150results about How to "Achieve optimization" patented technology

The application relates to the technical field of semiconductor integrated circuit manufacturing, and particularly discloses an OPC processing method for solving the MRC limitation of metal layer patterns, which comprises the following steps: S1, screening out metal layer line ends with hole layers as to-be-optimized line ends from a metal layer layout; S2, identifying 'L' type line ends from the to-be-optimized line ends, and the patterns opposite to the 'L' type line ends are 'I' type line ends; S3, screening out short side 'L' type line ends from the 'L' type line ends, and the length of the short side of the short side 'L' type line end is less than 0.5 times of a design standard of a hole to a target; and S4, identifying adjacent sides of the short side, and generating line end marks according to the adjacent sides. The OPC processing method for solving the MRC limitation of metal layer patterns can ensure that the 'I' type line ends obtain sufficient compensation by preferentially controlling and setting edge placement errors of the contours to the connected adjacent sides, and solves the problem of contour retreat of the 'I' type line ends.

The invention relates to a port toughness optimization method and system based on a traffic network and power grid coupling model. The method comprises the steps of obtaining system configuration and structure parameters of a traffic network and a power grid of a port; calculating the container throughput of the port in the initial state before an extreme event occurs in the port; after an extreme event occurs in the port, according to the traffic network and power grid coupling model, gradually calculating the operation state of a coupling network formed by the traffic network and the power grid at each moment, and calculating the container throughput of the port in the lowest state; after the port is repaired, a recovery strategy is obtained step by step according to the traffic network and power grid coupling model so as to repair the port, and the container throughput reaching a stable state after the port is recovered is obtained; and according to the container throughput of the port in the initial state, the lowest state and the stable state, calculating a port toughness index so as to carry out port configuration optimization. Compared with the prior art, the method realizes accurate and complete quantitative evaluation and optimization of port toughness.

This utility model relates to the field of foundation pit protection technology and discloses a protective device for water tank foundation pits. It comprises at least one set of two main protective railings, two connecting plates, and secondary protective railings equidistantly arranged between the two connecting plates. Movable seats are fixedly installed at equal intervals on the inner side of each connecting plate. This device achieves overall optimization of the protection system through a multi-layered reinforcement structure. The double-rib design built into the main protective railings forms a parallel reinforcement structure, effectively resisting the horizontal earth pressure on the sidewalls of the foundation pit. Experimental calculations show that under the same load conditions, the deformation of the railing is reduced by more than 40% compared to traditional single-layer structures. The hollow core slab uses a grid structure composed of reinforcing rib seats and reinforcing rib columns to form a three-dimensional support system. The diameter of the reinforcing rib columns is 1 / 3 to 1 / 2 of the height of the reinforcing rib seats, and the surface is provided with annular reinforcing ribs. This parameter configuration increases the compressive strength of the hollow core slab to over 8 MPa.

The embodiment of the invention provides a power grid strategy multi-level consistency evaluation method and device, and the method innovatively proposes a cross-stage strategy element embedding expression and consistency evaluation method, and carries out the element extraction, semantic embedding and cross-stage mapping of strategy, planning, project and plan multi-level texts. A strategic semantic conduction path between a strategic target and a power grid project execution link is established and optimized, so that consistency analysis and optimization in a strategic landing process are realized, the scientificity and intelligence level of strategic landing are improved, and finally a power grid project and strategic consistency evaluation method is constructed. Effects and defects of the project in response strategy aspects are obtained, and thoughts are provided for project optimization.

The application provides a magneto-rheological semi-active suspension active fault-tolerant control method and system, comprising the following steps: constructing a magneto-rheological suspension fault model, obtaining vehicle sensing data, using an unknown input observer to perform state estimation on the magneto-rheological suspension fault model based on the vehicle sensing data, and obtaining a residual error vector; constructing a preset fault feature vector according to the magneto-rheological suspension fault model, then using a projection method to extract features from the residual error signal according to the preset fault feature vector, and obtaining fault features; generating fault model parameters according to the preset fault feature vector and the fault features, then using an IMPC controller to generate an optimal control increment based on the fault model parameters; determining an optimal damping force according to the fault model parameters and the optimal control increment, and using the optimal damping force to control the vehicle suspension system. The application solves the problems of poor real-time performance and low precision in fault diagnosis of the magneto-rheological semi-active suspension in the prior art.

This invention discloses a path planning method for a snake robot based on fuzzy collision constraints and helical trajectory, comprising the following steps: S1, establishing an overall path model using the Archimedes' spiral equation; S2, obtaining the complete motion trajectory of the multi-node system through solving the state of the first node and recursion between nodes; S3, using a fuzzy collision risk function for flexible judgment to avoid path interference between the first segment and subsequent segments; S4, using the pitch as the optimization variable and employing a simulated annealing algorithm to find the optimal path parameters to ensure safe entry into the target area. The trajectory generated by this invention is smooth and continuous, can actively predict collisions, and can quantitatively optimize path parameters, making it particularly suitable for scenarios with high requirements for motion smoothness and safety, such as narrow pipe inspection, complex terrain exploration, space-constrained situations, or the need to maneuver into specific turning spaces.

The application provides a kind of based on search enhancement generation's internet of things security intelligent report generation method and system, it is related to data processing technical field, the method includes: data point is mapped to corresponding feature analysis area, generates collection optimization guidance quantity, the collection optimization guidance quantity includes supplementary collection data, increases collection frequency, prolongs collection time window;According to collection optimization guidance quantity, data collection strategy is adjusted, and optimization query instruction is generated;Optimized multi-source data set is collected from each data source by executing optimization query instruction;Optimized multi-source data set is carried out information fusion and structured organization, and comprehensive context information body is generated;Comprehensive context information body is combined with report structure, and prompt instruction combination is generated;Prompt instruction combination is input into pre-training large language model processing, and internet of things security analysis report is generated.The application effectively improves the efficiency, accuracy and professionalism of report generation.

This invention provides an intelligent identification and quantification method for microscopic residual oil, belonging to the field of microscopic residual oil analysis. The method includes preprocessing visual modal micro-CT images and textual modal geological description text, and inputting them into a multimodal pyramid pooling visual model for deep cross-modal fusion and semantic recognition to generate a high-precision semantic segmentation map of residual oil. The semantic segmentation map is then input into a task scheduler, where dynamic scheduling and collaborative intelligent agents execute seepage simulation and potential prediction to obtain dynamic simulation results. Based on the current residual oil state, a decision-making intelligent agent uses closed-loop optimization to obtain the optimal strategy and its verification simulation results. A structured report is generated based on the semantic segmentation map, dynamic simulation results, optimal strategy, and its verification simulation results. This invention solves the problems of fragmented identification-modeling-simulation-decision-making processes, low automation, and unquantifiable results in microscopic residual oil analysis.

The application discloses a standard cell layout external pin automatic leading-out method based on graph search, which is characterized in that a Hungarian algorithm is used to solve a pin leading-out assignment problem abstracted from a standard cell circuit layout pin leading-out, and then pin leading-out positions of different networks are obtained, so that network routing optimization is realized. The method specifically comprises the following steps of data preparation, data preprocessing, cost matrix calculation, optimal strategy solving, routing result generation and the like. The application solves the problem that it is difficult to lead out network ports in the standard cell layout routing process based on graph search, and improves the pin accessibility and layout quality of the generated standard cell layout.

The invention relates to the technical field of software development, and discloses a method, a device and equipment for arranging and testing laboratory orders, and a storage medium. The method comprises the following steps: according to a current order arrangement strategy generated based on a reinforcement learning model, performing chromosome coding on current laboratory order information, current experimenter information and current experimental equipment information to obtain a corresponding initial population; the fitness of individuals in the initial population is evaluated based on a current fitness function, the initial population is iteratively evolved by selecting and improving crossover and mutation operation of chromosomes, and the current fitness function is obtained based on examination parameters of laboratory orders predicted by a first AI model; and under the condition that a set genetic termination condition is met, an optimal laboratory order scheduling and testing scheme is obtained. Therefore, through the reinforcement learning model and the AI model and in combination with the genetic algorithm, comprehensive optimization of laboratory order arrangement and measurement is realized, and the order arrangement efficiency and the resource utilization rate are improved.

This invention provides a UAV power emergency communication and resource collaborative scheduling system, relating to the field of wireless communication technology. Through system initialization, data acquisition and hierarchical coding, satellite-to-ground link establishment, NOMA access and scheduling modeling, resource collaborative configuration model establishment, joint optimization solution, online collaborative execution, and anomaly response, it achieves dynamic resource scheduling and optimization, offering advantages such as efficient collaborative resource scheduling, improved spectrum utilization, optimized energy use, guaranteed access to key nodes, and enhanced system reliability and response speed.

The invention relates to the technical field of thermal management of electronic equipment, and discloses a precise temperature control method for components on a circuit board, and the method comprises the steps: executing multi-dimensional state synchronous sampling through a vertical conduction structure of a heat conduction through hole and a shielding shell, and obtaining the shell temperature, the environment temperature and the load current; processing current data by using amplitude domain judgment filtering and calculating instantaneous thermal power, substituting the instantaneous thermal power into a discretized thermal resistance-thermal capacity observer model to calculate the virtual junction temperature of a component to be subjected to temperature control in real time, and calculating the total thermal regulation power by adopting a strategy of combining virtual junction temperature feedback and power feedforward for control logic; and a target driving current is directly solved based on a thermodynamic reverse physical model, and a semiconductor chilling plate or a heating film is driven to work. According to the method, physical conduction lag is compensated through estimation of the observer, and the dynamic response speed and the steady-state control precision aiming at the load step are remarkably improved in cooperation with thermal resistance parameter self-adaptive calibration.

The invention discloses a flat panel detector and a method and device for using the flat panel detector. A flat panel detector is constructed on the basis of an amorphous silicon substrate on which a hexagonal pixel pattern is uniformly laid. The hexagonal pixels can be arranged more closely on a two-dimensional plane, and gaps among the pixels are reduced, so that a photosensitive area is maximized with a relatively high filling rate, and the spatial resolution of the detector is improved. And the hexagonal pixels enable a frequency space to generate an angle of 60 degrees, so that the influence of grid artifacts is reduced to a certain extent. Meanwhile, the hexagonal pixel array is effectively processed and optimized by adopting an image reconstruction algorithm, the signal-to-noise ratio of the single pixel of the flat panel detector is improved, and the definition and accuracy of the image are improved.

This application provides a signal communication method for a multi-dimensional domain of a data link, comprising: performing cross-domain correlation deconstruction on the data link's spatiotemporal-frequency multi-dimensional signal and error feature data under an electromagnetic environment to obtain the original spatiotemporal-frequency domain feature set; simultaneously integrating signal propagation characteristic data and error source attribute data to generate a multi-source correlation data cluster to generate a spatiotemporal-frequency multi-dimensional fused feature topology; constructing a multi-dimensional domain collaborative error-resistant model based on the spatiotemporal-frequency multi-dimensional fused feature topology; and performing dynamic weight allocation and error suppression strategy iterative optimization on the spatiotemporal-frequency domain error-resistant weight parameters and error suppression strategy parameters in conjunction with spatiotemporal-frequency domain resource adaptation rules to generate a multi-dimensional domain error-resistant control command; performing spatiotemporal-frequency collaborative optimization processing on the data link transmission signal according to the multi-dimensional domain error-resistant control command to obtain an error-resistant optimized signal; simultaneously collecting transmission quality data of the link feedback signal; and fine-tuning the multi-dimensional domain error-resistant control command parameters in reverse by the deviation between the transmission quality data and a preset quality threshold.

The invention discloses a cavitation shot peening surface strengthening method and system based on cooperation of high hydrostatic pressure and spherical focused ultrasound. The method comprises the following steps: establishing and maintaining a hydrostatic pressure environment higher than 0.1 MPa in a high-pressure processing cavity filled with a degassing liquid medium; the to-be-machined surface of the workpiece is positioned in a sound field focal region of the spherical focused ultrasound transducer; and in the high hydrostatic pressure environment, a transducer is driven to work so as to generate a cavitation bubble group in a space confinement range in a focal region of the transducer, and meanwhile, the workpiece is controlled to move according to a preset path, so that cavitation collapse impact acts on a target region on the surface of the workpiece. The device comprises a high-pressure processing cavity, a spherical focused ultrasonic transducer, a multi-degree-of-freedom movement mechanism and a control system. Through cooperation of high hydrostatic pressure constraint and the spherical focusing sound field, precise localization and energy strengthening of the cavitation effect are achieved, a plastic deformation layer can be efficiently and controllably introduced to the surface of a metal material, the surface hardness can be remarkably improved, a residual compressive stress layer is formed, surface layer grains are refined, and the method is suitable for precise surface strengthening of complex components.

This invention discloses a predictive current control method and system for a GaN-based permanent magnet synchronous motor. The method includes: predicting the current of each voltage vector among multiple voltage vectors of the inverter based on a predictive current model to obtain multiple predicted currents; filtering the multiple voltage vectors according to the multiple predicted currents and a first cost function to obtain candidate voltage vectors; determining the duration of action of the candidate voltage vectors; if there are multiple candidate voltage vectors, filtering them according to the duration of action of the multiple candidate voltage vectors and a second cost function to obtain the optimal voltage vector; and controlling the inverter according to the optimal voltage vector and its duration to control the operation of the permanent magnet synchronous motor. This improves the overall steady-state performance of the motor while reducing the computational load, thus lowering the complexity of the control method.

The application discloses a switch device soft start gain control method, system, device, medium and product, characterized in that, comprising: acquiring real-time current data of a low-voltage intelligent switch device in a soft start process; calculating a current error between the real-time current data and preset expected current data, inputting the current error into a proportional-integral-derivative control model to obtain an initial control quantity; inputting the real-time current data and the current error into a reinforcement learning model to select a gain adjustment coefficient from an action space according to a current state corresponding to the real-time current data, calculating a gain compensation quantity based on the gain adjustment coefficient and the current error, generating a target control quantity based on the initial control quantity and the gain compensation quantity, and controlling the soft start process of the low-voltage intelligent switch device based on the target control quantity. The application can adaptively and dynamically adjust the starting current in the soft start process of the low-voltage intelligent switch device, so as to improve the stability and control precision of the soft start process.

This invention provides a method and system for optimizing downhole communication links based on self-organizing networks, relating to the field of communication link technology. The method includes acquiring communication node information, constructing a network topology, and determining network characteristic parameters; constructing a link quality prediction model to evaluate link quality; performing dynamic network partitioning and establishing a node priority ranking table to select the optimal transmission path; and real-time monitoring of link status, triggering node self-organizing reconfiguration when necessary. This invention can improve the connectivity, stability, and transmission efficiency of downhole communication networks, reduce communication latency, and enhance the safety of downhole operations.

The invention relates to the technical field of computers, in particular to a text task cue word updating method based on a text processing task and related equipment. The text task cue word updating method comprises the steps of obtaining a first cue word sampling strategy parameter, a first output conversion mapping matrix and a text sample for a text processing task; sampling in a large model cue word library according to the first cue word sampling strategy parameter to obtain a first text processing task cue word; splicing the text sample and the cue word to obtain a first task query text, and inputting the query text into a target large language model to obtain a first output probability which is the output probability of each candidate lexical element in a large model vocabulary; performing vector space conversion on the first output probability through a first output conversion mapping matrix to obtain a first task processing output result; and updating the first cue word sampling strategy parameter and the first output conversion mapping matrix based on the result and the sample task output label.

The application discloses a skin treatment scheme optimization method, an electronic device and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring an initial skin state parameter of a skin area to be treated; based on the initial skin state parameter and a preset treatment target, a pre-trained energy sequence generation model is used to iteratively generate a personalized treatment scheme comprising multiple treatment steps, which can be adjusted according to the unique skin condition and aging characteristics of each individual, is suitable for precise layered anti-aging treatment, and realizes effective optimization of the treatment scheme.

This application relates to the field of soil remediation technology, and discloses a method, system, and storage medium for real-time monitoring of soil remediation effects. The method includes: collecting multi-depth data samples of soil in the vertical direction to construct a stratified soil characteristic dataset; identifying locations of highly heterogeneous sections based on the dataset; injecting a tracer at these locations and imaging in real time to obtain a sequence of infiltration path images; using a random forest model to predict diffusion velocity and blockage point locations, dynamically adjusting injection parameters to eliminate blockage, and obtaining infiltration path data; tracking and quantifying the effects of the soil amendment on each soil layer through time-series analysis to obtain quantitative indicators of the effect; comparing these indicators with the initial dataset to optimize the stratification model and construct a stratified monitoring framework; integrating multi-depth data samples to validate the framework and generating an evaluation report on the soil remediation effect. This invention achieves accurate characterization of soil vertical stratification characteristics and scientific, quantitative evaluation of remediation effects, improving the efficiency of soil amendment use.

The invention provides a super-large-scale MIMO system beam focusing method based on an adaptive time delay-phase structure, and relates to the technical field of radio communication, comprising the following steps: constructing an adaptive time delay-phase structure suitable for a super-large-scale MIMO system, and establishing a near-field beam focusing joint optimization mathematical model; solving an all-digital optimal beam focusing matrix through maximum ratio transmission; a switch matrix optimization problem is converted into a bipartite graph matching problem, and an optimal matching matrix is solved by using a Hungary algorithm; solving a phase shift matrix through a Riemann spectrum conjugate gradient method; optimizing the time delay matrix by using a gradient descent method; optimizing the digital precoding matrix by using a least square method; and giving a base station beam focusing matrix through alternate iteration, and completing beam focusing of the super-large-scale MIMO system. According to the structure provided by the invention, dynamic sharing with the antenna array elements can be realized by utilizing the switching network, so that the adaptive capacity of hybrid precoding to a channel environment is effectively enhanced.

The application relates to the technical field of collaborative allocation of warehouse resources, and discloses a warehouse resource adaptive collaborative allocation system based on multi-time scale deep reinforcement learning, which comprises a warehouse data acquisition unit, which acquires equipment operation data and environmental parameters and standardizes the same; a warehouse resource state feature extraction unit, which extracts resource state features to form abnormal features; a reinforcement learning state space construction unit, which analyzes the features to form state space construction parameters; a resource allocation strategy generation unit, which constructs a model to generate a strategy and divides influence factors; and a strategy adaptive optimization unit, which updates and optimizes the strategy by using an algorithm. In addition, the system is provided with a multi-source information fusion unit and a task queue dynamic adjustment module. The system realizes adaptive collaborative allocation of warehouse resources, improves warehouse operation efficiency, adapts to dynamic changes of a warehouse system, and meets the demand of modern warehouse intelligent operation.

The utility model relates to the technical field of intelligent transportation, concretely relates to high -speed toll station vice node railing machine, including railing machine body, set up on railing machine body and show module of fee of snapshot module and, snapshot module and show module of fee set up in the one side of railing machine body front end facing the lane transaction area, be provided with communication module in the railing machine body, this communication module is used for with ETC lane antenna carries out data interaction, and the transaction data of lane antenna is received through communication module and is shown through show module of fee of railing machine body, the lower extreme of pole machine body is provided with base, and the fixed part of base and setting in the bottom of railing machine body is connected in sliding fit, and the bottom of base is the sliding fit connection of sliding slot and sliding rail, the utility model relates to a kind of high -speed toll station vice node railing machine, solve the problem that multiple stand, construction complex caused by traditional ETC lane snapshot and fee show device independent setting, railing machine is simultaneously realized convenient installation and position adjustment by sliding base.

This invention discloses an energy-saving control method for central air conditioning chillers based on an energy demand prediction model, belonging to the field of central air conditioning energy-saving control technology. It addresses the problems of existing chiller control methods relying on manual experience, passive adjustments, and high energy consumption. The method includes: collecting relevant data from the air conditioning operating system, outdoor environment, control terminal environment, and control targets from multiple dimensions; constructing a chiller energy demand prediction model using machine learning algorithms to achieve accurate prediction of chiller energy demand; proactively and collaboratively adjusting the chiller operating frequency, circulating water pump operating status, the number of chillers and water pumps started and stopped, and inlet and outlet water temperatures based on the prediction results; and optimizing the model and control strategy through real-time feedback to form a closed-loop control. This invention achieves predictive and anticipatory chiller control, eliminating reliance on manual experience and realizing truly intelligent control. It significantly reduces chiller energy consumption, improves system operational stability and equipment lifespan, and is applicable to energy-saving control of various central air conditioning chiller systems.

The invention discloses a water mixing energy-saving optimization method based on oil pressure analysis, and relates to the technical field of oil field gathering and transportation water mixing optimizing.The method comprises the following steps that real-time parameters and historical data of wells in different metering rooms in a current oil field gathering and transportation station are collected, and the real-time parameters and historical data comprise the oil pressure and the water mixing flow of each well and the total water mixing flow of the metering rooms; establishing a watering optimization database and recording acquisition parameters of different metering rooms in the current oil field gathering and transportation station; the real-time data of each well is obtained through the watering optimization database, and the oil pressure safety upper limit and the oil pressure rising rate threshold value are obtained through the collected data of different wells of the current oil field gathering and transportation station in the historical monitoring period based on the change condition of the real-time parameters in the monitoring period. According to the method, the well state is accurately judged based on oil pressure analysis, overall collaborative optimization from a single well to a metering room is achieved, and safety guarantee, energy conservation and consumption reduction in oil field gathering and transportation are both considered.

The invention provides a new energy unit transient stability optimization method and system based on active feed-forward, and belongs to the field of new energy power generation. The system includes a current command generator and a current controller. The method comprises the steps of collecting terminal voltage and current of a unit, calculating active power and detecting a transient fault; when a fault is detected, generating an active current instruction through active feed-forward control based on power grid voltage information obtained by an active power signal, a fault voltage amplitude signal and phase locking; meanwhile, a reactive current instruction is generated; a current reference instruction is synthesized, and a converter is driven through closed-loop control to provide power support. According to the method, an active feed-forward mechanism is introduced, so that the new energy unit can respond to the power shortage of the power grid in advance, active and reactive support is quickly provided, frequency drop and power oscillation in the transient process are effectively inhibited, and the transient stability of the power system under the access of high-proportion new energy is remarkably improved.

The invention discloses a full-crosslinking layered fluorine-containing epoxy super-hydrophobic coating and a preparation method thereof, and belongs to the technical field of super-hydrophobic coatings. The coating comprises the following raw material components: epoxy resin, fluorine-containing epoxy acrylic resin, KH560 modified nano silicon dioxide, a curing agent, an accelerant and the like. The preparation method of the coating comprises the following steps: carrying out surface grafting modification on the nano silicon dioxide particles by using a KH560 siloxane coupling agent; the preparation method comprises the following steps: synthesizing fluorine-containing epoxy acrylate low-surface-energy resin by using tridecafluorooctyl methacrylate, glycidyl methacrylate and isobornyl methacrylate; the coating is prepared by adopting a step-by-step spraying method, the primer is epoxy resin, the surface wear-resistant super-hydrophobic layer is fluorine-containing epoxy acrylate low-surface-energy resin blended modified nano silicon dioxide particle filler, and the three components are integrally crosslinked through epoxy groups. According to the method, the adhesive force and durability of the coating can be improved, and the coating has good super-hydrophobic performance and is suitable for various working conditions.

The application discloses a kind of based on temperature control curve's forging heat treatment process optimization method, it is related to data processing technical field, including, based on process task data packet, temperature control performance prediction model is constructed and reverse solution is executed, generates core temperature control reference curve;To core temperature control reference curve executes heat response mapping, obtains furnace temperature control trajectory, and obtains online core tracking control scheme by heat treatment risk timing evaluation;Online core tracking control scheme is executed, process data is recorded synchronously, and combined furnace temperature control trajectory is passed through heat history inversion operation, obtains execution temperature control curve;Based on execution temperature control curve, temperature control performance prediction model is optimized, and obtains process quality evaluation result by performance deviation evaluation.The application is by constructing temperature control performance prediction model and executing reverse solution and feedback optimization, improves the calculation consistency of process parameter design and the quantifiable and iterative optimization ability of result evaluation.

The invention relates to a method for improving the dustpan filling rate of a bucket elevator. The method comprises the steps that dustpan filling images and equipment data are obtained in real time through a sensor network; transmitting the data to an edge AI calculation unit, performing millisecond-level reasoning by using a lightweight convolutional neural network model, estimating a filling rate in real time and identifying a material type; based on a reasoning result, dynamically and cooperatively adjusting operation parameters, including changing the geometric volume of the deformable intelligent winnowing pan through a micro driving mechanism, adjusting the speed of the elevator and controlling a feeding auxiliary device, and continuously optimizing decision logic of the system by a digital twin model, according to the model, an optimization strategy set is generated in advance through discrete element simulation and a Bayesian optimization algorithm, and the system has a maintenance function of predicting performance degradation by analyzing current and vibration data and can cooperate with upstream and downstream equipment to realize global energy efficiency optimization; according to the scheme, the problem that the filling rate of a traditional elevator is unstable due to variable materials and fixed bucket types is solved, and self-adaptive precise control is achieved.