2896 results about "Data visualization" patented technology

The invention discloses an interactive question intelligent agent system based on a large language model, and relates to the technical field of dialogue interaction systems. Aiming at the technical defects of the traditional BI tool, the technical scheme is as follows: a heterogeneous data management engine realizes unified access and secure access of cross-source data; the NLP semantic recognition engine converts a natural language into structured semantics through multiple steps, drives the hybrid SQL generation engine and provides visual parameters; the generation engine realizes precise generation from semantics to SQL through a two-stage architecture based on metadata and authority rules; and the visual management console is combined with multi-party configuration and parameters to visually build a number-asking agent. The method is used for realizing intelligent conversion from a natural language to a structured query language (SQL) and a data service interface, and automatically generating an interactive data visualization result.

The invention discloses a transformer substation electric power parameter real-time monitoring and analysis platform, and relates to the technical field of electric power monitoring. The monitoring analysis platform is in communication connection with a real-time monitoring module, a data acquisition and processing module, a data storage and management module, a fault feature extraction module, an event early warning module, a fault diagnosis module and a data visualization module. The transformer station electric power parameter real-time monitoring and analysis platform timely discovers abnormal conditions of electric power equipment by collecting and analyzing key parameters of voltage, current, power, temperature and humidity in real time, so that potential faults and accidents are prevented, and the real-time monitoring and analysis of the electric power parameters of the transformer station is realized by learning historical fault data and identifying modes. The platform can predict and identify an abnormal trend which may cause a fault, gives out an early warning in advance, remarkably improves the reliability and safety of a power system, reduces the risks of accidental power failure and equipment damage, and guarantees the continuity and stability of power supply.

The invention relates to a data access method and system of an intelligent Internet of Things gateway. The method comprises the following steps: performing feature matching and protocol identification on a plurality of sensors and terminal equipment connected to the intelligent Internet of Things gateway by using an equipment feature library to obtain an equipment protocol type; analyzing the original data to obtain standardized data; performing encryption processing to obtain an encrypted security data packet and an encrypted session key; performing multi-factor transmission channel selection to obtain an optimal transmission channel combination; and based on the optimal transmission channel combination, sending the encrypted security data packet to the Internet of Things platform, verifying the received data confirmation information based on a consensus algorithm, and outputting a data access state report through a data visual interface and an AI voice assistant. The processing strategy can be dynamically adjusted according to the equipment characteristics, the data characteristics and the network environment, and the flexibility and adaptability of the system are improved.

The invention discloses a multi-modal visual arrangement recommendation method, belongs to the technical field of artificial intelligence and data visualization crossing, and realizes visual arrangement recommendation based on multi-modal input analysis, a dynamic mixed recommendation model and an intelligent optimization algorithm. Comprising the following steps: multi-modal intention analysis: realizing intelligent analysis of multi-modal input through combined use of a base model and a fine tuning model, realizing high-precision intention classification in combination with a pre-training language model and a domain adaptation fine tuning technology, and triggering dynamic prompt word recommendation; performing intelligent layout generation: performing global optimization of component space allocation by adopting a genetic algorithm, performing business rule adaptation by combining a constraint solver, and modeling an interaction relationship between components by utilizing a graph neural network; and dynamic mixed recommendation: constructing a three-level recommendation architecture including collaborative filtering, content matching and reinforcement learning. According to the method, a closed-loop recommendation process of user intention-intelligent recommendation-feedback optimization is realized, and the intelligent level of visual arrangement and the user experience are remarkably improved.

The invention relates to the technical field of medical intelligent scheduling, in particular to a patient flow data visualization adjusting system and method, and the system comprises a global dynamic sensing unit, a medical intelligent evolution center, a space-time mirror image twinning module, a multi-dimensional decision optimization matrix, and a risk closed-loop management and control unit. The global dynamic sensing unit gathers data to construct a diagnosis and treatment panorama; the medical intelligent evolution center is used for building a medical process evolution system to form a three-dimensional cognitive architecture; the space-time mirror image twinning module is used for constructing physical virtual space mapping, and forming a diagnosis and treatment resource space-time distribution path based on Internet of Things position data and a digital twinning technology; the multi-dimensional decision optimization matrix extracts patient flow data according to the space-time simulation path and a multi-target model, and generates a resource scheduling scheme; and the risk closed-loop management and control unit is used for evaluating the risk, marking congestion early warning and dynamically optimizing a regulation and control strategy and a threshold value. Therefore, the problems of data isolation, poor resource configuration efficiency, insufficient real-time performance and the like in the prior art are solved.

The invention relates to the field of data visualization, in particular to a visualization method and system based on a vehicle service supply chain. The method comprises the following steps: acquiring whole-process information of a vehicle service supply chain; carrying out supply chain main body identification on the whole flow information of the vehicle service supply chain, carrying out spatial topology distribution analysis, and constructing a supply chain main body topology distribution map; obtaining supply chain main body interaction logic data based on the plurality of supply chain main bodies; performing topology interaction logic connection on the supply chain main body topology distribution graph by utilizing supply chain main body interaction logic data, and constructing a supply chain topology interaction network; performing intra-period path transportation frequency calculation on the whole-process information of the vehicle service supply chain to generate logistics demand trend characteristics; and performing operation behavior analysis of each link on the whole-process information of the vehicle service supply chain to obtain the capacity characteristics of each link. According to the invention, through visualizing the vehicle service supply chain, the resource scheduling efficiency and flexibility of the supply chain are improved.

The invention discloses an industrial environment information wireless monitoring system based on the Internet of Things and a control method thereof, and relates to the technical field of industrial management, and the system comprises an intelligent edge calculation module, a data visualization module, a self-healing network management module, a precise energy consumption management module, an environment anomaly detection module and a wireless network optimization module. According to the industrial environment information wireless monitoring system based on the Internet of Things and the control method thereof, real-time analysis and decision are realized at a data source by using an intelligent edge computing module, data transmission delay is reduced, response can be quickly made in an emergency, potential faults are predicted through a time sequence abnormity self-learning network model, and the monitoring accuracy of the industrial environment information wireless monitoring system based on the Internet of Things is improved. And network self-healing is actively carried out before a problem occurs, so that the network downtime is effectively reduced. In addition, due to the introduction of a low-power-consumption ad hoc network protocol, the energy consumption optimization management of the sensor nodes is realized, and the service life of equipment is prolonged.

The invention relates to the technical field of visual rendering, and provides a three-dimensional data visual rendering method and a visual rendering engine system.The method comprises the steps that space segmentation processing is conducted on three-dimensional model data to be rendered through the LOD technology to generate block slice data with different geometric detail levels, organizing the block slice data through a tree structure with a spatial relationship, and outputting the tree structure as an index file; the method comprises the following steps: adaptively screening block and slice data of different levels of detail based on a user vision field range, storing the block and slice data into a rendering request queue, querying block and slice data to be rendered from the rendering request queue according to index codes of the block and slice data, and updating a layer browser database; according to the method, to-be-rendered block slice data are downloaded and analyzed in parallel in batches in a separated collaborative operation mode, and a rendering task is executed according to a data analysis result, so that the rendering scheduling frame rate is remarkably improved, and rapid visualization of urban mass three-dimensional slice data at a webpage end is realized.

A method uses natural language processing for visual analysis of a dataset. The method includes receiving a first natural language (NL) input directed to a data source, from a first client. The method also includes parsing the first NL input into tokens based on a grammar and the data source. The method also includes generating and outputting an intermediate NL response, to a second client, based on the tokens and output modality of the second client. In response to receiving a user input to provide missing information: the method also includes generating an input query based on the user input; and querying the data source using the input query, to obtain a result set. The method also includes generating and outputting, to the second client, a first NL output and a snapshot of a data visualization, based on the result set and the output modality of the second client.

The invention relates to a database query method and device based on a large language model agent and electronic equipment, and the method comprises the steps: obtaining and analyzing query request information, recognizing a query request intention type, carrying out the problem splitting of the query request information according to the query request intention type, and obtaining sub-query request information; searching and obtaining an SQL statement corresponding to the sub-query request information in the target knowledge base according to the category of the query request intention, constructing and generating an SQL statement prompt word and sending the SQL statement prompt word to the large language model when the SQL statement is not searched, executing according to the returned SQL statement to obtain a sub-query result, integrating the sub-query result and obtaining a query result of the query request information, and generating a data visualization code based on the large language model, executing and outputting a query result and a visualization display result thereof. By combining natural language processing, a large language model and a multi-item optimization technology, the efficiency and usability of data query are greatly improved, and non-technical users can conveniently analyze complex data.

The embodiment of the invention discloses a multi-agent collaborative data visualization analysis method and device and a medium, and relates to the technical field of visualization analys.The method comprises the steps that a natural language analysis request input by a user is received, task splitting is conducted on the natural language analysis request through a preset task planning agent, and the task splitting result is obtained; generating corresponding task plan information, obtaining real-time operation data of a preset functional agent cluster, carrying out agent distribution on the plurality of sub-tasks based on the real-time operation data and the task plan information, determining a target functional agent corresponding to each sub-task, and sending the target functional agent to a server; the target function agent comprises any one of a data analysis agent and a visual display agent; and executing the corresponding data analysis subtask through the data analysis agent to obtain a data analysis result, performing agent cooperative verification on the data analysis result, and after the verification is passed, generating visual analysis data corresponding to the data analysis result through the visual display agent.

The invention discloses a building waterproof construction quality monitoring and early warning system based on the Internet of Things, relates to the technical field of building engineering, and realizes omnibearing and real-time monitoring and intelligent early warning of a building waterproof construction area through a multi-layer architecture formed by a data acquisition layer, a data transmission layer, a data processing layer and an application layer. The data processing layer analyzes data features from a time sequence and a spatial distribution dimension through normalization, denoising processing and a multi-head attention mechanism in a Transform model, and accurately recognizes the abnormality and risk trend of a weak point in combination with dynamic threshold and trend analysis, and the application layer determines the risk trend of the weak point through multi-dimensional data visualization, historical playback and real-time interaction. And the early warning module is combined with intelligent reasoning to generate dynamic maintenance suggestions, a maintenance scheme is optimized, the construction quality and the maintenance efficiency are improved, the intelligent level of building waterproof monitoring is improved, risk prediction and accurate maintenance are realized, the management cost is reduced, and the system has wide application value.

The invention relates to the technical field of fault positioning, in particular to a power wire fault positioning system based on the Internet of Things, which comprises a data collection module, a fault analysis module and a data visualization module, firstly, a data collection module obtains wire data collected by a sensor on a wire in real time; secondly, the fault analysis module is used for carrying out data processing on the wire data to obtain fault data; according to the conductor data and the fault data, constructing a power conductor digital twinborn model; analyzing the fault features and the environmental parameters through a power conductor digital twinborn model to obtain an output result; analyzing the output result through a topology detection algorithm and signal sensitivity adjustment to obtain an optimized output result; obtaining a space-time propagation process formula of the fault signal through signal propagation simulation and space-time analysis according to the output result; evaluating the accuracy of an output result according to a space-time propagation process formula of the fault signal; and finally, the data visualization module generates a visualization chart and an analysis report.

The invention discloses an AI intelligent collaborative monitoring management system for a multi-index water volume system, and relates to the technical field of monitoring management, the collaborative monitoring management system comprises a data acquisition module, a water volume system analysis module, a collaborative monitoring module, an emergency early warning module, an early warning scheme module and a data visualization module, all the modules are connected through electric signals. According to the AI intelligent collaborative monitoring management system for the multi-index water volume system, abnormal changes in water quality, water volume and water ecological indexes are identified through anomaly detection, an early warning mechanism is triggered according to the detected anomaly, early warning information is sent to management personnel through various modes such as a visual interface, a short message and an email, and the management personnel can carry out early warning on the water quality, the water volume and the water ecological indexes. According to the invention, the time interval from the occurrence of the abnormity to the discovery of the abnormity is greatly shortened, and valuable response time is provided for managers, so that further deterioration of the abnormity is effectively restrained, and the safety and sustainable utilization of water resources are guaranteed.

A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) abstracting result data to obtain a data abstraction, the result data being responsive to the one or more data requests, and (v) generating a visualization for the result data based at least in part on the data abstraction.

The invention relates to the technical field of monitoring systems, in particular to an electric power internet of things transformer substation auxiliary equipment monitoring system and method, and the method comprises the steps: collecting the operation data of transformer substation equipment in real time; preprocessing the collected operation data by utilizing edge calculation; analyzing the preprocessed operation data based on a deep learning algorithm, and generating a preliminary fault diagnosis and prediction result; constructing a digital twinborn model of the substation equipment, and performing equipment health assessment and fault prediction by utilizing a preliminary fault diagnosis and prediction result and combining a physical model and historical data of the equipment; and according to the equipment health assessment and fault prediction result, data visualization display is carried out through the monitoring platform, and hierarchical alarm is carried out to inform operation and maintenance personnel. Through the deep learning algorithm and the digital twinborn model, deeper fault analysis and prediction can be provided, and the problem that the equipment is not maintained in time or is excessively maintained is avoided.

The invention relates to the technical field of real-time image superposition, in particular to a bridge inspection method and system based on AR, and the method comprises the following steps: shooting a bridge on site, capturing a real-time image of a structure, and recording vibration frequency, displacement change and stress data by using acceleration, displacement and strain sensors; and synchronously integrating the structure real-time image, the vibration frequency, the displacement change and the stress data, and naming the data as multi-dimensional dynamic monitoring data. According to the method, the vibration frequency, the displacement change and the stress data are integrated in real time, so that the real-time performance and the analysis depth of the multi-dimensional dynamic monitoring data are remarkably improved, the high fusion of a real-time image and a three-dimensional model is realized, the accuracy of data visualization is enhanced, an abnormal region is directly visible through the change of colors and textures, and the accuracy of data visualization is improved. According to the method, the structure safety monitoring intuitiveness and interactivity are improved, in addition, through time sequence analysis, structure changes under different environment conditions are accurately simulated, and prospective risk prediction is provided.

The invention discloses a wind resource assessment report generation method based on a large model technology. The method comprises the following steps: processing multi-source data, and constructing a domain knowledge base and a fine tuning database; field adaptive RAG enhancement is carried out, professional literatures, historical cases and industry specifications in a field knowledge base are retrieved by adopting a retrieval enhancement generation technology, and wind resource assessment contents meeting technical standards are generated through a multi-modal fusion word vector technology; performing large model fine tuning, and optimizing the generative large model through a gradient-free optimization algorithm Wind-DFO on the basis of a fine tuning database by adopting a field self-adaptive fine tuning strategy; and automatically generating a report, arranging and matching multiple templates through an AI workflow, embedding a data visualization chart, executing verification of a grammar layer, a logic layer and a compliance layer, and outputting a standardized wind resource assessment report. The accuracy, specialty and efficiency of report generation are remarkably improved, and the problems that a traditional method depends on artificial experience, the data utilization efficiency is low, and standardization is insufficient are solved.

The invention discloses an enterprise financial management system, and the system comprises a data collection and integration module, a budget and financial execution prediction module, an intelligent decision optimization module, a financial risk prediction and automatic early warning module, an intelligent auditing and compliance guarantee module, and a real-time financial analysis and report module. The real-time financial analysis and report module provides a multi-dimensional dynamic financial analysis and customized report for a management layer by using a natural language generation and data visualization technology, and the system can dynamically process structured and unstructured data, ensure the uniformity and timeliness of the data, and improve the real-time financial analysis and report efficiency. According to the invention, the method achieves the seamless connection of budget and actual execution, supports multi-scene and multi-target decision optimization, remarkably improves the transparency, adaptability and foresight of financial management, improves the accuracy and response capability of decision, and provides an intelligent, global and dynamic solution for the financial management of enterprises.

The invention relates to the technical field of intelligent operation inspection of power transmission lines, in particular to an intelligent detection method of a power grid frame and a satellite image processing system.The method comprises the steps that the power grid frame is detected according to collected multi-source monitoring information, information of a plurality of power grid structures is obtained, and a power grid topology model is established; performing connection analysis on the power grid topology model to obtain a power grid topology analysis result, and performing spatial distribution analysis on the power grid frame by collecting coordinate information of the power grid frame and the power grid topology analysis result to obtain power grid coverage data. And performing data visualization on the plurality of pieces of power grid structure information, the power grid topology analysis result and the power grid coverage data to generate a power grid frame detection result. According to the invention, the method effectively solves a problem that the weak edge region is liable to leak detection in the recognition of the power grid frame in a large-range and high-complexity scene, remarkably improves the recognition efficiency and accuracy of the power grid frame, and reduces the cost and time of manual inspection.

The invention discloses a building pedestrian simulation statistics and analysis method, and belongs to the technical field of simulation. According to the invention, a comprehensive pedestrian behavior evaluation and optimization scheme is provided through normal pedestrian circulation simulation and emergency evacuation simulation in combination with statistical analysis, data visualization and an optimization algorithm. The system manages pedestrian density through a KD tree, performs real-time data visualization by using ScottPlot, generates one-dimensional, two-dimensional and three-dimensional charts, and visually displays pedestrian distribution and flow conditions in a building. In an emergency evacuation scene, the system dynamically plans a path through a # imgabs0 # algorithm, and identifies and relieves a potential bottleneck area in combination with a heuristic function of congestion measurement. The simulation system can collect abundant statistical data including evacuation time, people flow distribution, congestion point analysis and the like, and provides a scientific basis for building safety design improvement and emergency plan making.

The invention specifically relates to the technical field of intelligent irrigation, and discloses a meteorological prediction-based irrigation dynamic regulation and control system, which comprises a data acquisition module, a data analysis module, a strategy generation module, a strategy execution module, a feedback regulation module and a man-machine interaction module, the data acquisition module integrates a water quantity acquisition terminal, a crop state acquisition terminal and a meteorological monitoring terminal, acquires multi-source irrigation decision data of a target irrigation farmland in real time, judges a water shortage risk level of the target irrigation farmland through the data analysis module, and generates an irrigation strategy through the strategy generation module; the strategy execution module executes an irrigation strategy through an electrically-driven intelligent water-saving valve, the feedback adjustment module dynamically adjusts the irrigation strategy based on sensor feedback data, and the man-machine interaction module provides a data visual interface, dynamically optimizes the irrigation strategy in combination with real-time meteorological changes and irrigation feedback, divides water shortage risk levels, and provides a water-saving management system. The utilization efficiency of water resources is effectively improved, and the applicability and reliability of the system are improved.

A method generates data analysis templates. A computing device receives, via a graphical user interface, a natural language input, which includes multiple terms. The terms include one or more data fields and / or data values from a data source. The device designates the natural language input as trigger text for a data analysis template. The trigger text includes the multiple terms. A user defines one or more rules for a subset of the terms, each rule specifying respective criteria to match a respective term in the subset. A user specifies multiple data visualizations corresponding to the trigger text. Each of the data visualizations (i) uses a respective one or more data fields, from the data source, corresponding to terms from the trigger text and (ii) has a respective data visualization type. The device generates the data analysis template according to the trigger text, the user definition, and the user specification.

The invention discloses a transformer substation external damage prevention intelligent monitoring method and system based on cloud computing and artificial intelligence, and the method comprises the steps: data collection: collecting environment data and equipment state data of a transformer substation in real time through high-definition cameras and various sensors disposed around the transformer substation; data transmission: transmitting the collected data to a cloud computing platform for storage and processing; intelligent analysis: performing real-time analysis on the data transmitted to the cloud computing platform by using big data analysis and an artificial intelligence algorithm, and identifying potential external damage behaviors; performing early warning and response, triggering an early warning mechanism when an abnormal behavior is detected, and notifying operation and maintenance personnel; and data visualization and report generation: generating an operation and maintenance report, an alarm report and a risk analysis report for decision reference of operation and maintenance personnel and a management layer. Through the real-time monitoring and intelligent identification technology, the system can accurately capture abnormal behaviors inside and outside the transformer substation, effectively avoid external damage events, and significantly reduce safety risks.

The invention discloses a transformer substation intelligent monitoring system and method based on digital spasm, and relates to the technical field of digital spasm, the transformer substation intelligent monitoring system comprises a transformer substation information exchange hub, the transformer substation information exchange hub is in communication connection with an operation parameter monitoring module, a fault early warning module and a data visualization module; the parameter monitoring module collects temperature and current data of a transformer substation, the fault early warning module combines a simulation model and historical and real-time monitoring data, an LSTM model is used for early warning a fault, the data visualization module displays performance, trend and alarm, an LSTM is called to predict a load, and an algorithm is used for optimizing energy consumption, cost and load distribution. Intelligent monitoring of the transformer substation is achieved through the digital spasm technology, the accuracy and the real-time performance of monitoring are improved, the fault early warning precision and the load prediction capacity are improved through the LSTM model, meanwhile, the energy consumption, the cost and the load distribution are optimized through the algorithm, and the operation efficiency and the economic benefits of the transformer substation are effectively improved.

The invention relates to the technical field of coal mine safety monitoring, and discloses a coal mine heterogeneous data visualization processing method combined with artificial intelligence, and the method comprises the steps: collecting multi-source heterogeneous data above and under a coal mine to construct a real-time heterogeneous data matrix; feature categories are divided based on data dynamic relevance, and stable data areas are screened through a dynamic analysis window to generate an optimization matrix; performing pattern recognition on the unstable region to extract an abnormal data cluster, and calculating an abnormal feature factor of a data point; analyzing the feature distribution difference to generate a stable feature index, and calculating an abnormal risk value in combination with the distance, the abnormal feature factor and the stable feature index; and mapping the center coordinate of the stable region to a three-dimensional space of the coal mine, and positioning a key information region in combination with the abnormal risk value. An apparatus includes a memory, a processor, and a computer program. The coal mine heterogeneous data processing efficiency and the safety monitoring accuracy are improved, intelligent positioning of the key information area is achieved, and powerful support is provided for coal mine safety production.

The invention relates to the technical field of smart city data visualization, in particular to a visual smart city display method, which comprises the following steps: S1, collecting traffic flow data, energy consumption data, environment monitoring data and city three-dimensional geographic information data in real time; s2, constructing a reference three-dimensional model with a space coordinate system; s3, mapping the data into a dynamic data layer with a timestamp; s4, superposing the dynamic data layer to the reference three-dimensional model according to space-time coordinates to generate a fused dynamic scene; s5, receiving deduction parameters input by a user, and calculating a corresponding evolution path in real time; and S6, converting the evolution path into a dynamic visualization effect, and outputting the dynamic visualization effect to a display terminal. According to the invention, through integrated processing of multi-source dynamic data fusion, space-time path deduction and visual output, continuous expression and dynamic evolution display of the operation state of the smart city are realized.

The invention discloses a life cycle visual management method based on data, and relates to the technical field of data management. The method comprises the following steps: 1, data acquisition and identification; 2, classifying and dividing data life cycle stages; 3, data state monitoring and updating; 4, recording and associating data operation; step 5, constructing a data life cycle visual framework; step 6, data life cycle decision analysis optimization; 7, performing data archiving and deletion management; according to the invention, fine management of the whole life cycle of the data is realized, and the systematic method not only improves the efficiency of data processing, but also enhances the transparency of data management, so that managers can monitor the data state in real time, quickly respond to the data problem, optimize the data circulation process and improve the overall operation efficiency. Through application of a data visualization technology, complex data information is displayed in a visual and understandable form, and managers are helped to better understand data dynamics.

The invention provides a high-precision topographic mapping and three-dimensional modeling system based on an unmanned aerial vehicle, and the system comprises an unmanned aerial vehicle cooperation module which is used for deploying a multi-source sensor and a sensor electronic interface on the unmanned aerial vehicle, and building a distributed network of the unmanned aerial vehicle; the real-time dynamic positioning module is used for acquiring unmanned aerial vehicle positioning data and an initial target terrain map; the autonomous control module is used for generating a flight path, performing dynamic adjustment, constructing an autonomous flight control model and outputting a flight control instruction; the data quality enhancement module is used for performing parameter adjustment on the real-time data and performing space and signal level combined processing on the real-time data so as to enhance the data quality; and the terrain model optimization module is used for processing the laser radar point cloud data so as to construct a three-dimensional terrain model post-processing module, and carrying out data visual display and flight suggestion generation. According to the method, the positioning and modeling precision is greatly improved, efficient surveying and mapping are achieved, the single-point fault risk is reduced, and it is guaranteed that tasks can be completed in a high-safety, high-precision and intelligent mode.

The invention relates to the field of playing data visualization, in particular to a playing data visualization method and system. The method comprises the steps that at least one section of pedal data of at least one pedal is obtained, and the pedal data comprises a pedal value and a time stamp of the pedal value; generating at least one section of labeling track according to the pedal data; wherein the labeling track comprises a first simulation track and a second simulation track; correspondingly, the method comprises the steps that when the pedal value is larger than a first pedal threshold value, a first simulation track is generated according to the pedal value, and the first simulation track is displayed in a first labeling form; when the pedal value is larger than a second pedal threshold value and smaller than or equal to the first pedal threshold value, a second simulation track is generated according to the pedal value, and the second simulation track is displayed in a second labeling form; and generating a combined track according to the at least one section of labeled track, and displaying the combined track on the music score. According to the invention, the smoothness and integrity of pedal data display can be improved, and the user experience is optimized.