920results about How to "Achieve standardization" patented technology

The invention discloses a building measurement method and system based on three-dimensional scanning, a medium and a product, and relates to the field of exploration, and the method comprises the steps: obtaining BIM model data and a measurement parameter threshold value of a target building, and determining a subarea scanning path according to the BIM model data; scanning the target building according to the subarea scanning path to obtain a point cloud data set of the target building; generating a three-dimensional digital model of the target building according to the point cloud data set, and dividing the three-dimensional digital model into a plurality of feature regions; each feature region comprises at least one feature component; extracting a feature point set in the feature region, and establishing a mapping relationship with a corresponding point set of a corresponding region in the BIM model data; calculating actual measurement parameters of the feature region based on the mapping relation; and comparing the actual measurement parameter with the measurement parameter threshold, determining an abnormal area and generating a measurement technical report. By implementing the method, the building data can be more comprehensively acquired, and the precision of building measurement is improved.

The invention discloses a power grid data management system and method based on artificial intelligence data analysis in the technical field of power grid anomaly detection. The method comprises the steps of obtaining operation data of nodes in a power grid system; calculating an exception comprehensive score of the node based on the operation data by combining an exception detection model deployed by edge computing equipment; determining an abnormal response level of the node based on the abnormal comprehensive score; and triggering a corresponding response strategy based on the exception response level of the node, and performing exception processing on the node. According to the method, the lightweight anomaly detection model is deployed on the edge computing equipment, the power grid operation data is monitored in real time, the abnormal condition is quickly identified, the reliability and safety of power grid operation are improved, and the problems of response delay, network bandwidth limitation, single-point fault and the like of a traditional centralized anomaly detection system are solved.

The invention discloses a text robot application system based on a large model, and the system comprises the following modules: a knowledge base and analysis module which receives and processes a business document, decomposes the content into semantic units, and marks context features; the question-answer generation module automatically generates question-answer pairs through deep semantic analysis and stores the question-answer pairs in a vector database; the question extension module is used for dynamically extending similar questions by using a natural language generation technology; the semantic intention analysis module is used for accurately extracting a problem core intention through context semantic analysis and mapping the problem core intention to a service path; the text workflow management module is used for realizing dynamic routing of multiple service scenes by adopting a logic tree model; the context semantic association module is used for analyzing and optimizing problem expression through multiple rounds of dialogues; the bottom response module is used for providing multi-level answers in combination with a question and answer database, document recall and dynamic generation; and the intelligent learning module records unsolved problems and optimizes the question and answer library and semantic rules through a learning algorithm.

The invention provides an integrated metadata management method and system based on data source expandability, and relates to the technical field of data sources, and the method comprises the steps: executing real-time detection on a plurality of heterogeneous data sources through a PF4J plug-in framework, collecting connection information, and establishing a dynamic connection pool; obtaining a table structure, a field attribute and an association relationship list, and assembling the table structure, the field attribute and the association relationship list into JSON format data; performing analysis and standardization processing on the data, and constructing an association degree calculation matrix; generating a standardized data structure description file; establishing a three-layer index directory, and detecting structure change and updating; and calculating a data table reference dependency relationship, and generating a DAG data flow path. According to the method, efficient integration and management of heterogeneous data sources are realized, and the metadata processing efficiency is improved.

The invention provides a business process construction method combining a workflow engine and a dynamic form, which relates to the technical field of low-code platforms, and comprises the following steps of: establishing a data table according to a business, selecting and importing the data table in a code generation module, generating a basic code package, re-operating a main program compiling code package and loading the code package to a JVM (Java Virtual Machine) operating environment; creating a dynamic form on the basis of the entity class information of the code package through a visual form designer of the dynamic form module, and outputting dynamic form configuration in a JSON (JavaScript Object Notation) format; according to the method, the dynamic form and the process engine are combined, highly flexible business process design can be realized, a user can dynamically design the form and the process model as required to meet different business requirements, and the user-defined component can be designed according to a business data structure and common functions, so that the form can better adapt to a specific business scene, and the user experience is improved. And the user experience and the working efficiency are improved.

The invention relates to the technical field of tea leaf detection, and discloses a tea leaf quality grade detection method and system.The method comprises the steps that a tea leaf sample is collected and pretreated; extracting chemical component indexes and physical properties of the pretreated tea leaves, and performing fusion and analysis; and establishing a tea quality grade classification model, inputting characteristics of a tea sample to be detected, outputting a detection result, and generating a tea quality grade report. Through combination of the support vector machine, the gradient boosting decision tree and the improved logistic regression algorithm, the precision of the tea quality classification model is optimized. The dynamic threshold function and the segmented excitation function are introduced to further solve the boundary fuzzy problem of the high-grade tea leaves and the low-grade tea leaves, and accurate judgment of tea leaf grade classification is achieved. And data restoration is carried out through weighted compensation correction and a recheck process, so that the output tea grade report is ensured to have high accuracy and reliability.

The invention relates to the technical field of data analysis, and discloses a data analysis method based on a chain operation benefit supervision system, and the method comprises the steps: carrying out the collection and preprocessing of the multi-dimensional data of each store of a chain operation enterprise, and obtaining the multi-dimensional time series data; performing multi-dimensional similarity calculation and fuzzy clustering to obtain a store clustering result and a fuzzy membership degree; constructing a decision tree model and performing store operation state evaluation to obtain a store operation state evaluation result; time sequence feature extraction is carried out, a semantic segmentation network is constructed, and a store business prediction model is obtained; performing deep prediction on the multi-store business data to obtain a store business prediction result; and based on the store operation state evaluation result, the store business prediction result and the fuzzy membership degree, comprehensive anomaly prediction and resource optimization configuration are carried out to obtain an anomaly prediction report and an optimization scheme, so that the accuracy of operation state evaluation is improved.

The invention belongs to the field of remote virtual rehabilitation training, and particularly relates to a remote rehabilitation management method and system based on virtual reality. The method comprises the steps that firstly, the current health condition, the expected rehabilitation target and the needed period of a rehabilitation patient are predicted through a comprehensive evaluation algorithm and machine learning, secondly, a personalized training plan is intelligently recommended from a virtual rehabilitation training strategy library according to an evaluation result, and in the training implementation process, a sensor continuously monitors physiological indexes and micro-expression response of the rehabilitation patient; the rehabilitation progress is analyzed and evaluated through real-time data and fed back to a training strategy library in time, the training intensity and period are dynamically adjusted, and it is ensured that training is closely matched with the actual health state of a rehabilitative person; by fusing electronic medical record processing, virtual reality technology, machine learning prediction and visual emotion recognition, precise and intelligent management of rehabilitation training is realized, and rehabilitation efficiency and experience are remarkably improved.

The invention relates to the technical field of data processing, in particular to an automatic rule configuration process processing method, system and device and a medium, and the method specifically comprises the following steps: obtaining first delivery rule data, and carrying out semantic analysis and structured extraction on the first delivery rule data to form second delivery rule data; establishing a standard index library, and performing index systematic construction on the second putting rule data according to the standard index library to generate a multi-way tree rule; performing automatic verification on the multi-way tree rule according to a rule verification tool, determining whether the multi-way tree rule is reasonable or not, and if the multi-way tree rule is not reasonable, optimizing the multi-way tree rule; and obtaining historical advertisement putting data, and performing an advertisement putting scene simulation test on the multi-way tree rule according to the historical advertisement putting data. According to the invention, through generation, optimization and application of the multi-way tree rule, intelligent configuration, management and optimization of the advertisement putting rule are realized.

The invention discloses a code printing quality control method and system of a laser vision code printing machine, relates to the technical field of code printing quality control, and aims to solve the problem that the laser vision code printing machine cannot perform code printing optimization according to a code printing process. According to the method, abnormal identification is carried out on the unqualified quality indexes in the code printing monitoring data, specific problems such as laser parameter abnormity, equipment faults and hardware problems can be accurately identified, the accuracy enables subsequent improvement measures to solve the problems in a more targeted manner, and the accuracy of code printing quality detection is improved by formulating clear code printing quality detection standards and targets. According to the method, the standardization and consistency of quality detection work are ensured, the division standard of quality evaluation is clarified, the quality evaluation result is more objective and accurate, the coding efficiency is improved by designing a reasonable path type, a starting point, an ending point and a path sequence, the accuracy and no intersection or overlapping of a coding path are ensured through the path simulation step, and the coding efficiency is improved. And repeated coding and waste are avoided.

The invention discloses an intelligent drive-by-wire chassis comprehensive control platform, and belongs to the technical field of automobile chassis control. An intelligent drive-by-wire chassis comprehensive control platform is divided into an information interaction processing layer, a state information estimation layer, a control mode management layer, a comprehensive motion control layer and a drive-by-wire execution layer, so that the drive-by-wire chassis can generalize more intelligent capabilities; comprising environment information cognitive ability, chassis fault pre-judgment ability, real-time information interaction ability, vehicle stability autonomous control ability, minimum risk state automatic control ability and failure state autonomous adjustment ability. The chassis health state assessment is used for acquiring the execution capability and the comprehensive health degree of chassis components in real time, carrying out fault definition and division based on the information, and ensuring the implementation or degradation control of an expected target through failure reconstruction control; the minimum risk control module serves as a minimum intelligent driving backup, and it is guaranteed that after an intelligent driving system fails or exceeds a design operation domain, the vehicle can achieve basic decision making, planning and control for guaranteeing safety of the vehicle.

The invention relates to the field of constructional engineering, and discloses an assembly type reinforced concrete-steel structure foundation pit supporting system convenient to disassemble and a construction technology, and the assembly type reinforced concrete-steel structure foundation pit supporting system comprises a top beam, a waist beam, a supporting pile and an inner supporting system; the inner supporting system is formed by assembling a standard steel-concrete beam section main support and a steel member auxiliary support in cooperation with a jack adjusting system. The invention further provides a new system on-site assembly construction process, namely detailed steps of assembly construction from the uppermost layer to the lower layer step by step. The fabricated structure integrates the advantages of two fabricated structures, is suitable for foundation pit supporting with large stress and strict deformation control, and has the advantages of being high in construction speed, short in construction period, low in construction cost, convenient to dismantle and capable of completely recycling most of inner supporting components compared with a traditional cast-in-place steel-concrete foundation pit supporting system.

The invention discloses a CTC cell detection method based on a micro-fluidic chip, and belongs to the technical field of cell treatment. In order to solve the problems of high false positive and false negative rates, time consumption and low efficiency caused by difficulty in accurately distinguishing CTC from other cell types, the invention can efficiently and specifically capture CTC cells, reduce the possibility of false positive and false negative and improve the detection accuracy by constructing a specific capture chamber and filling specific antibodies and immunomagnetic beads. The multi-channel design allows a plurality of samples to be processed at the same time, the detection efficiency is improved, the micro-fluidic chip technology integrates a plurality of steps on one platform, automation and standardization of operation are achieved, personal errors are reduced, the stability and repeatability of detection are improved, the uniformity and stability of the detection process are ensured, and the detection efficiency is improved. The fluorescence imaging technology clearly displays CTC and obtains key parameters such as quantity, form and fluorescence intensity of CTC, thereby providing powerful support for cancer diagnosis and research.

The invention discloses an electric power project risk prediction method and system based on data mining, and relates to the technical field of electric power project risk prediction.The method comprises the steps that electric power project data are collected, the electric power project data are preprocessed, key features influencing project risks are extracted, and feature vectors are established; constructing an electric power project risk prediction model, and performing risk prediction analysis on the electric power project based on the feature vector; and taking a part of areas with risks as nodes to form a topological graph, identifying key paths and bottlenecks, and formulating corresponding resource allocation strategies. According to the method, the electric power project risk prediction model is constructed based on the feature vectors, risk prediction analysis is carried out on the electric power project in combination with the time change trend, the accuracy and foresight of risk prediction are improved, the topological graph is formed by taking part of areas with risks as nodes, key paths and bottlenecks are identified, and the risk prediction accuracy is improved. And a corresponding resource allocation strategy is formulated, so that the security and the stability of the project are improved.

The invention discloses an active learning-based electric power knowledge graph construction method and system, and relates to the technical field of electric power market transaction data analysis, and the method comprises the steps: collecting data, cleaning the collected data, generating word prediction task data of an electric power transaction scene, and training an electric power field word embedding model; generating an entity relationship training sample, inputting a word embedding model, performing entity relationship label prediction through an entity relationship joint extraction model, extracting a high-quality sample based on active learning to perform part-of-speech tagging, and training the model based on a tagged sample; and applying the trained entity relationship joint extraction model to power transaction data to construct a knowledge graph, performing manual correction and entity unification, and storing the knowledge graph into a Neo4j database. According to the method, active learning and deep learning are combined, so that the sample labeling cost is effectively reduced, and meanwhile, the model performance is ensured.

The invention provides a spliced frame structure for a flat plate type satellite, and belongs to the technical field of satellite structures. The problems that an existing satellite frame is high in production cost and difficult to produce in batches are solved. The beam unit comprises an X-axis beam unit, a Y-axis beam unit and an inclined beam unit, the X-axis beam unit and the Y-axis beam unit are arranged in an orthogonal mode, an included angle is formed between the inclined beam unit and the X-axis beam unit, the X-axis beam unit comprises a first X-axis beam, a second X-axis beam, a third X-axis beam and a fourth X-axis beam, and the X-axis beam unit comprises a first X-axis beam, a second X-axis beam, a third X-axis beam and a fourth X-axis beam. The Y-axis beam unit comprises a first Y-axis beam, a second Y-axis beam and a third Y-axis beam, the oblique beam unit comprises a first oblique beam and a second oblique beam, and the splicing unit comprises a Y-axis separation mechanism connector and an X-axis separation mechanism connector. The frame structure is mainly used for a flat plate type satellite.

The thoracolumbar vertebra fixing brace comprises a front chest supporting structure, a back supporting structure, an inflation and deflation device and a control module, the front chest supporting structure and the back supporting structure are connected and define a thoracolumbar vertebra clamping area, a front chest air bag set is arranged on the inner side of the front chest supporting structure, and the front chest air bag set is provided with a front chest pressure detection device; a back air bag set is arranged on the inner side of the back supporting structure and provided with a back pressure detection device. The chest air bag set and the back air bag set are both connected with the inflation and deflation device, and the chest pressure detection device, the back pressure detection device and the inflation and deflation device are all connected with the control module. The front chest air bag set and the back air bag set adjust the pressure value through inflation and deflation actions, the expectation of the pressure value applied to the thoracolumbar vertebra of a patient by a doctor can be achieved, standardization and scientization of the wearing and fixing tightness degree of the thoracolumbar vertebra fixing brace are facilitated, and the comfort degree of the patient is improved.

The invention discloses a risk control rule effect evaluation method and system based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting structured data and unstructured data in vehicle insurance claim settlement, and carrying out the preprocessing; analyzing the processed unstructured data by using a deep learning technology, and extracting risk control feature vectors; based on the processed structured data and unstructured data, constructing a claim settlement relation graph; constructing a graph neural network model by using the risk control feature vector and the claim relation graph; setting a new risk control rule based on the output of the graph neural network model; evaluating the effect of the new risk control rule through the risk control rule test, and generating a new risk control rule effect evaluation report; according to the method, deep learning and graph neural network technologies are combined, multi-source data of car insurance claim settlement are comprehensively analyzed, the identification accuracy and efficiency of fraudulent behaviors are improved, the economic loss of insurance companies is reduced, and the user experience and service quality are remarkably improved.

The invention belongs to the technical field of airborne radio frequency equipment testing, and particularly relates to a comprehensive simulation test system and method for airborne radio frequency equipment, and the system comprises a man-machine interaction unit, a comprehensive radio frequency rack unit, a power supply and control unit, and a cabinet matching test cable. Broadband radio frequency signal processing, waveform modulation and demodulation, audio analysis processing and data storage and recording of each airborne radio frequency device are realized through the integrated radio frequency rack unit; and signal processing and channel switching functions are realized through the intermediate frequency switching matrix module and the broadband radio frequency front-end processing module, so that different to-be-tested systems and radio frequency signals can be matched. According to the invention, a software radio technology is adopted, a software dynamic loading reconstruction scheme is adopted on a general radio frequency hardware platform to realize soft switching among different task functions of the airborne radio frequency equipment, a comprehensive simulation test on the complex airborne radio frequency equipment is realized, and the utilization rate of test resources is improved.

The invention relates to the technical field of data processing, and discloses an intelligent agent evaluation method and system, and the method comprises the steps: analyzing key factors and performance indexes of an intelligent agent in different combat environments, determining evaluation indexes, and constructing an evaluation index system; setting parameters and algorithms of the evaluation model, and configuring an association relationship between the evaluation model and the evaluation index system; gaming deduction data and agent decision data are collected, and evaluation calculation data are generated and stored; in response to the evaluation calculation data, configuring evaluation calculation parameters, calling the evaluation model to calculate the evaluation calculation data, and recording an evaluation calculation result; and in response to the evaluation calculation result, generating an evaluation report framework, integrating the evaluation calculation data and the corresponding evaluation calculation result into the evaluation report framework in a visual form, and outputting an evaluation report. According to the invention, standardization and systematization of the evaluation process are realized, scientificity and accuracy of evaluation are improved, and efficiency and accuracy of data processing are improved.

The invention discloses a heat transfer simulation method for a material freezing process, which comprises the following steps: step 1, according to each physical property parameter of a material before freezing, obtaining a liquid phase volume fraction VL of the material before freezing, a volume fraction VSL of a porous matrix before freezing of the material, an effective physical property parameter of a liquid phase before freezing of the material and an effective physical property parameter of the porous matrix before freezing of the material; step 2, obtaining the volume fraction VF of a frozen phase of the frozen material, the volume fraction VSF of a porous matrix of the frozen material, the effective physical property parameters of the frozen phase of the frozen material and the effective physical property parameters of the porous matrix of the frozen material according to the physical property parameters of the frozen material; and step 3, constructing a heat transfer model of the material freezing process according to the parameters in the step 1 and the step 2. According to the method, the temperature, phase change, freezing end point and the like in the freezing process can be accurately predicted, and standardization of freeze drying production of materials (especially agricultural products) is achieved.

An astronavigation material database system belongs to the technical field of astronavigation material databases and comprises a basic platform layer, an application service layer and a presentation layer. The public service layer comprises a public service plate; the application function layer comprises but is not limited to a material management plate, a material data application plate and a material big data analysis plate. The invention discloses an astronavigation material data system, which comprises a word standard specification, establishes an astronavigation material database, can perform big data analysis according to a computer software technology, a network technology and a digital technology, and can realize intelligent recommendation and intelligent knowledge management of astronavigation materials.

The utility model discloses a moxibustion fumigation traditional Chinese medicine external treatment device which comprises a display control bin, a radio frequency induction bin and an independently-installed chip medicine cake box which are connected with one another. A radio frequency chip, a radio frequency coil and a temperature-resistant protective cover are installed in the radio frequency induction bin, a heat transfer through hole and a heater are arranged at the bin bottom, and an independent chip medicine cake box is installed at the lower end of the outer bottom. According to the device, information of the chip medicine cake box is read through a radio frequency chip and a coil of the radio frequency induction bin, and parameters such as optimal working time, working temperature and working wavelength of different traditional Chinese medicine external treatment medicines or non-medicine materials such as moxibustion or fumigation are matched; convenience, digitization, intelligentization, safety and standardization of moxibustion fumigation and other hundreds of traditional Chinese medicine external treatment methods can be achieved.

The invention relates to the technical field of block chains, and discloses a block chain-based clinical data statistical management analysis method, which comprises the following steps of S1, collecting clinical data through sources of hospitals, clinics and patient equipment, and classifying the clinical data according to the sensitivity, frequent accessibility and size of the data by utilizing a hierarchical storage algorithm; s2, dividing the block chain into different data fragments by applying a fragmentation technology, and encrypting the data by using a homomorphic encryption algorithm; and S3, the patient can set the range of accessing the data and the access authority and the access duration through the smart contract. By combining a hierarchical storage algorithm, a homomorphic encryption technology and a revocable anonymity technology, sensitive clinical data can be effectively protected, the security and privacy of the data in the transmission and storage process are ensured, meanwhile, a patient can finely control the access authority of the data through an intelligent contract, part of the data can be safely disclosed, and the security of the patient is improved. And the privacy protection of the data is further improved.

The invention relates to the technical field of printing, in particular to a printing process of an anti-puncture flame-retardant label, and the flame-retardant label comprises an anti-puncture base material layer, a flame-retardant layer, a printed pattern layer and an anti-puncture surface layer which are arranged in sequence; the base material layer and the surface layer are attached to the Dupont film through the composite technology, and the firmness and the using effect of the label are improved by means of the anti-puncture performance of the Dupont film. In the printing process, the treatment of the base material layer comprises stretching to ensure the surface flatness, the bonding layer and the adhesive film layer are accurately coated on the base material layer, and the flame-retardant layer is attached on the base material layer, so that the flatness and the structural strength of the base material are effectively improved, and meanwhile, the product is endowed with excellent flame-retardant property; the flame retardant performance and the structural strength are both improved, and a powerful guarantee is provided for product safety.

The invention relates to the technical field of data processing, in particular to an intelligent recommendation system fusing big data and AI, and the system comprises a scheme obtaining module which obtains a plurality of target marketing schemes; the scheme analysis module analyzes a plurality of target marketing schemes to determine a plurality of marketing features; the data acquisition module collects a plurality of historical behavior data of a user; the data analysis module analyzes a plurality of historical behavior data to determine user characteristics; the association determination module analyzes association between the user features and the plurality of marketing features based on the initial association AI model, and determines prediction priorities of the plurality of target marketing schemes based on an association analysis result; a recommendation module constructs a user recommendation page based on the predicted priority, and determines target priorities of a plurality of target marketing schemes based on the real-time behavior data of the user; and the feedback module compares a comparison result of the prediction priority and the target priority to adjust the initial association AI model to obtain a target association AI model. According to the invention, the accuracy of personalized marketing scheme recommendation of the user is improved.

The invention discloses a multi-center inherited metabolic disease information integration platform, and relates to the technical field of medical treatment, according to the multi-center inherited metabolic disease information integration platform, the normalization and availability of data are improved through a data standardization module; data from different centers are integrated into a unified database through the data integration module by utilizing a data fusion technology, redundant data are removed, the problem of heterogeneous data integration is effectively solved, and the integrity and consistency of the data are improved; the privacy protection module avoids data leakage and unauthorized access; through the resource calculation management module, the resource utilization efficiency is effectively improved, and the calculation cost is reduced; and secondly, the storage resources are dynamically adjusted and allocated according to the evaluation result of the storage index Cczs, so that the optimal management of the storage resources is realized, the problems of resource waste and resource insufficiency are avoided, and the efficient operation of the system is ensured.

The invention relates to a liver transplantation post-operation nursing recommendation method and system based on an NNN link system, and the method comprises the steps: carrying out the construction of a knowledge graph based on the related data of a liver transplantation recipient post-operation NNN link, and constructing a corresponding liver transplantation post-operation nursing knowledge graph; and putting the liver transplantation postoperative nursing knowledge graph into clinical application, predicting an NNN nursing decision scheme matched with liver transplantation symptom information according to the liver transplantation symptom information of a clinical liver transplantation recipient, and executing the NNN nursing decision scheme on a patient. According to the method, an auxiliary decision-making system can be generated, medical staff are helped to reasonably set an outcome target for a liver transplantation recipient and formulate targeted nursing measures, the nursing efficiency is improved, and time and energy consumed by medical care decision making are saved. According to the invention, nurses can be guided to accurately identify and determine existing and potential health problems of liver transplantation recipients. Meanwhile, by introducing an NNN link system, systematized, standardized and intelligent management of postoperative care of liver transplantation recipients is realized.

The invention discloses a flight service system based on a knowledge graph and a large model. Comprising an ontology construction module used for predefining related information of a flight service system based on user demands; the data acquisition module is used for acquiring open source data related to the flight service system from multiple channels and performing deduplication and normalization processing on the open source data to obtain standard open source data; the knowledge graph construction module is used for extracting triads from standard open source data based on the related information to obtain a triad set of the knowledge graph; the prompt generation module is used for generating a corresponding target prompt based on a user demand; the large model fine tuning module is used for training a pre-constructed large model based on the target prompt and the triple set to obtain a trained large model; the trained large model is used for generating a result matched with the target task according to an input user prompt and the triple. According to the invention, diversified services can be provided for users.

The invention belongs to the technical field of stator processing, and discloses a stator bar less-glue insulation whole immersion process, which comprises the following steps: S1, early-stage preparation; s2, stator bar pretreatment; s3, binding a less-glue mica tape; s4, dipping treatment; s5, curing treatment; s6, cleaning and detecting; the early-stage preparation comprises material selection and equipment inspection and debugging. According to the method, the excellent performance of an insulating layer is guaranteed from the source through the epoxy resin-based solvent-free impregnating varnish with the accurate proportion, secondly, in the link of binding the mica tape with less glue, the binding tightness and uniformity of the mica tape are guaranteed by accurately setting the speed and tension of a numerical control taping machine, the insulation defect caused by poor binding is effectively avoided, and in addition, the service life of the insulating layer is prolonged. Key technical measures such as pressure impregnation, accurate temperature control and pressure maintaining in the impregnation and curing process further promote sufficient permeation of the impregnating varnish and uniform curing of the insulating layer, and the compactness and the electrical performance of the insulating layer are remarkably improved.