252 results about "Process analysis" patented technology

The invention provides an enterprise process intelligent analysis system based on a large language model. The enterprise process intelligent analysis system comprises a master control scheduling module, a data preprocessing module, a hierarchical analysis module, an insight extraction module, a report generation module and a knowledge retrieval module. The master control scheduling module generates a scheduling plan based on chain thinking reasoning, and dynamically calls each module; the data preprocessing module carries out cleaning and structured conversion on the enterprise event logs and outputs standardized JSON (JavaScript Object Notation) data; the knowledge retrieval module is combined with an RAG technology and a vector database to provide context support for a large language model; the hierarchical analysis module drives a model to execute process discovery and bottleneck identification through a structured cue word template; the insight extraction module converts an analysis result into a commercial insight text containing reasons, influences and suggestions, and has a self-repairing mechanism to guarantee consistency; and the report generation module automatically generates an image-text report. The system can improve the efficiency and accuracy of process analysis.

The invention provides an atmospheric pollution process analysis method, electronic equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the following steps: receiving an atmospheric pollution problem sent by a user, and respectively carrying out vector database retrieval and knowledge graph retrieval based on the atmospheric pollution problem to obtain a first retrieval result and a second retrieval result; wherein the vector database retrieval comprises the following steps: calculating cosine similarity between background information vectors in a vector database and atmospheric pollution problem vectors, and determining multiple pieces of background information of which the cosine similarity accords with a preset threshold value as a first retrieval result; the knowledge graph retrieval comprises the following steps: performing entity recognition and standardization on the atmospheric pollution problem, and generating a target knowledge triple as a second retrieval result; and fusing and inputting the atmospheric pollution problem, the first retrieval result and the second retrieval result into a large language model, and outputting an analysis result of the atmospheric pollution problem. Through the method provided by the invention, the illusion problem of a general large language model in the atmosphere field is relieved.

The invention discloses a device and method for transporting powdery raw materials for hydrogen production, the device comprises a spiral conveying rod, a feeding / discharging assembly and a feeding flow optimization system, and the system works cooperatively through four modules: a material state analysis module for outputting a material state coefficient based on particle breakage rate and moisture content change; the equipment operation state analysis module outputs an equipment state coefficient according to the raw material temperature, the current fluctuation and the vibration amplitude; the transmission dynamic process analysis module is used for generating a rotating speed-density matching coefficient in combination with the material state coefficient, the equipment state coefficient, the temperature rise speed and the filling compactness; and the feeding flow optimization module is used for dynamically adjusting the target feeding flow through a feeding flow optimization model on the basis of the current feeding / discharging flow of the rotating speed-density matching coefficient. Material integrity protection, equipment operation stability improvement and flow self-adaptive control in the powder conveying process are achieved, and the hydrogen production raw material conveying efficiency and reliability are remarkably improved.

The invention discloses a watershed multi-scale water quality target overall regulation and control method, which is characterized in that a regulation and control unit is delimited based on DEM data, a multi-scale spatial analysis framework is constructed through a hydrological topology and watershed nesting relationship, and the coupling process analysis of pollutant discharge, absorption and transportation is realized; deducing a water quality control target of each catchment area step by step through a process coupling reverse algorithm by taking a watershed outlet section water quality assessment target as a reference; dynamically quantifying a balance relation among pollutant discharge, land area system interception and river network system absorption based on a source-sink profit and loss intensity index, and realizing source-sink state diagnosis of different regulation and control units; and finally, generating a basin overall regulation and control scheme by delimiting a pollution emission hot spot area and a weak absorption capacity area and analyzing a regulation and control scene. The method can be widely applied to water environment refined treatment scenes such as river and lake water quality target management and pollution control zoning, and provides scientific basis and technical support for watershed water environment protection and overall restoration.

The invention relates to the technical field of data processing, in particular to a mine slope intelligent early warning method and system based on dynamic threshold optimization and a medium. Comprising the following steps: acquiring a multi-modal heterogeneous data stream from a sensor network, generating a time sequence data matrix, and sending the time sequence data matrix into a parallel data processing model; the first data processing model executes statistical process analysis to generate a first data set; the second data processing model compares the data with the prediction data set to generate a second data set; fusing the data sets, verifying and judging, and generating a slope data record; when the conditions are met, an optimization process is started; and outputting a state list, storing the state list in a graph database, and performing parameter adjustment on the prediction model. According to the system, heterogeneous data streams are analyzed through a parallel data processing and data fusion method, comprehensive state evaluation is generated, data attribution and model closed-loop optimization are started when conditions are met, high-precision recognition of sudden change and gradual change modes in the data streams is achieved, and the diagnosis depth and the self-adaptive capacity of the analysis system are improved.

The embodiment of the invention relates to the field of data processing, and provides a financial institution business process intelligent optimization method and a related device, and the method comprises the steps: obtaining business process node data, business interaction support data and business result feedback data of a to-be-processed financial institution; based on a dynamic condition response mechanism, performing dynamic bottleneck process mining processing according to the business process node data and the business interaction support data to obtain bottleneck process analysis data; performing bottleneck process influence quantification processing according to the bottleneck process analysis data and the service result feedback data to obtain bottleneck process priority data; performing bottleneck process association rule mining processing according to the bottleneck process priority data, the business process node data and the business interaction support data to obtain bottleneck process association relationship data; according to the bottleneck process analysis data, the bottleneck process priority data and the bottleneck process association relationship data, business process optimization processing is carried out, and a more accurate business process optimization strategy can be obtained.

The invention discloses a multi-vortex system space energy evolution process analysis method, belongs to the field of fluid mechanics and aerodynamics, and aims to solve the problem of energy analysis errors caused by integral radius dependence and single-vortex hypothesis limitation in a traditional method. According to the method, a vortex core is positioned through a Liutex method, a vortex to be analyzed is translated to an original point, a pseudo time sequence is generated in combination with evolution direction slices, and a first modal energy distribution and evolution law is extracted through eigen-orthogonal modal decomposition. According to the method, the integral radius does not need to be manually set, the adaptability is high, the vortex global energy space change process can be comprehensively reflected, the method is particularly suitable for energy evolution analysis in complex vortex system scenes such as bird flight and complex aircraft wake flow, a brand new view angle is provided for vortex energy evolution, and the method has certain engineering practical value. The method can be used for quantitative analysis of complex vortex field scenes such as aircraft design, biological bionics and wind energy engineering, and has important engineering application value.

The invention provides a fusion method of ground station monitoring and satellite remote sensing inversion PM2.5 data, and relates to the technical field of PM2.5 pollution prevention and control. Ground station data and satellite remote sensing data are subjected to time matching and space matching and then are fused by using a universal Kriging method to obtain a high-precision and large-area coverage PM2.5 product. The PM2.5 data spatial correlation is considered, so that the fusion result is closer to reality, the calculation complexity is reduced, and meanwhile, the reliability of the fusion result can be judged by giving an error after data fusion. According to the method, the limitations of insufficient spatial consideration and high calculation complexity of a traditional method are made up, and the PM2.5 product can be used for pollution process analysis, climate change and other researches.

The invention discloses a writing process analysis method based on computer vision, which relates to the technical field of handwritten character recognition, and comprises the following steps: carrying out perspective transformation on real-time writing data, obtaining a writing image frame sequence, carrying out motion blur correction and pen point coordinate positioning on the writing image frame sequence by adopting an RAFT (Reversible Addition Fragmentation Transform) optical flow algorithm, and forming a writing track data flow; and performing curvature segmentation on the writing trace data stream to obtain discrete stroke segments, and performing spatial topological correlation and geometric structure mapping on the discrete stroke segments to generate a writing stroke topological graph. Through the RAFT optical flow algorithm and the stroke semantic analysis model, the precision of stroke recognition is improved, and efficient and accurate analysis from dynamic visual input to structured character output is achieved.

The invention discloses a robot-assisted operation error detection method based on cooperative agent reasoning. The method comprises the following steps: constructing a multi-classification operation error system and a clinical informed knowledge base; based on a multi-classification operation error system and a knowledge base, a chain type reasoning prompt base is constructed according to different professional levels and analysis perspectives; for an input operation video clip, by calculating a composite risk score of a technical complexity score and a clinical influence score, allocating error instances of different risk scores to corresponding professional level reasoning paths; and deploying a time analysis agent, a space analysis agent and a process analysis agent for each professional level reasoning path, calling a corresponding chain reasoning prompt by each agent to analyze the operation video clip, and outputting a final error detection result based on an optimization threshold value by weighting and fusing analysis results of each agent. According to the invention, accurate detection of various surgical errors can be realized, and detection efficiency and clinical suitability are considered at the same time.

The invention relates to the technical field of aluminum oxide production, and provides an evaporation station intelligent optimization system based on multivariable coupling regulation, which comprises a DCS (Distributed Control System) lifting module used for optimizing a control strategy and hardware support; the intelligent optimization control module is used for realizing multivariable coupling regulation and control; the data storage and analysis module is used for historical data recording and process analysis; the execution module is used for receiving the control instruction and driving field equipment; the DCS control system lifting module, the intelligent optimization control module and the data storage and analysis module are in bidirectional communication connection in sequence, and the intelligent optimization control module is in unidirectional communication connection with the execution module. Through multivariable coupling regulation and an intelligent algorithm, mother liquor discharging index fluctuation is stabilized, and the operation qualification rate and the alkali circulation efficiency are improved; steam consumption matching is optimized, and energy conservation and consumption reduction are achieved; variable fluctuation chain reaction is reduced, and abnormal response time is shortened; automation of key procedures is promoted, and manual errors are reduced.

The invention provides an engineering investigation surveying and mapping intelligent management method and system based on a geographic feature processing technology. The method comprises the following steps: acquiring building distribution density, ground gradient and underground rock stratum distribution data of a target area, deploying a ground deformation monitoring radar at a selected position based on the building density and the rock stratum data, generating ground deformation data through radar images, and then separating ground subsidence change and original terrain characteristics to form a subsidence map; meanwhile, image reflection characteristics are analyzed to mark dangerous areas. And then integrating the ground gradient, the settlement trend and the rock stratum structure complexity to construct a land bearing evaluation model. The influence weight is further adjusted in combination with engineering requirements, and a bearing force evaluation result is generated after the model is input. Therefore, a scientific three-dimensional development planning scheme is generated, and optimized utilization and risk management and control of land resources are realized. According to the invention, through multi-source data fusion and model calculation, full-process analysis from land deformation monitoring to load bearing evaluation is realized.

The invention discloses a financial analysis agent training method and device, equipment and a storage medium, and relates to the technical field of machine learning, and the method comprises the steps: carrying out the full-process analysis of a financial problem sample, so as to obtain the thinking process of an initial financial analysis agent; displaying the decision tree corresponding to the thinking process by using a target memory, and obtaining feedback information of an industry expert to an intermediate node of the decision tree and a target score of a processing result of the financial problem sample; converting the feedback information and the score into a multi-dimensional reward value, and performing reinforcement learning training on the initial financial analysis agent based on a target reinforcement learning framework and the multi-dimensional reward value; wherein the multi-dimensional reward values comprise reward values corresponding to the thinking logicality and the thinking path of the decision tree respectively. The thinking process is used as a clear component of reinforcement learning, so that the agent can optimize the thinking mode of the agent instead of only optimizing the final output, and the reasoning ability of the trained agent is improved.

The invention discloses a BMS (Battery Management System) fault prediction method and system in the technical field of battery management system testing, which are used for solving the technical problem that random crash is difficult to position and reproduce in BMS operation. According to the method, the electrical, thermodynamic and RTOS task scheduling operation states of a BMS are synchronized in real time by constructing a multi-physics field coupling digital twinborn model, and feature extraction and fault diagnosis are performed based on simulation process parameters. And carrying out accelerated reproduction on the fault in the multi-physics field coupling digital twinborn model, recording a key parameter combination causing the BMS crash, carrying out verification on an actual BMS hardware platform, and positioning a crash reason and a critical condition. According to the method, real-time data acquisition, digital twin simulation and test verification are combined, and full-process analysis from data acquisition to fault reproduction can be completely realized.

The invention provides a carrier rocket ground test system and method supporting visual process configuration. The system mainly comprises: (1) a visual process configuration module, which configures a test process file through a graphical interface; (2) a process analysis and scheduling module for analyzing a process file and converting the process file into a task sequence; the test execution engine module (3) is used for driving bottom hardware and executing a test instruction sequence; (4) the test resource library module is used for storing and managing various information of test elements and various information of test equipment; the execution monitoring and data management module (5) is used for displaying a test execution state in real time and recording whole-process data; according to the method, the test logic and the execution program are separated, and a user can quickly construct, modify and reuse an automatic test process in a graphical mode, so that the test flexibility is greatly improved, and the test adaptability and efficiency are remarkably improved.

The invention discloses a clindamycin phosphate crystallization tracing method and system based on a block chain, and belongs to the technical field of medicine manufacturing process control. The method comprises the following steps: collecting multi-modal data of a crystallization process in real time through a Raman spectrum sensor, an FBRM sensor and other process analysis technology sensors; constructing a dynamic space-time atlas based on the data to characterize a process state; deeply analyzing the map by using a time-space diagram neural network model so as to identify key crystallization events such as nucleation and crystal transformation; the AI oracle machine automatically generates an event certificate containing event details, an original data hash value and a digital signature for the identified CCE; and finally, submitting the certificate as a transaction to a block chain network for uplink evidence storage, and forming a tamper-resistant tracing record. According to the method, the AI and block chain technologies are fused, so that the problem that key microscopic events are lack of credible and non-tampering records in the crystallization process is solved, and a high-fidelity tracing record with cryptographic guarantee is provided for the pharmaceutical production process.

The invention relates to the technical field of business and financial management, in particular to a business and financial fusion analysis decision management system and method based on multi-modal AI, and the method comprises the steps: configuring deep learning and testing according to financial use and formation information, and obtaining a multi-source contact analysis record; according to the multi-source connection analysis record, feature line and non-feature line difference is configured, and a fusion decision result is obtained; according to the fusion decision result, configuring information-driven machine learning and clustering analysis to obtain a decision value decision record; configuring real-time information analysis according to the real-time decision plan to obtain a real-time financial analysis record; configuring flow analysis according to the real-time financial analysis record to obtain a flow decision result; and configuring real-time information flow analysis and personalized management according to a process decision result to obtain a real-time management result. According to the method, the capability of effectively integrating different information sources is achieved, and the real-time decision-making and long-term financial demand evaluation effects are good.

The invention belongs to the field of oil field ground process analysis and evaluation, particularly relates to an onshore oil field green low-carbon level index evaluation method and system and electronic equipment, and aims to solve the problem that an existing evaluation system is incomplete and inaccurate in consideration. The method comprises the following steps: based on production operation of an oil field ground process system, selecting a green and low-carbon level main body evaluation index; based on the subject evaluation indexes, dividing evaluation indexes to which the subject evaluation indexes belong; the subject evaluation index and the affiliated evaluation index are both endowed with weights; calculating a standardized score of each subject evaluation index; calculating a standardized score of each affiliated evaluation index; calculating a comprehensive score of the green low-carbon level of the to-be-evaluated oil field based on the standardized scores of the subject evaluation indexes and the affiliated evaluation indexes and the weights of the subject evaluation indexes and the affiliated evaluation indexes; and performing overall evaluation based on the comprehensive score. The method guides the improvement of the production construction level, promotes the refinement of production management, and provides a quantifiable scientific evaluation method.

The invention relates to a binding material single particle local spatial evolution analysis method, and belongs to the technical field of civil engineering binding material microstructure characterization. The method comprises the following steps: acquiring back scattering (BSE) and characteristic X-ray energy spectrum (EDS) images of a sample; selecting a target gel particle based on the BSE image and intercepting a local area; identifying the reaction edge of the target gel particle; performing equal-width stepped strip division inwards and outwards by taking the reaction boundary as a starting point, and storing the mask; carrying out image operation on adjacent masks to extract strips, and carrying out statistical analysis on gray feature and element feature changes of each strip; according to the method, surrounding phase interference is avoided through local analysis, whole-process analysis is realized by adopting unified image processing software, a programming basis is not needed, the technical threshold is reduced, the operation process is simplified, the uniformity of strip division and the reliability of an analysis result are ensured, and the method is suitable for large-scale popularization and application. And a simple, convenient and effective technical means is provided for revealing the reaction mechanism and quantitative reaction activity of the cementing material.

The invention discloses a real-time quantitative calibration spectrum on-line detection device and a use method thereof, a standard substance with a known concentration is accurately injected into a mixer and is mixed with a reaction liquid on line, and then a spectrum detector obtains spectrum absorption data of the mixed liquid; on the basis of the spectral absorption intensity linear superposition relation between the standard substance and the reaction liquid and the metering relation between the target product and the injected target product, online correction is carried out, and finally the concentration value of the target product is obtained. The online standard sample injection and dynamic online calibration technology is introduced, so that the problems of low quantitative precision, manual sampling lagging and the like in chemical reaction monitoring are solved, and the online standard sample injection and dynamic online calibration technology is particularly suitable for the fields of photochemical synthesis, continuous pharmacy and the like with strict process analysis timeliness requirements.

The invention relates to the technical field of network geographic information systems, and discloses a visual modeling method, system and device for a spatial analysis process and a medium. The method comprises the following steps: constructing a visual component library; in response to a canvas interaction instruction input by a user, performing parameter configuration and component connection based on the visual component library to obtain workflow logic of the canvas; analyzing the workflow logic in real time based on a directed acyclic graph to generate a spatial analysis code and obtain an analysis result of the spatial analysis code; and performing result visualization and export on the analysis result based on the visual component library. According to the method, component dragging, parameter configuration and connection mechanisms suitable for WebGIS spatial analysis are defined, and visual workflow construction is achieved. Based on a directed acyclic graph process analysis algorithm, efficient and executable spatial analysis codes are automatically generated, and dynamic optimization and parallel computing are supported, so that visual modeling and automatic execution of a spatial analysis process are realized.

The invention relates to a trade bill multi-dimensional processing method, device and system, and the method comprises the steps: obtaining a plurality of pieces of trade bill data, and carrying out the intelligent recognition and structural processing, and obtaining bill field information; performing service association integration on the bill field information based on a preset service identifier to generate bill service data; performing multiple verification and analysis on the bill business data to obtain verification information; and performing multi-dimensional trade process analysis according to the verification information and the bill business data, and outputting decision-making auxiliary information. According to the invention, the automatic conversion from the original bill to the decision auxiliary information can be realized, and the transparency, controllability and operation efficiency of the whole trade process are improved.

The application belongs to the technical field of process automatic control, and discloses a self-adaptive cooperative control system and method for food processing and stirring process. The system comprises a multi-dimensional process analysis unit for collecting multi-dimensional parameter data flow in real time, and a cooperative control module. The cooperative control module internally stores a process stage characteristic model database and a cooperative control strategy library, and is configured to process the multi-dimensional parameter data flow in real time, match the model database in combination with the change rate trend, diagnose the current process stage of the material, then call the preset cooperative control strategy corresponding to the stage to cooperatively control the running state of a low-shear main stirring mechanism, a high-shear dispersion emulsification mechanism, a self-adaptive wall scraping mechanism and a temperature control unit. Through active process stage diagnosis and cooperative control, the application realizes self-adaptive optimization of the process, and improves product quality, production efficiency and process stability.

The present invention provides a coal mine production process control system, which relates to the field of process management technology and includes: a data acquisition module for acquiring data of each production process in a mine in real time and outputting initial data; a preprocessing module for preprocessing the initial data to obtain data to be analyzed; a model training module for training a model to be trained selected from a model database in combination with preset data resources, outputting an alternative model, and outputting an alternative model that meets preset performance conditions as an analysis model; a data analysis module for analyzing the data to be analyzed based on the analysis model, outputting process analysis results, and updating parameters and optimizing performance of the analysis model in combination with preset data resources and cloud data. The present invention can monitor the data of each production process in a mine in real time, promptly discover potential risks of each production process, continuously update parameters and optimize performance of the model, and ensure the real-time and accuracy of the process analysis results.

The invention relates to the technical field of food production and process analysis, and discloses a mixing uniformity test system and method for a stirring tank, and the system comprises a space-time light field excitation module which is used for projecting a preset space-time light field to a material in the stirring tank; the high-dimensional light field response capturing module is used for capturing response light generated by the material to the space-time light field and generating response data; the model storage module is used for storing a forward physical model representing the distribution relationship between the response data and the material key component concentration; the inversion calculation module is used for calculating a spatial covariance matrix of the key component concentration distribution based on the response data and a forward physical model; and the index generation and display module is used for generating and outputting a quantitative index representing the mixing uniformity of the material based on the spatial covariance matrix. According to the invention, global non-intrusive, real-time and quantitative monitoring of the mixing uniformity is realized, and the control efficiency is improved.

The invention discloses a mobility extraction method, system and equipment of a low-temperature CMOS (Complementary Metal Oxide Semiconductor) and a storage medium, which are corresponding schemes: on the premise that a mobility model does not need to be preset, effective carrier mobility can be accurately extracted from standard I-V data, and errors caused by model dependence are avoided; moreover, different contributions of a strong field and a weak field to the mobility can be effectively distinguished and quantified, so that decoupling of a mobility physical mechanism is realized; meanwhile, drain-source parasitic resistance is extracted synchronously, interference of the drain-source parasitic resistance on mobility errors is avoided, and modeling consistency and physical integrity are enhanced; in addition, the method has good robustness and universality, is suitable for devices with different process nodes and different sizes, and can be conveniently integrated into an automatic modeling and evaluation process; and finally, the extracted mobility has clear physical parameter interpretability, can be directly used for tasks such as low-temperature circuit simulation, process analysis and device reliability evaluation, and has important engineering practical value.

The invention provides a credit granting approval process analysis method and device. Comprising the steps of performing word segmentation on text content in a credit granting approval document set, and combining the obtained segmented words to obtain combined phrases; calculating weighted word frequency-inverse document word frequency of the combined phrases; target phrases with weighted word frequency-inverse document word frequency larger than a word frequency threshold value are screened out from the combined phrases, and an amplified word list is generated according to the target phrases and the original word list; training a target word segmentation device based on the amplified word list; finely adjusting the basic vector model according to the training corpus to obtain a term vector model; analyzing the auditing opinion information based on a large language model to obtain an initial risk analysis rule containing a preset dimension; based on a similarity algorithm, a target word segmentation device and a term vector model, grouping and integrating the initial risk analysis rules to obtain risk analysis rules; and processing the information of each examination and approval stage by using a big language model and adopting a risk analysis rule to obtain examination and approval suggestion information.

The invention relates to the technical field of industrial wastewater treatment, and discloses a treatment method and system for industrial wastewater in mortar production, and the method comprises the following steps: obtaining source processes and characteristic property real-time parameters of the industrial wastewater in mortar production, carrying out treatment difficulty grading treatment on the industrial wastewater to obtain a treatment difficulty grade, the method comprises the following steps: carrying out intelligent distribution of treatment processes on industrial wastewater, carrying out time grading gravity precipitation analysis on the industrial wastewater, calculating the addition amount of a flocculating agent in each grade of industrial wastewater based on a data set after gravity precipitation to obtain a flocculating agent addition amount sequence, and carrying out time gradient stirring process analysis on the industrial wastewater to obtain a flocculate mass index; performing quality grading treatment process analysis on the industrial wastewater to obtain a separation liquid index, and analyzing the water quality condition of the industrial wastewater subjected to multi-stage filtration treatment based on the concentration of residual pollutants to obtain a final water quality result; the treatment efficiency of industrial wastewater in mortar production can be improved.

The invention belongs to the technical field of data flow, and discloses a data flow monitoring model device based on a government affair system. By solving the problem that government affair public data generally lacks security monitoring blind spots of overall government affair public data flow monitoring, the depth and breadth of security monitoring are effectively improved, so that the problem that a traditional security protection means is difficult to deal with advanced persistent threats, large-scale sensitive data leakage and novel threats of complex network attacks is solved. Through safety supervision and safety panoramic analysis of government affair public data flow monitoring, a result after safety data analysis is analyzed according to research and judgment analysis, authorization analysis and flow supervision process analysis of flow data safety monitoring and supervision design, and cross-platform, cross-department and cross-level unified data safety situation presentation and centralized management are realized.

The application provides a power equipment temperature rise load performance index diagnosis method, comprising the following steps: establishing a power equipment load current and temperature mathematical model according to current heat generation and heat dissipation process analysis; calculating the equipment temperature rise load performance index according to the power equipment load current and temperature mathematical model; and judging the equipment fault state according to the amplitude and trend of the deviation of the equipment temperature rise load performance index with time or the three-phase deviation degree or the phase-to-phase temperature rise load variable ratio of the equipment temperature rise load performance index. The application relates to an electronic device and a storage medium, which are used for executing the above method. The application applies the load current and temperature relationship model to the monitoring and diagnosis of the power equipment, greatly promotes the development of the power equipment state monitoring and diagnosis technology, improves the accuracy and reliability of the power equipment monitoring and diagnosis, and well solves the inherent problems existing in the power equipment state monitoring and diagnosis.