cylinder is connected with a pushing bottom plate, a first-stage pushing plate, a second-stage pushing plate and a third-stage pushing plate are arranged on the pushing bottom plate, a first-stage fixed material guiding plate is arranged on the adjacent side of the first-stage pushing plate, a second-stage fixed material guiding plate is arranged on the adjacent side of the second-stage pushing plate, and a third-stage fixed material guiding plate is arranged on the adjacent side of the third-stage pushing plate. And a third-stage fixed guide plate is arranged on the adjacent side of the third-stage push plate. The device has the advantages of simple structure, convenience in operation, easiness in maintenance and the like. And a supporting prism is arranged at the bottom of the pushing air cylinder, the stability of the equipment can be enhanced, the equipment can be conveniently installed and debugged, and wide application prospects and important practical value are achieved.

The invention discloses a vehicle-mounted charger shell friction welding device and a welding method thereof, and relates to the technical field of resistance substrate detection.The vehicle-mounted charger shell friction welding device comprises a base, Y-axis displacement mechanisms are fixedly installed on the two sides of the upper end face of the base, and an X-axis displacement mechanism is installed between the two Y-axis displacement mechanisms; an X-axis displacement mechanism is installed on the upper portion of the base, a vertical displacement mechanism is installed below the X-axis displacement mechanism, a friction welding mechanism is arranged at the bottom of the vertical displacement mechanism, a shell clamping mechanism is arranged in the middle of the upper end of the base and comprises guide grooves, clamping plates are installed above the guide grooves correspondingly, and the clamping plates are arranged on the upper portions of the guide grooves correspondingly. And a transmission rod is installed in the guide groove, a threaded transmission pipe is installed outside the transmission rod, a sliding block is installed outside the threaded transmission pipe, and the problems that in a traditional welding mode, the welding speed cannot be increased on the premise that the flatness of the welding position is ensured, and the flexibility of a positioning mechanism is poor are solved.

The invention discloses an underground engineering intelligent grouting method based on an improved discrete fracture network model. The underground engineering intelligent grouting method is characterized by comprising the following steps: 1) early-stage preparation and rock mass fracture data collection; 2) on the basis of a matrix joint model algorithm, constructing a discrete fracture network model through rock mass fracture data; 3) intelligent optimization of grouting parameters is carried out based on a multi-target particle swarm optimization algorithm; (4) grouting operation is carried out; and 5) effect evaluation and long-term monitoring. According to the underground engineering intelligent grouting method and system based on the improved discrete fracture network model, accurate control and long-term monitoring of the grouting process are achieved by combining the advanced modeling technology, the artificial intelligence algorithm and the Internet of Things technology. According to the method, the grouting effect is improved, resource consumption and environmental influence are remarkably reduced, and an innovative solution is provided for rock mass reinforcement and anti-seepage treatment of important projects such as water conservancy and hydropower, tunnels and the like.

The invention relates to the technical field of biological materials, in particular to an intrauterine degradable shape memory isolating membrane and a preparation method thereof. The raw materials of the isolating membrane at least comprise a compound of an artificial high-molecular compound and a natural high-molecular compound. The mass ratio of the artificial high-molecular compound to the natural high-molecular compound is (5-95): (95-5); the isolating membrane is used for loading the medicine and continuously releasing the medicine into the uterine cavity. The isolating membrane is folded and conveyed to a womb wound part after an operation, the purpose of automatically unfolding the isolating membrane to reach the womb wound part is achieved, and intrauterine adhesion is physically blocked. In addition, the isolating membrane can load bioactive medicines according to requirements, so that the functions of relieving pain or stimulating and continuously activating an endometrial basal layer are realized, the occurrence of uterine scars is inhibited, and the normal uterine fertility function of a patient can be recovered more quickly.

The invention specifically discloses a fuel cell oxygen supply system control method based on a BP neural network and active-disturbance-rejection control, and the method comprises the steps: constructing an oxygen supply system model, constructing an active-disturbance-rejection control model, and connecting the active-disturbance-rejection control model with the oxygen supply system model. Controlling the rotating speed of an air compressor and the opening degree of a back pressure valve in the oxygen supply system model through the active disturbance rejection control model so as to adjust the flow and the pressure of air entering the fuel cell stack; a BP neural network is constructed, the BP neural network is connected with the active-disturbance-rejection control model and the oxygen supply system model, parameters in the active-disturbance-rejection control model are optimized through the BP neural network, and the parameters comprise an estimated value and the bandwidth of the linear expansion observer. The air flow and pressure can be accurately controlled, fluctuation of the flow and the pressure in the control process is reduced, the robustness of an oxygen supply system is enhanced, the response time of parts is shortened, overshoot of the parts is smaller, and the anti-interference capacity is higher.