159results about How to "Collaborative work" patented technology

The invention relates to the technical field of artificial intelligence, and discloses an AI large model enterprise knowledge base system based on cue words, comprising a front end interaction module; a large model module; a knowledge base module; a vector database module; a fine tuning module; a function calling module; and a monitoring and optimizing module. According to the AI large model enterprise knowledge base system based on the cue words, knowledge documents in an enterprise are stored and managed in a centralized mode, efficient knowledge retrieval and matching are conducted through the vector database module, the knowledge base module can be customized according to enterprise requirements, document storage of various formats is supported, a convenient document management function is provided, and the knowledge management efficiency is improved. And the fine tuning module integrates enterprise knowledge into the large model, so that the large model can understand and process special knowledge and implicit knowledge in the enterprise, thereby improving the specificity and knowledge application capability of the system, effectively integrating and managing the enterprise knowledge, converting the enterprise knowledge into operable information, and providing powerful support for decision and operation of the enterprise.

The invention discloses an intelligent security and protection monitoring method and system based on image recognition. The method comprises the following steps: S1, acquiring multi-modal data; s2, performing preprocessing to generate complete target information; s3, performing real-time detection on the generated complete target information, and performing primary processing on a conventional scene; s4, based on an improved visual SLAM technology, obtaining three-dimensional information of multiple cameras; s5, when the edge device detects a potential abnormal condition, performing abnormal behavior analysis on the data by using a Swin Transform model, and optimizing a detection result in combination with the three-dimensional information of the multiple cameras; s6, performing adaptive learning on historical data by using a depth deterministic strategy gradient algorithm, and dynamically adjusting a threshold value of abnormal behavior detection; and S7, after an abnormal condition is detected, processing data through differential privacy protection and an end-to-end encryption technology, automatically controlling security and protection equipment, and giving a real-time alarm. According to the invention, image recognition and deep learning technologies are fully utilized, and accurate real-time monitoring in a complex scene is realized.

The invention discloses a data cooperative transmission method and system for a low earth orbit satellite Internet of Things terminal, and the method specifically comprises the steps: carrying out the classification cutting of environment data, and forming a plurality of environment data subsets; determining a plurality of cooperative sending terminals and respective optimal communication paths between the first low earth orbit satellite Internet of Things terminal and each cooperative sending terminal based on a communication topological structure relationship between the low earth orbit satellite Internet of Things terminals in the ad hoc network; transmitting the environment data subsets with different priorities to corresponding cooperative sending terminals through different optimal communication paths; and according to the environment data subsets sent by each cooperative sending terminal and received by the low-orbit satellite, splicing the environment data subsets and forwarding the spliced environment data subsets to a target terminal or a ground station or a data center. According to the invention, the cooperative effect among a plurality of low-orbit satellite Internet of Things terminals can be fully utilized, and stable and reliable data transmission under the requirements of large data volume and high real-time performance is realized.

The invention belongs to the technical field of artificial intelligence and big data analysis, and particularly relates to a scenic spot passenger flow trend prediction analysis method based on an AI big language model. According to the method, big data and artificial intelligence technologies are utilized, LBS data, scenic spot data, holiday and festival information, third-party maps, weather data and other multi-source data are comprehensively applied, a comprehensive multi-dimensional knowledge base is constructed, and meanwhile, the knowledge search and generation capability is improved by utilizing an RAG technology; through model pre-training and fine tuning, the universal model capability is developed, and a multi-agent system is further constructed; based on the natural language processing capability of the AI large language model, the LLM can intelligently analyze the text input of the scenic region administrator, drive the cooperative work among multiple agents, and achieve the intelligent prediction and analysis of the scenic region passenger flow trend. The method can more accurately predict the passenger flow trend of the scenic area.

The invention provides an intelligent industrial quality inspection method and system based on AI visual identification, and relates to the technical field of visual identification, and the method comprises the steps: inputting an industrial product image collected at an edge end into a pre-trained defect region detection model, and obtaining a defect region detection result; extracting defect area features according to a defect area detection result, carrying out dimension reduction processing to obtain compressed defect area features, and deciding to unload a defect classification task to a cloud end or directly carry out defect classification at the edge end according to an adaptive task unloading strategy in combination with working data of the edge equipment; if the defect classification task is determined to be unloaded to the cloud, transmitting the compressed defect area features to the cloud through a network, performing defect type identification on the cloud by adopting a pre-trained defect classification model, outputting a classification result of the defect area, returning the classification result to an edge end, and combining a defect area detection result and the classification result of the defect area to obtain the defect classification task. And generating a defect visualization effect picture and a quality inspection report.

The invention relates to the technical field of illumination night scene control, in particular to an urban travel illumination night scene interconnection control method and system based on a photovoltaic technology. The method comprises the following steps: acquiring scenic spot people flow monitoring parameters and photovoltaic illumination night scene equipment state data; carrying out spatial position positioning calculation on all the photovoltaic illumination night scene equipment, and carrying out spatial distribution analysis to obtain a plurality of equipment area distribution diagrams; carrying out regional electricity load calculation on the plurality of equipment region distribution diagrams based on the state data of the photovoltaic illumination night scene equipment, and carrying out electricity load demand prediction so as to generate electricity load demand prediction data of each region; and carrying out people flow distribution calculation on the scenic area people flow monitoring parameters based on the plurality of equipment area distribution diagrams, and carrying out short-term people flow situation prediction to generate people flow situation prediction data of different areas. According to the invention, illumination night scene control with efficient response and low energy consumption is realized.

The invention discloses an HDI circuit board laser drilling device, and particularly relates to the technical field of HDI circuit board drilling, the HDI circuit board laser drilling device comprises an operation table, a rotating mechanism is rotatably connected to the right side of the middle of the upper end of the operation table, a transmission mechanism is rotatably connected to the front side of the upper end of the operation table, and a drilling mechanism is fixedly connected to the middle of the upper end of the operation table; an air blowing mechanism is arranged on the left side of the lower portion of the drilling mechanism. According to the HDI circuit board laser drilling device, in the descending process of the laser drilling head, a baffle is driven to be matched with a rectangular block, the HDI circuit board can be automatically and accurately positioned, the drilling precision and efficiency are improved, in the drilling process, a spray head is matched with a limiting pipe and a first sliding block, and therefore the HDI circuit board can be accurately drilled. According to the HDI circuit board drilling device, the surface of a drilled HDI circuit board is cleaned through the soft brush, chippings and dust generated in the drilling process can be removed, meanwhile, in the reset process of the laser drilling head, the surface of the drilled HDI circuit board is cleaned through the soft brush, the residual chippings and dust can be removed, and the cleanliness of the HDI circuit board is guaranteed.

The invention relates to the technical field of power distribution room inspection, in particular to an inspection control system based on a power distribution room inspection robot. Comprising a server, an inspection analysis module and an inspection control module, the inspection analysis module performs real-time monitoring and comprehensive analysis on each power distribution room, equipment in the power distribution room and the environment of the power distribution room to obtain a monitoring index value; generating a trend curve of monitoring index values along with time change through a time sequence analysis method, and performing graphic analysis on the curve to effectively judge the routing inspection priority of the power distribution room; the inspection control module carries out analysis according to the inspection value of each power distribution room and the historical maintenance record and historical inspection times of each inspection robot, and can comprehensively know the operation stability and inspection work efficiency of the inspection robot; according to the matching value of the inspection robot and the current task number, the tasks of the inspection robot can be updated in real time, load balance of each robot is ensured, and the high-risk inspection task of the distribution room is processed preferentially.

The invention provides a digital twinning method and system for a flexible brushless motor production line, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: collecting a multi-source data set from the flexible brushless motor production line, and extracting time sequence features from the multi-source data set; analyzing the extracted time sequence features by adopting a recurrent neural network, and outputting a rule adjustment strategy; based on the rule adjustment strategy, updating a preset data mapping rule in real time to obtain an updated data mapping rule; according to the updated data mapping rule, correspondingly filling the extracted time sequence features into a plurality of pre-constructed simulation modules; and based on the time sequence determined by the time sequence characteristics of the simulation modules, running the pre-configured simulation modules corresponding to the distributed computing nodes on the distributed computing nodes of the pre-constructed distributed computing framework so as to simulate the production state of the flexible brushless motor production line in real time and realize digital twinning of the flexible brushless motor production line.

The invention relates to the technical field of traffic control, and discloses an expressway traffic prediction method and system based on a cloud side end, and the method comprises the steps: configuring data collection equipment of an expressway, and constructing a whole-region road sensing network of the expressway; configuring edge computing nodes of the expressway at the key hub, and obtaining a lightweight data packet of the expressway; according to the lightweight data packet, cloud storage data of the expressway is generated, and a traffic mode of the expressway is analyzed; identifying a traffic flow change trend and an abnormal traffic condition of the expressway, and setting an abnormity self-service processing mechanism and an intelligent auxiliary system of the expressway; defining a traffic management mode and a user interaction mechanism of the expressway, and generating a data sharing platform of the expressway; and in combination with the whole-region road sensing network, the traffic flow change trend and the data sharing platform, traffic prediction processing of the expressway is executed, and a prediction processing result is obtained. According to the invention, the prediction efficiency and accuracy of the expressway traffic prediction system can be improved.

The invention discloses a three-phase intelligent electric energy meter and an intelligent metering system thereof, relates to the technical field of three-phase electric energy meter metering, and aims to solve the technical problem that a large error exists in a measured value of a traditional three-phase electric energy meter metering system, and the three-phase intelligent electric energy meter comprises an electric energy metering unit which is used for collecting and metering three-phase voltage and three-phase current, a corresponding three-phase pulse digital quantity signal is generated; the processor module is connected with the electric energy metering unit and is used for receiving the three-phase pulse digital quantity signal and calculating to obtain voltage and current measurement values of each phase; the metering module is connected with the processor module, and is used for receiving the voltage and current measurement values, processing single-phase, two-phase and three-phase imbalance conditions, calculating an active electric energy metering value and a reactive electric energy metering value, and generating digital quantity signals of the active electric energy and the reactive electric energy; and the signal acquisition module is connected with the metering module and is used for acquiring digital quantity signals of the active electric energy and the reactive electric energy. The method has the advantage of improving the electric energy metering precision.

The invention provides a single cell sequencing data autonomous analysis method and system based on a large language model. The method comprises the steps that S1, the large language model, task description and single cell sequencing data are initialized; s2, constructing a planner based on a large language model, and analyzing and decomposing tasks according to the task description; s3, constructing an actuator based on the large language model, and retrieving and acquiring a tool document; step S4, based on the tool document, generating a code solution for the subtask; s5, executing the code solution in the code sandbox; s6, constructing an evaluator based on the large language model, and evaluating the code solution and the execution result thereof; and S7, returning and repeatedly executing the steps S3 to S6 until the execution is finished. Effective cooperative work among the planner, the actuator and the evaluator can be realized, full-process automation and high-quality single cell sequencing data analysis aiming at natural language input are realized, and the labor cost is reduced.

The invention relates to the technical field of hot stamping, in particular to a hot stamping forming steel plate high-temperature stamping forming table and a control method thereof.The hot stamping forming steel plate high-temperature stamping forming table comprises a bottom frame, an upper stamping die and a lower stamping die, and stamping grooves are formed in the upper end and the lower end of the lower stamping die; a lower stamping die is installed in the support base through a connecting piece and a second fixing shaft, an upper stamping die is arranged at the upper end of the lower stamping die, the upper end of the upper stamping die is fixedly connected with the moving end of the hydraulic push rod through a bolt, positioning mechanisms are arranged on the two sides of the lower stamping die, and a driving mechanism is arranged on one side of each positioning mechanism. According to the double-sided stamping lower die, after stamping is completed once, the double-sided stamping lower die can be turned over, then automatic discharging can be achieved, meanwhile, the cooling duration of the stamping lower die in the continuous stamping process can be prolonged, and the situation that due to overheating of the stamping lower die, the double-sided stamping lower die cannot be cooled easily can be effectively reduced. And the service life is influenced due to aggravated abrasion.

The invention relates to an electric mine truck driving control system and method, in particular to a large-tonnage electric wheel mine truck driving control system and method, and solves the technical problems that the import purchase price of an existing high-power diesel engine is high, electric energy emitted by a mine truck is difficult to store, and a large amount of energy is wasted and the environment is polluted. The driving control system for the large-tonnage electric wheel mine truck comprises a driving unit and an electrical unit, the driving unit comprises two driving mechanisms connected with mine truck hubs on the left side and the right side correspondingly. Each driving mechanism comprises a driving module, a speed reduction module and two driving inverters. The electrical unit comprises a whole vehicle VCU, a power generation module, a battery module, a generator inverter and a PDU power distribution module. According to the driving control method for the large-tonnage electric wheel mine truck, the whole truck can independently use the power generation module to output a power supply, can also independently adopt the battery module to normally drive, and can also adopt the power generation module and the battery module at the same time, so that high efficiency, intelligence and environmental protection are brought into full play.

The utility model discloses a hydraulic multifunctional valve box for deep sea, and belongs to the technical field of valve boxes for deep sea. Comprising a valve box body, a valve box cover plate, a plurality of hydraulic valve groups, a throttle valve group and a control circuit, the valve box body is provided with at least one assembling face used for installation. An oil inlet end and an oil return end are arranged on the valve box body; the valve box cover plate is detachably connected to the valve box body; the valve box cover plate covers the assembling face, and a cavity is formed between the valve box cover plate and the assembling face. The hydraulic valve sets are arranged on the assembling face in an array mode and located in the cavity. The throttle valve group is arranged on the valve box body and is arranged on the assembling surface; and the control circuit is arranged in the cavity. The valve box body is detachably connected with the valve box cover plate, a plurality of functional hydraulic valves are integrated on one valve box, and cooperative work among the hydraulic valves is achieved through an internal pipeline and a control circuit.

The invention relates to the technical field of enterprise assessment, and discloses an enterprise financial health degree assessment method based on big data, comprising the following steps: step 1, establishing a dynamic model, and adding a data collection module, a data preprocessing module, a data assessment analysis module, an assessment risk identification module and an assessment risk response module in the model; 2, collecting various data related to the enterprise in a data collection module, wherein the data comprises but is not limited to financial data, market data, industry data and macroeconomic data; 3, cleaning the collected data in a data preprocessing module, removing wrong, repeated or incomplete data, and carrying out data standardization and normalization operation on the cleaned data; step 4, calculating the preprocessed data in a data evaluation and analysis module; step 5, performing risk identification on a calculation result in an evaluation risk identification module; and step 6, formulating a corresponding risk coping strategy for the risk factors influencing the financial health degree of the enterprise.

The invention provides a learning recommendation method and system based on a cluster model, a terminal and a storage medium, and the method comprises the steps: obtaining an evaluation data set of a target student, the evaluation data set comprising learning behavior data, score data and character data; according to data types existing in the evaluation data set, feature extraction is conducted on corresponding data in the evaluation data set through corresponding feature extraction models, corresponding feature vectors are obtained, and the data types comprise a video data type, a text data type and a time series data type; performing feature fusion on each feature vector to obtain a fused feature vector; and inputting the fusion feature vector into a preset hybrid model, so that the hybrid model evaluates the learning ability of the target student according to the fusion feature vector to obtain an evaluation result, and generating a learning path corresponding to the target student according to the evaluation result, thereby improving the accuracy and flexibility of personalized learning recommendation.

The invention discloses an operation tunnel disease case library construction and rapid retrieval method and system, and the method and system achieve the efficient collection, arrangement, storage and retrieval of operation tunnel disease cases through employing an advanced data processing method and a knowledge graph construction and retrieval technology. Data mining and ontology modeling technologies are utilized to carry out deep processing and classification on collected data, an operation tunnel disease case library based on a knowledge graph is constructed, intelligent retrieval of disease knowledge is realized in combination with an NLP natural language processing technology, and powerful technical support is provided for diagnosis, processing and prevention of operation tunnel diseases.

The invention discloses a router EasyMesh fast networking method and system, and the method comprises the steps: obtaining the equipment information and connection relation of an EasyMesh router through a network topology discovery protocol, and generating a global network topology view. And according to the global network topology view, performing comprehensive scoring on each router by adopting a multi-dimensional index to obtain an equipment capability score of each router. And performing a link quality test on links between the routers in the global network topology view to generate a link quality test result. And taking the global network topology view, the equipment capability score and the link quality test result as input, and calculating an optimal role scheme of each router through a role decision algorithm. Therefore, the router role can be quickly determined through an automatic process, the networking efficiency is optimized, the network compatibility and safety are improved, and management and maintenance are simplified.

The present invention discloses an industrial automatic control data processing system and method based on digital twin, which belongs to the field of industrial automation control technology. The present invention establishes a connection between the edge side and the cloud center through the edge side management module, automatically collects industrial data through the edge collection node, and stores the collected industrial data in the edge device; sends a data request to the cloud center through the data mapping module, and the cloud center receives the industrial data uploaded by the edge side and maps the received industrial data in the digital space based on the digital twin technology; analyzes and feedbacks the data collection status of the edge side through the cloud processing module; updates the data collection strategy of the edge side according to the analysis results fed back by the cloud center through the collaborative control module, and transmits the updated data collection strategy to the edge device, and adjusts the data collection business of the edge collection node. The data in the industrial production process is processed more flexibly, which reduces the resource consumption of operation and maintenance.

The invention relates to the technical field of asset management, discloses a specific model construction method and system based on an asset digital intelligent management platform, and aims at solving the problems that a traditional asset management mode is low in efficiency, inaccurate in prediction, incomplete in evaluation, not intelligent in decision making and the like. The method comprises the step of constructing an asset performance prediction model, an asset health degree evaluation model and an asset management decision model. The performance prediction model predicts future performance indexes based on asset configuration and environmental condition data; the health degree evaluation model comprehensively considers multiple factors to evaluate the current health state of the assets; the management decision model models a management process into a Markov decision process, and optimizes decision actions through a deep reinforcement learning algorithm. According to the system, effective integration and cooperative work of the models are realized, the intelligent level and decision-making efficiency of asset management are improved, and a brand-new and intelligent solution is provided for asset management.

The invention discloses a hydropower station unmanned aerial vehicle security construction method and system, and relates to the technical field of unmanned aerial vehicle intelligent security, and the method comprises the steps: automatically setting an inspection path based on an unmanned aerial vehicle cloud computing platform; deploying ground camera monitoring equipment, and performing identification based on a first technology; and transmitting the monitoring data in real time through the first communication mode. According to the method, automatic planning and dynamic adjustment of a task path are realized through routing inspection path setting based on an unmanned aerial vehicle cloud computing platform, the capability of all-weather real-time monitoring is realized through deployment of multifunctional ground camera monitoring equipment, cooperative work of the unmanned aerial vehicle and a ground system is realized by adopting a linkage mechanism, and the unmanned aerial vehicle and the ground system are integrated. Through the first communication mode, the real-time data transmission between the unmanned aerial vehicle and the ground equipment is ensured, the signal coverage capability is enhanced by adopting the multi-point relay device, the problem of communication blind areas in a complex terrain environment is effectively solved, the signal intensity is monitored in real time, the transmission path is dynamically adjusted, and the communication stability is further ensured.

The invention relates to the technical field of hydraulic machines, in particular to a primary-secondary cylinder hydraulic machine and a control method. The two sub-cylinders are mounted on the movable beams on the two sides respectively and share the same hydraulic control system with the main cylinder; the hydraulic control system is used for controlling the actions of the main cylinder and the sub-cylinder; the electromagnetic valve is used for controlling the pressurizing action of the sub-cylinder, and when the main cylinder is downwards pressed to a designated position, the sub-cylinder is pressurized; the hydraulic control system can simultaneously or independently adjust the pressing pressure of the main cylinder and the sub-cylinder; and the movable beam is fixedly connected with the upper cross beam and the lower cross beam through bolts.

The present invention belongs to the technical field of lens assembly, and discloses a lens assembly device, including a frame, a component feeding device and a component assembly device, wherein the component assembly device includes a mounting seat, a shaping mechanism and a suction mechanism, wherein the shaping mechanism is located downstream of the component feeding device, the suction mechanism is located downstream of the shaping mechanism along a first direction, the mounting seat is located downstream of the suction mechanism along a second direction, and the suction mechanism is slidably arranged on the frame along the first direction and the second direction. The mounting seat can fix the lens frame, the shaping mechanism can shape the components provided by the component feeding device, the suction mechanism can move along the first direction to absorb the components on the shaping mechanism, and then move along the second direction to assemble the components onto the lens frame of the mounting seat, at which time, the component feeding device and the shaping mechanism synchronously repeat the feeding and shaping processes, and the component feeding device, the shaping mechanism and the suction mechanism are separately arranged, which can realize collaborative work, thereby improving production efficiency.

The utility model belongs to circuit board technical field especially is a kind of multilayer formula interlaced circuit board, including first circuit board and second circuit board, the below of first circuit board is provided with second circuit board, the top of first circuit board is fixedly connected with electronic component, the top of first circuit board is respectively provided with mounting hole around, the right side top of first circuit board is fixedly connected with power interface, the front and back of first circuit board is respectively provided with conducting wire belt, the front and back top of first circuit board is respectively provided with electricity connection hole, the top of first circuit board is provided with isolation component around.The utility model passes through first circuit board, second circuit board, power interface, electronic component, guide tape, electricity connection hole, realizes the two-way communication and collaborative work between two circuit boards, and can prevent electronic component from being damaged or circuit connection unstable due to external force shaking.

The invention belongs to the technical field of coal rock mechanical property testing, particularly relates to a mechanical testing device and method for coal rock loading, and solves the problems that an existing device is single in function, fragments splash, cleaning is inconvenient, and protection and cleaning are not linked. The device comprises a supporting mechanism, and a modular loading mechanism is detachably mounted on the supporting mechanism and comprises a static extrusion loading module and a dynamic impact loading module; the linkage type protection mechanism is provided with two protection half barrels, and fragments can be prevented from splashing when the two protection half barrels are closed; the sweeping mechanism is started when the protective half barrels are unfolded, a rotating ring drives a Z-shaped plate to rotate, an annular inclined panel is driven to vibrate, and fragments are swept; the device integrates a static extrusion function and a dynamic impact function, so that the equipment utilization rate and the application range are improved; protection and cleaning are linked, safety is guaranteed, cross contamination is avoided, and the experiment accuracy and efficiency are improved.

The utility model discloses an improved ladle cover of a steel ladle roaster, which comprises a ladle cover assembly, a first cover plate and a second cover plate, the ladle cover assembly is mounted on the steel ladle roaster, and the steel ladle roaster can seal and bake tilting steel ladles and plug rod bottom pouring steel ladles by replacing the first cover plate and the second cover plate. The steel ladle roaster comprises a base, a rotary lifting device, a supporting arm and a roasting temperature control device, a burner is arranged at one end of the upper portion of the supporting arm, an air blower, a gas pressure control device and counterweight iron are arranged at the other end of the upper portion of the supporting arm, the rotary lifting device is connected between the base and the supporting arm, and the gas pressure control device comprises a burner, an ignition gun, a gas pipe and an air pipe. The upper portion of the burner is communicated with a burning torch and a gas pipe, and the side face of the burner is communicated with an air pipe and an air blower. According to the improved ladle cover of the steel ladle roaster, the steel ladle roasting efficiency and quality are improved, and the improved ladle cover has the advantages of being high in production efficiency, safety and reliability.

The present invention relates to the field of data access technology, and in particular to a data access system, method, and program product for a heterogeneous multi-core processor. The present invention provides a data access system for a heterogeneous multi-core processor, comprising: a heterogeneous multi-core processor, a target storage block, and a register module. The present invention introduces a register module comprising a counting unit, a register unit, and a lock status unit, which provides a hardware basis for the heterogeneous multi-core processor to access the target storage block, and can support the rapid response and atomicity of the lock operation. The present invention takes into account the possible data competition and data dependency of the processing core, and by assigning a line program number to the processing core and designing management logic in combination with the register module, it can effectively adapt to data competition and data dependency, avoid unnecessary time consumption, and ensure that the processing core efficiently completes data access.

The invention relates to the technical field of medical instruments, in particular to a piezoelectric driving miniature optical probe for cerebrovascular interventional imaging, which comprises a glass tube base body, a single piezoelectric ceramic piece and the like, and is characterized in that the glass tube base body is of a hollow cylindrical structure, and an inclined groove is formed in the axial center of the glass tube base body; the single piezoelectric ceramic piece is fixed on the outer side of the glass tube base body. Through a hollow rod type stator structure composed of a single piezoelectric ceramic piece and a glass tube base body with a 10-degree inclined groove, mode conversion from longitudinal vibration to longitudinal-torsional coupling vibration is achieved, an elliptical motion track is formed at the position of a miniature magnetic ring at the front end of the stator, 360-degree optical scanning is achieved through friction driving of a rotor, and the mechanical property of the motor is improved. Compared with a traditional far-end miniature probe with the diameter usually larger than 1.5 mm, the whole outer diameter of the probe is reduced to 0.4 mm, and smooth navigation and passing in tortuous and narrow brain middle artery (the diameter is usually smaller than 0.5 mm) are easier.

The invention discloses an intelligent vibrating wire sensor measurement method with self-identification of serial numbers and temperature compensation, and relates to the technical field of intelligent sensor measurement, and the method comprises the specific steps: configuring various modules for intelligent vibrating wire sensor nodes, and distributing unique serial numbers; after the nodes are started, a dynamic micro-cluster is established; selecting a main node in the micro cluster to construct a local three-dimensional temperature field model and synchronizing; performing temperature data error correction by each node according to the data; and finally, outputting the corrected temperature measurement data marked by the self-identification number by each node, and determining the data affiliation node. According to the invention, unique numbers are distributed for nodes to solve data affiliation chaos; dynamically building a micro cluster and electing a main node to guarantee stable operation; a local three-dimensional temperature field model is built based on the cluster, and the traditional limitation is broken; error types are accurately distinguished and differentiated compensation is carried out, comprehensive correction is carried out in combination with multiple calibration parameters, data additional check codes are output, and transmission completeness is ensured.