428results about How to "Improve friendliness" patented technology

The invention belongs to but not limited to the technical field of fault diagnosis and maintenance of power equipment, and discloses an intelligent diagnosis and maintenance system and method for power equipment based on a knowledge graph. A data acquisition and preprocessing module acquires real-time operation data and historical data of the power equipment; the knowledge graph construction module associates various kinds of information of the power equipment to construct a knowledge graph; the intelligent diagnosis module performs association analysis on power equipment faults based on a knowledge graph and a machine learning algorithm, identifies fault modes and potential faults, and predicts possible faults of the equipment; the maintenance suggestion module automatically generates a detailed maintenance scheme according to the diagnosis result; the operation and maintenance visualization module provides visual fault diagnosis results and maintenance suggestions, supports multi-level data display, and helps operation and maintenance personnel to clearly understand the equipment state. The operation safety of the power equipment is improved, the operation and maintenance cost is remarkably reduced, and the overall efficiency of equipment management in an intelligent power grid environment is improved.

The invention relates to the technical field of virtual simulation and human-computer interaction, in particular to a semantic association modeling and self-adaptive simulation method based on multilayer correction, which comprises the following steps of: acquiring characteristic data from a three-dimensional simulation model and an electrical schematic diagram, and generating situation dynamic model data through data cleaning and standardization processing; constructing a semantic incidence matrix based on the situation dynamic model data, generating a geometric layer model, a logic layer model and a cross-domain layer model, and generating dynamic state and logic state data through distributed cellular automaton simulation; and in combination with simulation data, optimizing a semantic incidence matrix and a dynamic modeling rule by utilizing a causal path inference algorithm and a multi-layer correction mechanism, and realizing state linkage and user interaction feedback of the three-dimensional simulation model and the electrical schematic diagram. The state synchronization accuracy and interaction efficiency of the complex system are remarkably improved, and the method is suitable for the fields of industrial design, simulation verification and teaching training.

The invention discloses an automatic large language model selection method based on multi-dimensional evaluation and dynamic weight adjustment, and aims to solve the problems of low text generation quality, inaccurate dialogue questions and answers, low online assistant task completion rate and the like in an existing large language model by introducing a multi-dimensional evaluation mechanism. According to the method, a plurality of evaluation dimensions such as ROUGE index evaluation, text quality evaluation, semantic similarity evaluation, safety compliance evaluation, front suitability evaluation, question and answer evaluation, dialogue evaluation, online customer service evaluation and online assistant evaluation are comprehensively considered, the performance of the large language model is comprehensively evaluated, and through analysis of operation data and user feedback, the evaluation accuracy of the large language model is improved. And dynamically adjusting the weight of each evaluation dimension to adapt to continuously changing application requirements and user expectations. And finally, according to the comprehensive score, an optimal large language model is automatically selected, and high quality and user satisfaction of Web services are ensured.

The invention provides a multi-agent cooperation system, which comprises a multi-agent cooperation engine module, a task decomposition and distribution module and a tool calling normal form module, and is characterized in that the task decomposition and distribution module is used for decomposing tasks and distributing decomposed sub-tasks to agents; the multi-agent cooperation engine module is used for managing cooperation and communication between agents; and the tool calling module enables the intelligent agent to dynamically call different tools. According to the multi-agent collaboration system, the collaboration efficiency among the agents, the flexibility of task decomposition, the adaptivity of tool calling and the intelligent level of user interaction are remarkably improved, and remarkable technical advantages and effects are shown in complex task processing and dynamic environment processing.

The invention discloses a high-flow-resistance multi-point observation type fish school monitoring underwater robot based on multi-source data fusion. The high-flow-resistance multi-point observation type fish school monitoring underwater robot comprises a shell, a self-adaptive ocean current resistance system and an energy system. The self-adaptive ocean current resistance system comprises an ocean current information detection module and a PID control algorithm real-time regulation and control propeller module; the ocean current information detection module is used for collecting ocean current information in real time, including water velocity, direction and turbulence intensity; the control algorithm real-time regulation and control thruster module regulates and controls the power and direction of a thruster in real time by utilizing a PID control algorithm according to ocean current changes, and it is ensured that the underwater robot keeps stable in complex ocean currents; the telescopic multi-sensor fusion system collects multi-dimensional data of a fish school by combining a plurality of sensors, and performs fusion analysis on the data by using a deep learning algorithm, thereby realizing high-precision fish school identification and tracking. And an integrated ocean current-solar energy system enables the underwater robot to have long-time cruising ability.

The invention discloses a multi-scale feature fusion fault prediction method for a high-speed rail bearing. The method comprises the following steps: acquiring a fault vibration signal of the high-speed rail bearing through a vibration signal comparison technology; noise and interference signals of the high-speed rail bearing fault original vibration signals are removed through an adaptive filter; performing multi-level decomposition on the vibration signal by using wavelet packet decomposition, extracting sub-band signals of different frequency bands, calculating instantaneous frequency and energy distribution of the sub-band signals by using Hilbert-Huang transform, and forming a time-frequency-energy three-dimensional feature map; carrying out weight distribution on each feature dimension in the three-dimensional feature map by adopting a self-adaptive weighting algorithm; constructing a training data set through the time-frequency-energy three-dimensional feature map and the fault type label; and training the long short-term memory network LSTM by using the training data set, constructing a fault prediction model, and performing fault prediction on the high-speed rail bearing. According to the invention, accurate prediction of the high-speed rail bearing fault is realized, and the accuracy of fault detection is improved.

The invention relates to the technical field of smart city traffic, in particular to a smart city traffic indication system and a working method thereof. According to the technical scheme, the system comprises a multi-source heterogeneous data acquisition module, a data preprocessing and fusion module, a feature extraction and analysis module, a traffic flow prediction and signal timing decision module and a signal display and communication module, the acquisition frequency is dynamically adjusted according to the traffic flow. Traffic and meteorological data are dynamically collected through multiple types of sensors, the quality of data preprocessing and fusion is guaranteed, features are accurately extracted, signal timing is optimized through reinforcement learning, the display and communication module effectively transmits information and cooperates with surrounding traffic, emergency situations can be dealt with, tail gas emission is reduced, pedestrian waiting time is shortened, and traffic safety is improved. And a basis can be provided for long-term traffic planning, and the traffic efficiency, the environmental protection property and the pedestrian friendliness are comprehensively improved.

The invention discloses a high-integration-level and efficient-cooling external rotor motor ducted fan system, which belongs to the technical field of ducted fans and comprises a motor stator winding and a fan external rotor integrated part integrally formed by fan blades and a motor external rotor turntable, the integrated shell is integrally formed by a motor inner stator sleeve, a ducted nacelle, a motor controller main shell and a plurality of groups of ducted stationary blades; a cooling structure is mounted on the integrated shell; a motor stator winding is fixedly connected to the outer wall of one end of the integrated shell, the front flow guide cover is fixedly connected to the fan outer rotor integrated part, and the rear flow guide cover is installed at the other end of the integrated shell. And the integrated shell is rotationally connected with the fan outer rotor integrated piece. The system is low in noise, high in integration level, high in system reliability, high in system cooling efficiency, high in power level compatibility and high in expandability.

The invention relates to the technical field of mine electromechanical equipment management and maintenance, in particular to a mine electromechanical equipment full-life-cycle management method and system, and the method comprises the steps: carrying out the equipment debugging according to the production characteristics and environmental conditions of a mine; the operation state and performance indexes of the equipment are monitored in real time, the monitoring content is analyzed through an intelligent diagnosis algorithm of the mine electromechanical equipment, and fault judgment is conducted; formulating an intelligent repair scheme and a maintenance strategy according to a fault judgment result; carrying out full life cycle management and optimization on the mine motor equipment; by combining technical means of equipment debugging, real-time monitoring, intelligent diagnosis, intelligent repair and maintenance, full-life-cycle management and the like, the management and maintenance level of the mine electromechanical equipment is improved, the comprehensive benefits of the equipment are improved, and the service life of the equipment is prolonged.

The invention relates to an intelligent photovoltaic power generation control device which integrates a photovoltaic power generation panel, a series connection base, a supporting assembly, a water collection groove, a rainwater collection assembly, a cleaning assembly and a control assembly. A series base and a series interface are arranged below the photovoltaic panel, so that modular installation is facilitated; the supporting assembly comprises two supporting rods, the light following function is achieved, and the photovoltaic panel is automatically adjusted to face the sun. A water collecting groove above the photovoltaic panel and a rainwater collecting assembly at the bottom of the photovoltaic panel can collect and store rainwater; the cleaning assembly comprises a spraying unit and a cleaning brush and is used for automatically cleaning the surface of the photovoltaic panel; the control assembly monitors operation of the system and adjusts the posture of the photovoltaic panel and work of the cleaning assembly. Redundant electricity generated by the photovoltaic power generation panel in sunny days is stored for the system to use, and the light following function is not started in cloudy days, so that electric energy is saved; through the design, the efficiency and sustainability of photovoltaic power generation are improved; the energy conversion efficiency can be improved, the reliability and automation level of the system are enhanced, and the utilization and environmental friendliness of rainwater are improved.

The invention discloses a steel wire rope derailment early warning method and system for a container crane pulley block, and the method comprises the steps: collecting real-time images of the pulley block and a steel wire rope, and achieving the automatic monitoring of the operation state of the steel wire rope through feature point detection and geometric transformation estimation; and by utilizing the structural knowledge of the pulley block, accurate derailment detection is carried out under the condition of a small number of samples or even almost no samples, so that the cost of data preparation and model training is reduced. The method is easy to control, a user only needs to manually specify masks of a pulley area, a cross beam area and a steel wire rope area and mark key structure feature points, the system can automatically extract features and perform subsequent automatic detection, and the method has good user friendliness and adaptability.

The invention relates to an inter-satellite link communication simulation system and method based on a satellite constellation. The system comprises a satellite orbit simulation module, a satellite attitude simulation module, an inter-satellite communication link simulation module, a visualization and interaction technology module and a data interaction and system test module. The satellite orbit simulation module is used for calculating a movement track of a satellite in an earth gravitational field; the satellite attitude simulation module is used for accurately simulating a satellite attitude; the inter-satellite communication link simulation module is used for evaluating inter-satellite communication quality; the visualization and interaction technology module is used for presenting real-time states of satellite orbits, attitudes and inter-satellite links; and the data interaction and system test module is used for smoothly exchanging data, and comprehensively testing and checking the correctness and performance of satellite orbits, attitudes and communication functions. The method has the beneficial effects that the real-time states of the satellite orbit, the attitude and the inter-satellite link are efficiently presented, so that a user can easily monitor and control the simulation process.

The invention relates to an agricultural waste intelligent classification and processing system, which comprises a sensor system, a data acquisition and processing module, an intelligent algorithm module, an execution mechanism module and a user interface, the data acquisition and processing module cleans and preprocesses sensor data and extracts data features, the intelligent algorithm module provides a feasible scheme for classification and processing of agricultural wastes in the environment, and the execution mechanism module selects automatic processing programs including waste incineration and organic matter composting according to classification results. The user interface provides an interface for interaction between a user and the system, allows the user to monitor the operation state of the system, inquire the processing result and carry out necessary adjustment, and the system realizes intelligent processing of agricultural wastes, improves classification accuracy and processing efficiency, and provides an innovative solution for environmental protection and resource recovery.

The invention provides an epilepsy detection device, and relates to a medical equipment technology. The epilepsy detection device comprises a wearable device, the wearable device comprises a data acquisition module, a data processing unit, a communication module, a software algorithm and a system platform, and the data acquisition module comprises an electromyogram sensor, a heart rate monitoring sensor, an accelerometer, a gyroscope and a skin electrical activity sensor. The data processing unit comprises a microprocessor and a memory, the communication module comprises a Bluetooth / Wi-Fi module and a mobile application / cloud platform, and the software algorithm comprises a signal processing algorithm and an optimization algorithm. By combining medical history data of a patient, including epileptic seizure history, seizure type, frequency, duration time, preamble before seizure, symptoms after seizure and the like of the patient, genetic history and medical history of epilepsy or other related diseases in a family, a more personalized model is trained, and more accurate monitoring and early warning are provided for the patient.

The invention provides a method and device for calculating pipeline leakage flow based on pressure change, and belongs to the technical field of gas leakage detection. The method for calculating the pipeline leakage flow based on the pressure change comprises the following steps that S1, a pressure simulation model is established, a pipeline is simulated according to the pressure simulation model, and pressure change data, changing along with time, in the pipeline is obtained; s2, the leakage opening area value and the total gas volume value corresponding to the gas meter and the pipeline are obtained; and S3, establishing a leakage rate calculation model, and inputting the gas total volume value, the leakage port area value and the pressure change data into the leakage rate calculation model to calculate and obtain a leakage flow rate value. The pressure simulation model simulates the pipeline to obtain the pressure change data, the gas leakage flow can be accurately calculated by comprehensively considering the pressure change, the leakage opening area and the gas volume, the method can be widely applied to household and industrial gas pipelines, gas waste is reduced, and environmental pollution is reduced.

The invention belongs to the field of pesticides, and relates to a composition containing a biological source pesticide. The composition contains an active component A and an active component B, the component A is selected from a compound I-72, and the component B is selected from biological source insecticides and acaricides; the weight part ratio of the component A to the component B is (1: 99)-(99: 1); wherein the structural formula of the compound I-72 is shown in the specification, and the composition disclosed by the invention has an obvious synergistic effect and can be used for preventing and treating various pests and pest mites. # imgabs0 #

The invention relates to the technical field of environment monitoring, in particular to a pollution source online monitoring and analysis system and method, and the system comprises a map building unit which is used for carrying out the three-dimensional map modeling of a target monitoring area; the man-machine interaction unit is used for issuing a monitoring control command; the acquisition monitoring unit is used for calculating data sampling density and acquiring environment data; the threshold value early warning unit is used for comparing data to judge whether the pollution source is a suspected pollution source or not; the pollution confirmation unit is used for setting an identification framework for the received environmental data of the suspected pollution source so as to judge whether the suspected pollution source is a real pollution source or not; and the diffusion analysis unit is used for matching the environmental data of the real pollution source with the pollutant diffusion model to obtain the diffusion range of the real pollution source. According to the invention, through environment data acquisition of the unmanned ground vehicle, multiple environment data of a water area and soil can be obtained in real time in a target monitoring area, so that pollution conditions can be found and responded in time, and potential hazards caused by environment pollution are reduced.

The invention relates to the technical field of brain-computer interfaces, in particular to a self-adaptive calibration method and system for a brain-computer interface earphone, and the method comprises the following steps: obtaining electroencephalogram data; based on the electroencephalogram data, constructing an initial model through federal learning; selecting a user specific sample by using an active learning strategy; performing dynamic parameter optimization on the initial model; based on the result of the dynamic parameter optimization, adaptive personalized calibration is executed; performing anomaly detection and correction on the result of the self-adaptive personalized calibration; performance evaluation is carried out on the result obtained after anomaly detection and correction, the evaluation result is fed back to the previous steps, and the steps form a closed-loop optimization process; through the combination of federal learning and active learning, the calibration time is shortened from 45 minutes of a traditional method to about 5 minutes, and the efficiency is improved by nearly 9 times; the accuracy rate of the method reaches 95.8% and is improved by 8.6% compared with that of a traditional method.

The invention provides a smart home control system of a single-chip microcomputer based on the 5G Internet of Things, and the system comprises a sensor module which collects environment data, a data processing module which integrates the data, and a deep Q network control module which is internally provided with a DQN algorithm model, learns and trains home environment data and user behavior data, generates a control strategy, and achieves the intelligent control of home equipment. According to the invention, the automation and intelligence level of the home environment can be effectively improved, and efficient, energy-saving and user behavior self-adaptive home equipment management is realized.

The invention discloses a gold leaching process using a high-safety bromine-containing substance, and belongs to the technical field of gold extraction. According to the method, the dibromo dimethyl hydantoin and the calcium bromide are prepared into the leaching solution according to a certain proportion, efficient gold leaching is achieved by adjusting parameters such as the pH value and the leaching time under the condition of the metal ion catalyst, and the gold can be effectively adsorbed, analyzed and recycled through the leached pregnant solution. Meanwhile, bromine in the leachate is recycled through an electrochemical method, bromine is prevented from permeating into the environment, the dosage of chemicals is reduced, a complete gold leaching and chemical circulating system is constructed, the gold leaching efficiency is improved, the environmental risk is reduced, the technical applicability is expanded, and the defects that traditional liquid bromine gold leaching is large in toxicity, low in leaching rate and leaching efficiency and the like are overcome.

The present invention relates to the technical field of catalysts, and discloses a hydrogenation catalyst and a preparation method thereof, and a hydrogenation method of an organic hydrogen storage material, the method comprises: (1) mixing an active metal component precursor, a dispersion component precursor, an auxiliary agent metal precursor, an Al salt and a solvent to obtain a salt solution; wherein the active metal component is selected from Ni and / or Co, the dispersion component is selected from Zn and / or Mg, and the auxiliary metal is selected from at least one of rare earth metal, VIIB group metal, IVB group metal and VIB group metal; (2) contacting the porous carbon with acid under a stirring condition to obtain acid-treated porous carbon; (3) mixing the acid-treated porous carbon, a salt solution, a surfactant and alkali, and carrying out precipitation reaction; and (4) roasting the product obtained in the step (3) in an inert atmosphere. The hydrogenation catalyst prepared by the method shows extremely high activity in the hydrogenation process of a hydrogen storage medium.

The invention provides a cross-micro-grid power transaction method based on cross-chain of a block chain, and comprises a cross-micro-grid power transaction method based on a cross-chain technology of the block chain. Comprising the steps of transaction demand and quotation submission, cross-chain information synchronization and summarization, expected transaction set generation, transaction matching calculation, transaction result verification, smart contract transaction execution, reputation index adjustment and unmatched transaction processing. The micro-grids share power supply or demand and quotation information through the cross-chain technology, and the relay chain technology broadcasts information to ensure information synchronization. The micro-grids form an expected transaction set, and transaction matching is calculated and synchronized through a cross-chain technology. And after verification succeeds, the smart contract automatically executes a transaction and records a result, the reputation index is updated, and unmatched transactions can be transacted with the public power grid. According to the invention, the transaction efficiency and reliability can be improved, the reputation index is dynamically adjusted, a multi-dimensional evaluation system is adopted, and the fairness and environmental friendliness of the transaction are enhanced.

The invention discloses a digital modeling response method, system and device based on artificial intelligence, and a medium. The method comprises the following steps: S1, obtaining multi-level public security system business data; s2, performing preprocessing operations of data filtering, data recovery, data enrichment and data serialization on the public security system business data to form structured data; s3, inputting text information required by digital modeling by a user through a visual interface, and performing semantic recognition on the input text information by using a large language model to obtain text information features; and S4, selecting corresponding digital modeling demand information features according to the text information features, constructing a data analysis model in combination with standard structured data, and outputting a digital modeling result according to the data analysis model. According to the method, the problems that a digital modeling technology based on artificial intelligence has a high access threshold and a complex use process in the field of public security, and non-professional users are remarkably limited in the process of participating in digital modeling are solved.

The invention discloses a high-effect sludge deep dehydration coupling resource utilization system and method, and relates to the technical field of sewage treatment.The method comprises the steps that special stirring equipment is adopted for stirring sludge, the stirred sludge is pretreated through ultrasonic waves and an advanced oxidation technology, and pretreated sludge is obtained; discharging free water and interstitial water from the pretreated sludge through an intelligent pressure maintaining and pressure relief regulation mechanism, then carrying out microwave-assisted heating by using a continuous low-temperature sludge drying machine, and adjusting microwave power and heating time to deeply remove bound water and interstitial water; carrying out pyrolysis carbonization on the sludge subjected to microwave-assisted heating through an indirect heating reaction furnace, and converting organic matters in the sludge into pyrolysis products; the sludge treatment efficiency and quality are remarkably improved through a series of innovative technologies, the special stirring equipment is combined with ultrasonic waves and the advanced oxidation technology, the physical and chemical properties of the sludge are optimized, and the energy consumption of the subsequent process is reduced.

The invention relates to the technical field of building materials, and provides a high-durability modified cement-based composite material and a preparation method thereof.The high-durability modified cement-based composite material comprises a carbon dot polymer, mixing water and Portland cement, and the specific preparation steps are as follows: adding citric acid and urea into water to be dissolved, and then putting into a high-pressure reaction kettle to be heated to obtain an initial product; adding the initial product into water, and carrying out centrifugation, filtration, rotary evaporation and drying to obtain the carbon dots; the preparation method comprises the following steps: dissolving carbon dots in water, preparing an initial carbon dot polymer product by adopting a hydrothermal method or a microwave method, adding the initial carbon dot polymer product into water, centrifuging, filtering, rotationally evaporating and drying to obtain a carbon dot polymer; and mixing the carbon dot polymer with mixing water and Portland cement to obtain the high-durability modified cement-based composite material. The modified cement-based composite material prepared by the invention is simple to prepare, low in cost, green and low-carbon; the rust can be efficiently inhibited, and concrete reinforcements are effectively protected from being corroded; the method can be widely applied to reinforced concrete and has wide application prospects.

The invention relates to a multi-mode-based family member relationship autonomous learning method and device. The method comprises the following steps: acquiring image data and voice data; the image data comprises a face image, and the voice data comprises voiceprint information and semantic information; acquiring attribute information corresponding to the face image based on the image data, predicting a family identity corresponding to the face image based on the face image in combination with the voiceprint information and the attribute information, and generating a family personnel knowledge graph; identity keywords related to family identities are monitored on the basis of continuously updated semantic information, and a family personnel knowledge graph is iteratively corrected on the basis of the identity keywords and continuously updated face images, attribute information and voiceprint information, so that autonomous learning of family personnel relationships is realized. According to the invention, through combination of various modes such as human faces and voiceprints and combination of a natural language processing technology, completely autonomous learning of family personnel relationships is realized, and naturalness and friendliness of man-machine interaction are improved.

The invention provides a method for crushing zero-valent iron. The method comprises the following steps: adding FeS, FeS2, zero-valent iron powder and absolute ethyl alcohol into a container, and uniformly stirring to form slurry to be ground; the wet ball mill is filled with grinding beads, the slurry to be ground is added into the wet ball mill to be ground, slurry is obtained, and the grinding time is 10-640 min; taking out the slurry from the wet ball mill, putting the slurry into magnetic separation equipment for separation, collecting ground zero-valent iron particles, and washing with absolute ethyl alcohol; and the washed zero-valent iron particles are placed in a vacuum drying box and dried at the temperature lower than 40 DEG C.

The invention relates to the technical field of data caching, and discloses a rapid page configuration method and device for customer customization and a medium, and the method comprises the steps: obtaining a user demand, behavior data and an accessory library, encrypting and uploading the user demand and the behavior data to a preset block chain, obtaining an intelligent contract, and storing the intelligent contract in the accessory library; extracting a basic accessory from an accessory library according to a questionnaire demand in the user demand by using an intelligent contract; semantic analysis is carried out on supplementary demands in the user demands to obtain supplementary information demands, and supplementary accessories are screened out from the accessory library by utilizing the supplementary information demands; calculating the actual accessory use probability of the user according to the behavior data, and performing weight configuration on the supplementary accessory and the basic accessory according to the actual accessory use probability of the user to obtain to-be-processed accessory information; and performing personalized page construction according to the to-be-processed accessory information to obtain a customized page. According to the method, the individuation degree of page configuration can be improved, and privacy data of a user can be protected.

The invention discloses a person and post matching system based on candidate geographical location information and retail stores, and relates to the technical field of post matching systems. The candidate geographic position information and retail store-based person and post matching system comprises a candidate information management module, a retail store information management module, a commuting data analysis and path planning module, a candidate and store matching module and a result display and feedback adjustment module. By collecting and processing commuting modes and time period preferences of candidates, a commuting path is planned in combination with a map service API, and commuting time considering congestion and congestion influence is calculated, so that the matching accuracy and practicability are improved. In addition, the system also combines factors such as working experience, skills and the like to carry out matching result optimization, so that bidirectional selection is realized, and the matching satisfaction degree is improved. And the result display and feedback adjustment module enables the user to visually see the matching result.

The utility model discloses a high-precision laser welding machine which comprises a main machine body, a moving device is installed on the upper portion of the main machine body, the moving device comprises an X-axis lead screw machine, the lower portion of the X-axis lead screw machine is fixedly connected with the main machine body, and a Y-axis lead screw machine is fixedly connected to the upper portion of a sliding seat of the X-axis lead screw machine. A Z-axis lead screw machine is fixedly connected to the upper portion of a sliding base of the Y-axis lead screw machine. A sliding connection structure of the rectangular sleeve and the rectangular supporting block is introduced into the fine adjustment device, the transverse installation frame and the transverse supporting rod are matched, and the fine adjustment function of the laser welding head is achieved. By means of the innovative design, the adjusting process is simplified, the adjusting precision is improved, and the stability and the repeated positioning precision of the laser welding head after adjustment are guaranteed. In this way, the device has the advantage that the device can be quickly recovered to a set accurate position even after long-time operation.