2579 results about "Power engineering" patented technology

The invention discloses an intelligent cable digital comprehensive monitoring system, and relates to the technical field of electric power engineering, the intelligent cable digital comprehensive monitoring system comprises a digital monitoring center, the digital monitoring center is in communication connection with the following modules: a holographic sensing monitoring module used for deploying an intelligent sensing system and collecting monitoring data including cable operation parameters and environmental data, and the collected data is preprocessed. According to the invention, real-time and comprehensive monitoring of the cable body and the surrounding environment is realized through the holographic sensing monitoring module and the digital twinning technology, the virtual model of the cable is dynamically updated, and the physical state change of the cable is reflected in real time, so that operation and maintenance personnel can find potential problems in cable operation in time, and the working efficiency is improved. And the service life trend and the fault risk of the cable are predicted in advance through the simulation prediction module, and differential maintenance strategies are formulated, so that the possibility of sudden faults of the cable is effectively reduced, the operation reliability of the cable is remarkably improved, and stable operation of a power system is ensured.

The invention relates to the technical field of engineering management and control, in particular to an electric power engineering construction management and control method and system based on digital twinning. The method comprises the following steps: acquiring heterogeneous sensing data of a construction area, and carrying out dynamic modeling on a structural member to obtain a member-level digital twin grid; performing environmental factor-material performance response coupling based on the component-level digital twin grid to obtain a material environmental response distribution diagram; component environment sensitivity dynamic injection is carried out according to the component-level digital twin grids, and a construction process dynamic map is obtained; performing multi-mode construction state field deduction based on the construction process dynamic map to obtain a construction state evolution distribution field; and performing reversible process scheduling optimization and simulation according to the construction state evolution distribution map to obtain a reversible scheduling optimization map. The efficiency of electric power engineering construction and the resource utilization rate can be improved.

The invention discloses an electric power engineering knowledge base construction method based on a large model. The method comprises the following steps: acquiring electric power engineering original knowledge data and an electric power engineering terminology library; the original knowledge data comprises text data and image and drawing data; performing model training on the pre-training language model based on the text data and an electric power engineering terminology library to obtain a language model; performing naming recognition on the text data based on a language model to obtain a plurality of entities in the electric power engineering, and performing extraction labeling on relationships and attributes among the entities to obtain entity associated data; constructing a multi-modal knowledge graph based on the image and drawing data and the entity association data; and performing model training on the pre-trained large model based on the text data and the multi-modal knowledge graph to obtain a large model, and performing fusion storage on the large model and the multi-modal knowledge graph to obtain the electric power engineering knowledge base. According to the method, the query efficiency of the knowledge base in practical application and the effectiveness of answers are improved.

The invention relates to the technical field of electric power engineering, and discloses an electric power engineering multi-modal RAG system based on a knowledge graph and multi-Agent collaboration, and the system comprises a multi-modal dynamic knowledge base construction module which is configured to carry out the structural processing, multi-dimensional knowledge organization and dynamic optimization of electric power engineering multi-modal data; the self-adaptive retrieval strategy engine module is configured to construct a weight decision network based on deep reinforcement learning and execute multi-channel parallel retrieval and result fusion; the iterative self-reflection reasoning module is configured to generate a reasoning path in combination with the retrieval result and verify evidence validity from multiple dimensions; the MCP tool intelligent calling module is configured to integrate multiple types of standardized MCP tools; and the multi-Agent collaborative framework is configured to provide multiple types of Agents which are specific in function and have a cross-module interaction capability. According to the method, the question and answer accuracy, the reasoning depth and the result interpretability in the complex multi-modal scene of the electric power engineering can be remarkably improved.

The invention relates to the technical field of intelligent power grids, in particular to an intelligent design method and system for electric power engineering cloud resources based on distributed computing. Comprising the following steps: constructing an electric power engineering multi-dimensional resource modeling system, dividing calculation nodes into three types of heterogeneous resource units including a real-time processing core, a data analysis core and a disaster recovery backup core, and establishing a dynamic attribute matrix containing time delay sensitivity, an energy consumption coefficient and a risk assessment value; the real-time processing core is configured with a hardware acceleration instruction set and supports microsecond response; a self-adaptive dynamic clustering algorithm is adopted, elastic resource clusters facing task requirements are generated according to the spatial topological relation of resource units and the load change trend, a quantum genetic optimization mechanism is introduced in the clustering process to dynamically adjust the inter-cluster coupling degree, and a cross-cluster communication link based on credibility evaluation is established; according to the design, the problems of low resource utilization efficiency and service quality degradation caused by a static allocation mode can be fundamentally solved.

The invention discloses a power transmission line constructor identity verification method based on face recognition, and relates to the technical field of electric power engineering safety management, and the method comprises the steps: collecting multispectral face data, and generating a spectral stereo feature matrix; micro blood flow pulsation characteristics, skin texture characteristics and thermal imaging temperature distribution characteristics are extracted from the spectrum stereo characteristic matrix, a three-layer cascade anti-counterfeiting verification mechanism is constructed, and comprehensive living body judgment is carried out; establishing a distributed feature matching network, and matching the spectrum stereo feature matrix with a pre-stored feature library; collecting a geographic position track and an operation behavior mode of a constructor, and carrying out multi-dimensional cross validation on the geographic position track and the operation behavior mode and an identity matching result to generate a multi-level safety evaluation index; and writing the identity verification process and the multi-level security evaluation index into a distributed account book, and generating a verification voucher. According to the invention, cross analysis is carried out on the identity matching result of the constructor and the behavior characteristics, so that the problem that a traditional face recognition system is easily falsely used by the identity is effectively solved.

The invention relates to the technical field of electric power engineering management and control, and discloses an electric power engineering construction project whole process management and control system. The system comprises an engineering parameter monitoring module, a risk analysis module, a progress control module, a quality evaluation module, an early warning output module and a background supervision terminal. The engineering parameter monitoring module collects multi-dimensional real-time parameters through a sensor array and sends the multi-dimensional real-time parameters to the risk analysis module and the background supervision terminal. The risk analysis module generates a progress control instruction according to the deviation between the real-time parameter and a preset standard parameter and sends the progress control instruction to the progress control module. The progress control module executes progress adjustment operation, and the quality evaluation module monitors the adjustment process and generates a quality signal. The early warning output module receives the quality early warning signal, generates early warning information and sends the early warning information to the background supervision terminal, and the background supervision terminal gives an alarm. According to the system, collaborative operation of engineering parameter real-time monitoring, risk analysis, progress adjustment, quality evaluation and early warning is realized, and a whole-process management and control closed loop is formed.

The embodiment of the invention provides a BIM electric power engineering collaborative design method and a related device, and the method comprises the steps: obtaining data of a plurality of professional design models, carrying out the cross-professional feature extraction of the data of the plurality of professional design models, generating a feature information set related to each professional design model, and carrying out the collaborative design of the BIM electric power engineering based on a preset electric power engineering constraint rule set. Carrying out conflict coordination processing on cross-professional feature information in the feature information set, determining collaborative constraint parameters associated with the plurality of professional design models, carrying out parameter synchronous updating on the data of the plurality of professional design models according to the collaborative constraint parameters, generating a unified electric power engineering collaborative design model, and finally, carrying out collaborative design on the plurality of professional design models. And outputting three-dimensional space coordinate data and equipment interface parameter data corresponding to the electric power engineering collaborative design model, and triggering a data docking protocol with an external construction system.

The invention provides an electric power engineering survey data processing method and a related device, and the method comprises the steps: obtaining a multi-source survey data set of a target region, the multi-source survey data set comprises geological topographic data, electromagnetic interference data and equipment layout data, carrying out the joint feature mapping of the multi-source survey data set through a pre-trained feature extraction network, and obtaining a feature mapping result; a multi-dimensional survey feature vector is generated, the multi-dimensional survey feature vector is input into an optimization decision model for iterative parameter adjustment, an electric power engineering optimization parameter set of the target area is generated, and the optimization decision model is obtained through training based on a mapping relation between historical survey data and a verification optimization result; and generating an electric power facility deployment scheme of the target area according to the electric power engineering optimization parameter set, wherein the deployment scheme comprises a power transmission line path planning result, substation site selection coordinates and an electromagnetic interference suppression strategy. According to the method, the environmental adaptability, the global coordination and the construction performability of a power facility deployment scheme can be improved.

The invention relates to the technical field of electric power engineering purchase demand prediction, in particular to an electric power engineering purchase demand prediction system based on machine learning, and the system comprises the steps: obtaining historical purchase data, construction progress information and electric power engineering design parameters, carrying out the standard stage division and time alignment, and constructing a stage sequence model reflecting the material use rhythm; and a coupling factor matrix is generated based on the material co-occurrence frequency and the stage position relationship, and the modeling capability of the model for the material cooperation relationship is enhanced. And the stage time sequence features, the coupling information and the structured engineering parameter vectors are fused and input into a regression prediction model, so that accurate mapping of material demands and multi-dimensional engineering features is realized, and the purchase prediction precision in a target period is improved. A deviation sequence is constructed based on historical prediction errors, and error correction is performed through a feedforward neural network, so that prediction accuracy and response capability are effectively improved, and resource waste and construction delay are reduced.

The invention discloses a progress management system and method for electric power engineering, and belongs to the field of electric power construction engineering, and the system comprises a data collection module which is used for obtaining real-time sensor data, construction log data and external data of a construction site; the feature engineering module is used for integrating the multi-source data of the data acquisition module based on a spatial-temporal feature fusion engine and constructing an enhanced feature matrix; the model processing module is used for outputting a progress deviation and an equipment fault probability based on the PhaseAware LSTM network; key features are selected according to the construction stage, structured prediction is carried out based on a random forest, and a progress deviation rate prediction value and a risk factor evaluation result are output; and the dynamic weight fusion module is used for dynamically distributing model weights based on the prediction results of the random forest and the LSTM, the real-time equipment state and the environment parameters, and generating a fused progress prediction value. According to the invention, high-precision progress prediction and risk early warning can be output.

The invention discloses an electric power engineering construction safety monitoring system based on deep learning, and belongs to the technical field of electric power engineering construction safety, and the system comprises a data collection module which is used for collecting an RGB image, a laser radar point cloud and a depth map of a construction site in real time; the intelligent analysis module is used for predicting the risk levels of material dumping, personnel falling, mechanical collision and electrical danger in parallel based on a multi-task deep learning model; the dynamic decision-making module is used for dispatching personnel, the AGV and the unmanned aerial vehicle based on reinforcement learning according to the risk prediction result and the risk priority, sending a mechanical sudden stop instruction and guiding the personnel to avoid risks in real time through alarm information; and the feedback optimization module is used for optimizing the model through incremental learning. According to the invention, real-time prediction and automatic response of various accidents are realized through multi-modal data fusion and intelligent decision.

The invention relates to the technical field of electric power engineering information processing, and discloses a power grid power transformation engineering knowledge graph construction and retrieval method and system, and the method comprises the steps: carrying out the dynamic adaptive partitioning of a power grid power transformation engineering related document, and obtaining semantic coherent and independent text blocks; extracting entities and relationships based on the text blocks, and complementing implicit entities and relationships through a multi-round refining mode; performing fusion and disambiguation on the extracted and complemented entities and relationships to form a unified knowledge graph; performing hierarchical clustering on the formed knowledge graph to generate a multi-granularity community structure and a corresponding community report; intention resolution and pre-judgment guidance are carried out aiming at fuzzy questions of the user, and a retrieval strategy is optimized; and executing multi-hop semantic retrieval based on the optimized retrieval strategy, recalling related knowledge and generating answers. According to the method, automation, precision and intelligentization of power grid power transformation engineering knowledge graph construction and full-link retrieval can be realized.

The invention provides an electric power engineering detection method, system and device and a storage medium, and relates to the technical field of power plant operation management, and the method comprises the steps: determining the remaining bearable power of each normal generator according to the output power and rated power of each normal generator; determining a first power transfer scheme of each normal generator in combination with the residual bearable power and the to-be-transferred load power of the abnormal motor; according to the historical load data, predicting a load change trend of each normal generator in a preset duration, and adjusting the first power transfer scheme according to the load change trend to determine a second power transfer scheme; and adjusting the second power transfer scheme according to the historical operation parameters, determining a target power transfer scheme of each normal generator, and adjusting the output power of each normal generator. The method has the technical effects of accurately transferring and distributing the load power of the abnormal generator and ensuring safe and stable operation of the generator set.

The invention discloses an electric power engineering project management talent intelligent evaluation and dynamic training system, and the system comprises a multi-dimensional quality capability model construction module which constructs a four-dimensional capability framework based on the characteristics of an electric power engineering industry, generates a differentiated post capability model through a dynamic weight distribution algorithm, and carries out the dynamic training of the differentiated post capability model; constructing an industry ability dictionary library by utilizing a knowledge graph technology; the intelligent evaluation and matching module integrates a multi-modal evaluation tool to collect dominant and implicit capability data, dynamically adjusts capability index weights through a pre-trained AI model based on project characteristic parameters, and calculates man-post adaptation indexes by adopting a cosine similarity algorithm; and the dynamic training and development module is used for generating a personalized training scheme by quantifying the capability difference, tracking the training effect in a closed-loop manner based on a Korotkoff four-level evaluation model, and dynamically optimizing a training path by adopting a Bayesian network. The technical defects of single evaluation dimension, low man-post matching degree and insufficient cultivation efficiency of traditional power engineering human resource management can be solved.

The invention discloses an electric power engineering defect diagnosis method based on AI image recognition and a block chain technology, and relates to the technical field of electric power engineering defect diagnosis, and the method comprises the following steps: setting the initial flight rate of an unmanned plane according to the monitoring demands and field conditions of an electric power line, it is ensured that the unmanned aerial vehicle can cover all key areas of the power line in the inspection process, and meanwhile the inspection efficiency is kept. According to the invention, by intelligently adjusting the flight rate of the unmanned aerial vehicle, the unmanned aerial vehicle can stay in a potential abnormal area for a longer time, and detailed acquisition of temperature data is ensured, so that tiny temperature changes, especially tiny temperature anomalies caused by electric arcs and electrical overload, can be captured more accurately. According to the intelligent adjusting mechanism, in the inspection process, the inspection efficiency of the whole process can be guaranteed, accurate monitoring of the key area can be guaranteed, and the risk of detail loss or temperature anomaly missing detection caused by the too high flight speed is reduced.

The invention discloses a circulating fluidized bed temperature intelligent prediction method based on a physical information neural network, and mainly relates to the technical field of industrial process intelligent control and energy power engineering crossing. Comprising the following steps: S1, acquiring operation data of the circulating fluidized bed, and preprocessing the operation data to obtain a data set; s2, constructing a physical information residual neural network; s3, constructing a loss function of adaptive weight adjustment; s4, training the physical information residual neural network by using the data set, and performing iterative optimization in combination with the constructed physical information residual neural network and the loss function to obtain a bed temperature prediction model; s5, inputting operation data of the circulating fluidized bed into the bed temperature prediction model to obtain a bed temperature prediction value; the method can solve the problem of complexity and nonlinearity of dynamic prediction of the bed temperature of the circulating fluidized bed, can optimize the operation efficiency of the boiler, improves the combustion stability, and reduces the emission of pollutants.

The invention discloses an electric power state stability monitoring system and method, and relates to the field of electric power engineering and energy management, and the method comprises the steps: capturing an abnormal sound signal through a high-sensitivity ultrasonic sensor, collecting amplitude data through the sensor, and fusing the abnormal sound signal and the amplitude data to obtain an ultrasonic signal data set; the information is transmitted to the central processing unit; after the ultrasonic signal data set is transmitted to the central processing unit, the ultrasonic signal data set is preprocessed, unique modes of the potential fault modes are extracted through a deep learning algorithm, and a feature report is generated; and training a deep learning model by using the feature report and historical data, identifying a power grid topological structure and a change rule, collecting power grid operation data by using a sensor, and inputting the data into the trained model. Abnormal sound signals are captured through the high-sensitivity ultrasonic sensor, amplitude data are collected, the abnormal sound signals and the amplitude data are fused to form the ultrasonic signal data set, and precise detection of tiny anomalies in the power equipment is achieved.

The invention discloses an acoustic imaging positioning method for intelligent monitoring of electric power engineering regional faults, which relates to the technical field of fault monitoring, and comprises the following steps: arranging a microphone array to collect sound wave signals, and monitoring and recording sound data in real time; determining the spatial position of a sound source by using an ultrasonic sound source positioning technology; sound source distribution generated by the equipment fault is displayed; displaying the relationship between the three-dimensional position of the equipment fault point and the surrounding environment; fault sound sources are classified, and types and reasons are determined; a diagnosis result is fed back in real time, a fault position is displayed, and inspection and repair suggestions are provided; and detecting the health condition of the equipment in combination with a machine learning model, predicting potential faults and giving out early warning. According to the invention, a high-precision microphone array and an ultrasonic sound source positioning technology are utilized, the distribution state of a sound source in a space is displayed in real time through an imaging mode of superposing an acoustic image and a visible light image, a partial discharge point, a gas leakage point and an equipment abnormal sound site are rapidly determined, and the inspection efficiency and the maintenance speed are improved.

The invention relates to a method and a system for intelligent retrieval and review of a multi-modal electric power engineering document, belongs to the technical field of natural language processing, and solves the problems of poor relevance and incomplete review of an existing multi-modal document retrieval result. The method comprises the following steps: performing logic region division on each electric power engineering document, extracting a multi-modal fusion vector of each logic region, and aggregating to obtain a document feature vector; calculating the multi-level similarity between the received query word and each electric power engineering document, and obtaining a plurality of electric power engineering documents with the highest similarity as retrieval documents; and dynamically expanding each rule in the rule base, and performing compliance review on each retrieval document by utilizing the expanded rule according to the document feature vector of the retrieval document to generate a review report. The efficient and accurate retrieval of the multi-modal electric power engineering document is realized, and the comprehensiveness and flexibility of review are improved.

The invention relates to the technical field of electric power engineering, and discloses an internet of things type box-type substation based on online monitoring, which comprises a sensor network layer, an edge intelligent node layer, a self-healing communication module layer and a cloud management platform layer, the sensor network layer is used for collecting the operation state and environmental parameters of equipment in the box-type substation in real time; the edge intelligent node layer is used for processing sensor data, executing self-adaptive monitoring and local diagnosis and communicating with the cloud; the self-healing communication module layer is used for ensuring the reliability and continuity of data transmission; and the cloud management platform layer is used for receiving the data uploaded by the edge nodes and carrying out long-term analysis, model training and remote management. Through the adaptive multi-parameter fusion monitoring technology, the sampling frequency of the sensor is dynamically adjusted (for example, the temperature is increased from one time per second to two times per second when the temperature is abnormal), and in combination with a lightweight machine learning model of an edge intelligent node, equipment faults (such as insulation degradation and overheating) can be accurately predicted.

The invention discloses an electric power engineering cost simulation analysis method and system based on digital twinning, and relates to the technical field of simulation analysis, and the method comprises the steps: obtaining multiple engineering task multi-modal data and task dependency relationships for electric power engineering; processing the multi-modal data of the plurality of engineering tasks and the task dependency relationship based on a digital twinning technology so as to construct an electric power engineering virtual model; inputting the electric power engineering virtual model into a graph neural network so as to extract task node features corresponding to each engineering task virtual module through a message passing mechanism; and defining an input state of a reinforcement learning model according to each extracted task node feature so as to generate a task resource allocation action for each engineering task through reinforcement learning. Therefore, the digital twinborn technology, the graph theory feature extraction technology and the reinforcement learning technology are comprehensively applied, real-time monitoring and simulation analysis are carried out on cost and resource consumption of different links in the electric power engineering, and resource allocation is intelligently optimized.

The invention relates to the technical field of electric power engineering automation, in particular to a low-voltage equipment power factor automatic adjusting system and method based on end compensation, and the system comprises a load monitoring module, a compensation strategy generation module, an end compensation execution module, a dynamic balance correction module and an effect evaluation module. According to the invention, the sequential relationship between the load fluctuation and the compensation demand can be accurately identified by continuously monitoring the current waveform, the voltage waveform and the phase difference change trend of the low-voltage equipment, and the compensation strategy is dynamically formulated in combination with the response duration and the compensation demand matching rule, so that the compensation response agility and the matching property of the fluctuating load are improved; dynamic scheduling is carried out according to the capacitor switching capacity and the combination relation in compensation execution, switching weight configuration is analyzed and optimized through the power factor change rate before and after compensation and the load synchronization characteristic, the dynamic balance of the compensation process is enhanced, the power factor stability and the load fluctuation matching capacity after compensation are effectively improved, and the compensation efficiency is improved. And the adaptability and continuity of the adjusting effect are enhanced.

The invention belongs to the technical field of electric power engineering digitization and intelligent drawing auditing, and particularly relates to a dynamic rule engine and multi-target auditing task decomposition method oriented to electric power drawings. Obtaining a power rule file, analyzing and verifying to generate qualified rules, and screening the qualified rules to obtain an effective rule pool; the method comprises the following steps: reserving candidate areas by preprocessing an electric power engineering drawing, generating structured cells through line segment classification and combination and table detection, extracting and cleaning a text, and affiliating the text to the corresponding cells to form a structured result; screening candidate rules from the effective rule pool, extracting auditing objects from the structured result, generating auditing points, calculating the priority of the auditing points, and packaging the auditing points into an assignment unit set capable of being executed in parallel; on the basis of the dispatching unit set, optimizing task distribution by adopting a dynamic model and a greedy algorithm in an execution environment with the maximum concurrency, and doubly optimizing task execution by quantifying benefits and verifying rules; and performing rule judgment and result measurement on a task execution result.

The invention discloses a line intelligent planning and fault early warning method suitable for electric power engineering design, and relates to the technical field of electric power engineering. The method comprises the following steps: quantifying geographic information, geological conditions and construction cost into a continuous decision curved surface through spatial semantic segmentation and a cost curved surface model, and identifying a large-area low-cost region as a primary feasible region in combination with a dynamic clustering algorithm; a multi-dimensional decision index is constructed based on spatial features, geological stability and facility association data, fault regions such as terrain abrupt change or facility conflict are identified through real-time association coefficients, and an exception handling mechanism is triggered; and selecting a seed region with an optimal construction condition as an anchor point, constructing a joint probability model of spatial features and cost, and generating an optimal path considering feasibility probability and cost effectiveness in combination with an expectation maximization algorithm and a graph optimization technology. According to the invention, scientificity and economical efficiency of cable planning under complex geological conditions are improved, and key technical support is provided for intelligentization of electric power engineering.

The invention discloses a power consumption control method and device for a power distribution network monitoring control chip and a storage medium, and the method comprises the steps: carrying out the clock domain division of the power distribution network monitoring control chip, and obtaining a target clock domain; obtaining current load data and historical load data of the target clock domain; according to the historical load data, trend prediction processing is carried out by using an autoregressive moving average model to obtain predicted load data; according to the predicted load data and the power consumption state of the control chip, performing action evaluation processing by using preset reinforcement learning to obtain a state action function value; calculating a to-be-adjusted clock frequency and a to-be-adjusted voltage according to the current load data; determining a predicted clock frequency and a predicted voltage according to the state action function value; and performing power consumption control on the target clock domain according to the target clock frequency and the target voltage to obtain a power consumption control result. The power consumption control is realized, and the resource utilization rate and the control efficiency are improved. The method can be widely applied to the technical field of electric power engineering.

The invention belongs to the technical field of computer-aided project management, and discloses an electric power engineering design project management system and method, and the system comprises a data integration and processing module, a multilayer dynamic knowledge graph data storage library, a graph-based automatic compliance check engine, and a graph neural network-based predictive risk engine. And an active design change impact analysis module. According to the method, a unified and intelligent project data core is constructed, heterogeneous data sources such as design files and law and regulation texts are integrated in a multi-layer dynamic knowledge graph, automatic compliance review is realized by utilizing graph query, data-driven risk prediction is realized by utilizing a graph neural network GNN, and the risk prediction efficiency is improved. And the linkage influence of design change can be simulated and quantitatively evaluated. According to the method, the problems of data islanding, passive compliance examination, subjective risk management, difficulty in change analysis and the like in the prior art are solved, and the management efficiency, accuracy and initiative of the electric power engineering design project can be remarkably improved.

The invention relates to the technical field of computer vision, and provides an electric power engineering drawing defect positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the defect analysis of an electric power engineering drawing through a preset multi-level progressive analysis architecture, sequentially generating a drawing analysis result, a functional block identification result, an equipment component detection result and an element parameter verification result; performing feature fusion based on a drawing analysis result, a functional block recognition result, an equipment component detection result and an element parameter verification result by adopting a cross-level feature fusion mechanism to generate a comprehensive defect positioning result; and based on the comprehensive defect positioning result, generating a corresponding defect positioning report and performing visual display. Through a multi-level progressive analysis architecture and a cross-level feature fusion mechanism, accurate positioning from the whole drawing to element parameters is realized, and the efficiency and accuracy of defect positioning of the electric power engineering drawing are effectively improved, so that the automation level and reliability of drawing auditing are improved.

The invention discloses a GIS circuit diagram intelligent generation method based on an electric power pipe arrangement engineering drawing, and relates to the technical field of electric power engineering design. The method comprises the steps of preprocessing multi-source data, planning a path and detecting conflicts, intelligently generating a dynamic layer and adaptively outputting in a cross-platform manner. The preprocessed multi-source data receives design parameters and multi-class data to generate a standardized data set; the path planning and conflict detection are combined with various conditions to generate constraints, and accurate parameters are output; the dynamic layer intelligent generation module is used for generating multiple types of layers according to the data, generating drawings and accounting the cost; in the cross-platform self-adaptive output step, graphs are displayed on multiple terminals based on a framework, and a multi-format export interface is provided. According to the method and the system, intelligent generation of the GIS circuit diagram of the electric power tube bank engineering drawing is realized, and the design efficiency and accuracy are improved.

A primary and secondary fusion complete column-mounted circuit breaker convenient to disassemble and assemble relates to the technical field of electric power engineering and comprises a quick disassembly and assembly mechanism and a quick lifting mechanism. The rapid disassembly and assembly mechanism comprises a triangular support, a pole-mounted circuit breaker, a circuit breaker base, a limiting bottom plate, a sliding rod, a spring, an unfolding assembly and a clamping assembly. The pole-mounted circuit breaker is fixedly installed on the circuit breaker base, a plurality of sliding rods are arranged on the side face of the circuit breaker base, and the sliding rods are in sliding connection with round holes in the limiting bottom plate; during use and installation, the limiting bottom plate can be stretched out and drawn back so as to adapt to the widths of different triangular supports, the circuit breaker base can be stably installed on the triangular supports, meanwhile, after the width, corresponding to the triangular supports, of the limiting bottom plate is adjusted, the clamping plates can slide towards the two sides in a tool-free mode, and the circuit breaker base can be stably installed on the triangular supports. And the round rod on the clamping plate clamps the round hole in the triangular bracket, so that the fixation of the circuit breaker base is completed.