1535 results about "Data conversion" patented technology

The invention relates to the technical field of data processing, and discloses an industrial one-stop multi-source data acquisition and monitoring system and equipment, and the system comprises a data acquisition module which is used for obtaining multi-source industrial monitoring data and generating a data stream input node; the data preprocessing module is used for processing the input data in the data flow model to generate a standardized data flow; the data conversion module is used for dynamically converting data nodes in the standardized data stream according to different data protocols to generate a compatible data stream; the task scheduling module is used for optimizing the data flow and distributing the data flow to a target node according to the compatible data flow in combination with a node priority and a dynamic scheduling strategy in the data flow model; and the exception detection module is used for carrying out exception state analysis on the optimized data stream and judging whether an exception exists or not according to a preset rule. According to the technical scheme, the compatibility and reliability of the monitoring system can be improved.

The invention discloses a coastal port pile foundation structure load calculation method based on a coupling mode, and the method comprises the steps: a hydrodynamic module which evaluates the load and mechanical properties of a port pile foundation structure under different environment conditions; the water power module at least comprises an atmospheric mode module, a sea wave mode module, an ocean mode module and a coupler module; wherein the coupler module exchanges and synchronizes data among the atmosphere mode module, the sea wave mode module and the ocean mode module; the data conversion module is used for converting the wind field data, the wave field data and the flow field data obtained by the hydrodynamic force module into aerodynamic force and hydrodynamic force input files of the pile foundation structure; the finite element analysis module is used for receiving the aerodynamic force and hydrodynamic force input files, establishing a port pile foundation structure model and calculating stress distribution and displacement response of a pile foundation structure, and simulation results output by the finite element analysis module include but not limited to a stress nephogram, displacement field distribution and a buckling phenomenon of a pile foundation.

The invention discloses a multi-agent collaborative reasoning system for intelligent teaching intervention, and relates to the technical field of artificial intelligence and education, and the system comprises a data collection and convergence module which collects data of learning behaviors, emotional states, academic scores and knowledge point mastering conditions of students by means of a classroom behavior analysis system, a camera, a microphone and a learning management system; according to the intelligent teaching intervention-oriented multi-agent collaborative reasoning system, the precision and individuation of teaching intervention are realized by constructing the intelligent teaching intervention-oriented multi-agent collaborative reasoning system, the system collects multi-dimensional data of students through the data acquisition and convergence module, and through the processing of the data conversion and cleaning module, the accuracy and availability of the data are ensured; the teaching strategy planning module generates a dynamic decision model by means of a large language model, a customized intervention strategy can be generated according to the learning condition and problem root of students, and the multi-agent collaborative reasoning module further improves the intelligent level of the system.

The invention relates to the technical field of concrete pouring, in particular to a concrete pouring homogeneity detection system and method based on sensing data, and aims at achieving efficient and accurate concrete pouring homogeneity evaluation and defect detection. The system comprises a multi-sensor sensing module, a multi-sensor data conversion and transmission module and a concrete homogeneity evaluation module, the multi-sensor sensing module comprises a temperature sensor, an ultrasonic sensor and a vibration sensor; the multi-sensing data conversion and transmission module is used for acquiring multi-sensing data and performing data type conversion and transmission on the multi-sensing data; and the concrete homogeneity evaluation module is used for constructing a concrete pouring homogeneity evaluation model to detect and evaluate the homogeneity and defects in the concrete pouring process. According to the invention, detection and evaluation of the concrete pouring homogeneity are realized through combination of multi-sensing data, and the accuracy of detection of the concrete pouring homogeneity is improved.

The embodiment of the invention provides a multi-source heterogeneous data integration method and device fusing a large model conversion operator. The method comprises the steps that heterogeneous data are collected from a multi-source heterogeneous data source, preprocessing operation of data cleaning is carried out, and preprocessed data features are obtained; inputting the preprocessed data features and the target format into a large language model, and generating a conversion operator including data structure analysis, field mapping and type adaptation; and based on the conversion operator, performing distributed parallel data conversion and integration in a distributed computing framework, and integrating and verifying the integrated data. According to the scheme, by introducing the intelligent reasoning ability of a large language model, the efficiency optimization of distributed calculation and the quality verification mechanism of the whole process, the core problems of the traditional data integration technology in the aspects of rule stiffness, high manual dependency and quality control deficiency are systematically solved.

The invention discloses a real-time e-government affair platform based on big data processing, relates to the technical field of e-government affair platforms, and solves the problem of relatively large time delay in a data integration process caused by inconsistent data conversion rates. Based on different capacities corresponding to different formats of data and the conversion rate of the whole data in the format unification process, the conversion rate interval of related data is confirmed, then subsequent correlation confirmation of related completion time is carried out in the confirmed conversion rate interval, and subsequent correlation confirmation of the related completion time is carried out based on a computing power distribution mode. The data in the corresponding format tends to be consistent gradually in the related completion time, so that it can be fully guaranteed that related data converted by multiple different conversion processes can complete the related conversion process in a relatively consistent time period, it is guaranteed that the fusion rate is relatively high when subsequent data is fused, and the data waiting time of the corresponding government affair platform is shortened.

The invention relates to a multi-airport luggage full-process tracking method and system, and the method comprises the following steps: data collection, tag collection of temperature, humidity and acceleration data, obtaining of a luggage tag image by a high-definition camera, synchronization of airline flight dynamic information, collection of airport real-time operation data and passenger feedback, personalized demands, data conversion, and data processing. The method comprises the following steps: coding and converting into a sequence token suitable for large model processing, a multi-head attention mechanism, focusing luggage timeliness, equipment load and other key parameters according to a specific rule, cooperating an intelligent label with a block chain, dynamically optimizing sensor parameters, recording luggage key state information and performing personalized feedback, and performing automatic identification and path planning. The system combines computer vision and a multi-head attention mechanism to identify labels in real time and optimize a transfer path, virtualizes luggage accompanying service, provides intelligent interaction and immersive experience, performs cross-airport collaborative management, monitors global airport dynamics in real time, establishes a risk early warning model, and coordinates resources to execute a transfer adjustment scheme.

The invention discloses a heterogeneous data conversion method and system based on a multi-modal large model, and aims to solve the problems of single-modal limitation, high migration cost and the like in traditional heterogeneous data processing. The method comprises the following steps: firstly, carrying out format adaptation and classification preprocessing on multi-source heterogeneous data such as images, texts, audios and videos; then, through a ViT, BERT and Transform cross attention mechanism, deep analysis and cross-modal semantic association of visual, text and audio features are realized, and visual-text-audio semantic mapping is established; and based on a dynamic prompt project, guiding the multi-modal large model to generate structured data according to a preset Schema zero sample. And then error correction and format normalization are carried out through a Drools rule engine to ensure that the data meet the business standard. And finally, supporting multi-format output of JSON / XML / database table and the like, and meanwhile, associating original data storage to realize data traceability. According to the method, the limitation of single-modal processing is broken through, and cross-modal data deep association is realized.

The invention discloses a cross-platform equipment alarm information acquisition method, and particularly relates to the field of information acquisition, the method adapts to different platform equipment through a standardized interface layer, the interface layer comprises an equipment connection protocol library and a unified data conversion unit, and an original log of the equipment is analyzed in real time based on a preset alarm rule template; extracting key information and generating an alarm event object; converting the alarm key information into an alarm event in a unified format, and adding equipment identification metadata; alarm events are asynchronously transmitted to a central processing server by utilizing a high-reliability message queue, and the transmission reliability is guaranteed by adopting various mechanisms; performing duplicate removal, priority classification and persistent storage on the alarm events in the central server, and ensuring data consistency by adopting a hierarchical storage architecture; the whole processing link is provided with perfect monitoring indexes, and automatic capacity expansion and contraction are achieved.

The invention discloses a multi-modal feature fusion model construction method and a multi-step wind power prediction method, and belongs to the field of wind power prediction.The multi-modal feature fusion model construction method comprises the steps that firstly, two data conversion channels are added on the basis of a Grubrum angle field to construct a multi-channel Grubrum angle field, and wind power data are converted into RGB color images with color information; secondly, the time text features are embedded into the data features and the image features respectively, and the time sequence expression ability of the data features and the image features is improved; fusing the data features and the image features by using a cross-modal fusion method, and adjusting dynamic weights of the data features and the image features during fusion by using an adaptive decision mode to obtain fusion features containing different modal information; and finally, extracting association information between the fusion features and the wind power by using an encoder of the Transform, and decoding the input data into the wind power to be predicted by a decoder according to the association information and the prior data. A simulation experiment shows that the method effectively improves the prediction precision of the wind power.

The invention discloses a power distribution network fault identification method and device based on artificial intelligence, and the method comprises the steps: obtaining the multi-source fault characterization information of a power distribution network, and the multi-source fault characterization information comprises telemetering data and telecommand data; performing expert database-based normalization processing on the multi-source fault representation information to generate a standardized fault data sample; matching and checking the standardized fault data sample to generate checked fault data; performing graph data conversion processing on the checked fault data according to a power distribution network graph model to generate fault graph data; and based on the fault graph data, reasoning the fault of the power distribution network through the fault reasoning model to obtain the speculated fault of the power distribution network. The multi-source information is obtained, the limitation of a single channel is broken, data differences are eliminated through expert database normalization, data accuracy is guaranteed through matching checking, graph data conversion is associated with topology, artificial intelligence reasoning gets rid of manual dependence, and efficiency and accuracy are improved.

The invention relates to a medical data dynamic management method based on multi-modal data fusion and deep reasoning, which comprises the following steps: establishing a three-layer dynamic management architecture, collecting various medical data of a patient in real time through a bottom layer, performing primary processing on the various medical data of the patient, receiving the primarily processed medical data through a middle management layer, and performing dynamic management on the medical data through the middle management layer. The double-flow Transform network architecture performs medical event prediction, the event-driven architecture triggers a data processing flow, medical data after primary processing is subjected to dynamic extraction, data conversion, data loading and multi-modal data fusion processing, a data processing result is transmitted to the application layer, the application layer performs dynamic field generation, and the event-driven architecture performs multi-modal data fusion processing. And data automatic dynamic management and real-time feedback calibration are carried out based on a data fusion analysis result. The limitation of a static field structure existing in an existing medical data management SEER database is solved, the data quality is improved, automatic management and real-time feedback calibration of follow-up visit data are achieved, and separation of a follow-up visit system and a data management platform is avoided.

The invention discloses an intelligent glasses streaming voice dialogue interaction system and method based on a large language model, and the system comprises a data collection module which is used for collecting the interaction information of a voice dialogue between a user and intelligent glasses and the resource condition information of the intelligent glasses; the data conversion module is used for processing the interaction information by adopting a real-time streaming processing technology, adaptively selecting an interaction information identification model of a corresponding type, and converting the identified content into text information; the data processing module is used for receiving the text information, calculating a comprehensive score according to a preset scoring rule, matching and loading large language models configured by different models according to the comprehensive score, performing intention recognition and generating a reply text; the data interaction module is used for converting the generated reply text into voice and outputting the voice; and the data feedback module is used for receiving the feedback user interaction satisfaction so as to optimize the interaction information identification model or the large language model. According to the invention, efficient, accurate and smooth voice interaction experience can be realized.

The present invention discloses a distributed data integration method and system for multi-source device protocols, and relates to the field of data processing technology. The method comprises: connecting a protocol adaptation layer to perform data protocol adaptation and analysis of multi-source protocol data, and outputting conversion data; fusing distributed data in the conversion data to obtain monitoring data; obtaining abnormal warnings by detecting abnormalities in the monitoring data; performing data correction on the abnormal warnings, combining with normal data in the monitoring data, and encrypting and integrating the corrected data to obtain distributed integration results; constructing a distributed architecture with distributed data and distributed integration results, and storing and managing data. The method solves the technical problem of low data integration efficiency caused by incompatibility of multi-source device protocols in the prior art, and achieves seamless connection between different device protocols through protocol adaptation and analysis of the protocol adaptation layer, and fusion of conversion data, thereby achieving the technical effect of improving data integration efficiency.

The invention discloses a method for generating a railway optical cable path diagram, which comprises the following steps of: S1, inputting data, more specifically, inputting the data into an optical cable path data center so as to process the data; s2, data preprocessing: more specifically, preprocessing the input data so as to facilitate data conversion; s3, coordinate calculation / deformation conversion: more specifically, converting the related position data into coordinate positions; s4, generating a station yard optical cable path diagram, and more specifically, displaying the processed data in a drawing manner; and S5, planar graph output, more specifically, the drawings are output in different formats. According to the method, the drawing work of the optical cable path diagram can be greatly reduced, and the corresponding optical cable path diagram can be output only by inputting the collected data into the generation software realized by adopting the method.

The invention relates to the technical field of serial deserializer design, and discloses an FPGA-based direct-current balanced digital audio and video signal serial deserializer, which comprises a serializer, a deserializer, a control configuration module, a power management module, a configuration storage module and a time sequence control module, the serializer is used for converting parallel digital audio and video data into high-speed serial data streams; the deserializer is used for detecting and repairing abnormal data in the high-speed serial data stream by using a machine learning technology, and converting the repaired high-speed serial data stream back to parallel digital audio and video data; the control configuration module is used for configuring working parameters of the serializer and the deserializer through an external interface; the time sequence control module is used for managing the time sequence relation in the system and ensuring synchronization of data flow between different modules. According to the method, the defects of a traditional deserializer in the aspects of anomaly detection and repair, signal quality evaluation and parameter optimization are overcome, and the stability and quality of high-resolution digital audio and video data transmission are improved.

An analog-to-digital converter circuit incorporating includes a multi-bit input buffer having a differential input and configured to generate, at a plurality of differential outputs, a plurality of residues of a differential input sample relative to a corresponding plurality of zero-crossing references. Chopping stages chop the residues, for example with a pseudo-random binary sequence. The circuit further includes zero-crossing comparators, each with differential inputs coupled to receive one of the chopped residues. The zero-crossing comparators are in an ordered sequence of zone thresholds within the input range of the circuit. Folding logic circuitry has inputs coupled to outputs of the comparators, and outputs a delay domain signal indicating a magnitude of the one of the residues relative to a nearest zone threshold. Digital stage circuitry generates a digital output word representing the received input sample responsive to the comparator outputs and the delay domain signal.

The invention provides an A320 model original QAR data frame structure compiling engine and method, and belongs to the field of civil aviation. The engine adopts a multi-node transverse deployment and distributed computing architecture, and comprises four modules: an original file reader, an original data standardizing device, a data converter and an engineering value data writing device, the original file reader is used for reading an original RawData file sent by external aviation software; the original data standardizing device is used for converting an original RawData file into a new standardized RawData file; the data converter decodes the new standardized RawData file according to a decoding rule to obtain plaintext engineering value data; and the engineering value data writer writes the plaintext engineering value data into different storage media. The method is suitable for large-scale, multi-source and heterogeneous flight data processing scenes, and the data processing efficiency and the system performance can be remarkably improved.

An operation accelerator that performs an operation between a floating point matrix and an integer matrix includes a first buffer storing integer matrix data; a second buffer storing floating point matrix data; a data converter to convert the floating point matrix data into an integer; and an operator to perform multiplication on the integer matrix data and integer operation target matrix data output from the data converter, wherein the data converter includes a pre-aligner to find a maximum exponent value among multiple floating point values included in the floating point matrix data, perform pre-alignment for moving a mantissa of each of floating points by a difference between the maximum exponent value and an exponent value of each of the multiple floating point values, and generate the integer operation target matrix data based on mantissas of a preset number of high-order bits extracted from among mantissas of pre-aligned floating point values.

The invention provides a sound classification target model construction method and system, and relates to the technical field of sound signal processing, and the method comprises the steps: obtaining original sound data and auxiliary modal data, carrying out the sound data conversion processing of the original sound data, and obtaining corresponding multi-resolution sound image data; processing the auxiliary modal data to obtain a corresponding auxiliary modal space-time matrix; performing local feature processing on the multi-resolution sound image data and the auxiliary modal space-time matrix to obtain local sound image features and auxiliary modal features; constructing a hierarchical feature sequence space according to the local sound image features and the auxiliary modal features, and obtaining a corresponding fusion feature sequence; and constructing a sound classification target model according to the fusion feature sequence, and generating a dynamic sound index according to the sound classification target model, thereby obtaining a sound classification result, and improving the accuracy of sound classification.

A display device may include a display panel which includes pixels, a data driver which provides data voltages corresponding to output image data to the pixels, and a data converter which generates a compensation grayscale from reference compensation values for compensating at least one selected from a color shift and a luminance shift corresponding to a temperature based on an input temperature, an input grayscale included in input image data, and an input luminance, and converts the input image data into the output image data based on the compensation grayscale.

The invention provides a structured data representation method, a structured data conversion method, a structured data scheduling method, a structured data conversion device, a structured data scheduling device, a structured data conversion system, a medium and electronic equipment. The representation method comprises the following steps: responding to an operation of dragging a module from a module library to a visual editing canvas by a user to form a node corresponding to the dragged module; responding to the operation that a user establishes visual connection between input ports and output ports of different nodes on the canvas to form edges, wherein the edges define a data flow and calculation dependency relationship between the nodes; a structured data representation of a machine-readable AI model structure is generated based on all the nodes on the canvas and user-configured parameters thereof, and a set of edges defining the edge interconnection relationship. According to the representation method, conversion from graphical representation to structured data of the artificial intelligence model is completed.

The invention provides a verification method and device of a chip register, equipment and a medium. The verification method comprises the steps of obtaining parameter information of a register in a to-be-verified chip and processing the parameter information to obtain data in a set format; based on the data in the set format, register related files containing different set values are generated through scripts; and integrating the register related file into a verification environment through the script so as to automatically verify the register in the chip to be verified according to different set values. According to the technical scheme, the data in the set format is converted into the register related file through the script, the verification efficiency is improved, the verification reusability can be improved, the chip register is verified through different set values, full verification of the chip register can be achieved, and the accuracy of register mapping problem detection is improved.

The invention discloses a magnetic suspension rotor system model identification method and system based on a frequency response model, and the method comprises the steps: exciting a magnetic suspension rotor system through a harmonic signal, and collecting a time domain signal data sample under each input / output channel generated through excitation in the magnetic suspension rotor system in real time; converting the time domain data sample into frequency domain data to form a frequency response data set for model identification; performing unbiased estimation on the frequency response data set by adopting an optimization algorithm, and establishing an empirical transfer function estimation model; and evaluating the precision of the empirical transfer function estimation model by using a normalized root mean square error, and comparing the predicted output of the model with the time domain signal data sample to verify the accuracy and reliability of the model. Through precise harmonic excitation and real-time data acquisition, in combination with a data conversion technology, time domain signals are effectively converted into frequency domain data, and the efficiency and accuracy of performance analysis and control design of a magnetic suspension rotor system are remarkably improved.

The invention provides a multi-database automatic synchronization method under an AI platform, and belongs to the technical field of database automatic synchronization. The captured change records are converted into synchronous messages in a unified format, the synchronous messages are input into an intelligent scheduling optimization model for dependency analysis and transaction reordering based on dynamic programming, data conversion rules are dynamically generated according to mode version differences, and data consistency is verified through a Merkle tree hierarchical structure; the multi-stage self-adaptive compression transmission and data writing are completed after the target node executes conflict detection and circular dependency processing, and finally the final consistency among the multiple databases is guaranteed through a periodic full-amount account checking task, so that the technical problem of synchronization performance bottleneck caused by low transaction scheduling efficiency in the automatic synchronization process of the multiple databases is solved.

The invention relates to the technical field of fault diagnosis, in particular to a power distribution network fault intelligent positioning and response system, which comprises a data conversion module, a power distribution network fault intelligent positioning and response module, a power distribution network fault intelligent positioning and response module, a power distribution network fault intelligent positioning and response module and a power distribution network fault intelligent positioning and response module, the voltage fluctuation and the circuit breaker state are represented, and power distribution network graph data are generated. According to the invention, through converting the operation data of the power distribution network into the point cloud and utilizing a persistent coherence method, topology analysis is carried out on the power grid state, and through capturing and analyzing changes of rings and holes in graphic data, topology changes related to voltage fluctuation and load abnormity are identified, so that the accuracy of fault diagnosis and the perspectiveness of fault prediction are improved; fault points are monitored in real time, time sequence analysis is adopted to predict the time and place of potential faults, the fault response speed and precision are accelerated, and stable operation of the power system is enhanced through a data analysis and prediction mechanism.

A modulation signal processing apparatus and method is provided. The apparatus is applied to a microcontroller unit. The apparatus includes a first signal processing module and a second signal processing module. The first signal processing module is connected to an analog-to-digital converter of the microcontroller unit, and used for receiving a completion mark output by the converter, collecting a conversion value output by the converter, and generating corresponding bit data according to a total number of sampling times and a preset half-cycle value. The second signal processing module is connected to a PWM output timer of the microcontroller unit, and used for converting the bit data into a modulation data packet that complies with a Qi protocol, and respectively calculating a reload value of the PWM output timer and a corresponding frequency modulation parameter according to the modulation data packet and a preset modulation configuration parameter.

The invention discloses a spatial data format conversion method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining and analyzing to-be-converted spatial data, and determining geometric type information and dimension information of the to-be-converted spatial data; determining target type information according to the geometric type information; and performing format conversion on the to-be-converted spatial data according to the target type information and the dimension information to form target spatial data, thereby solving the problem of relatively low spatial data format conversion efficiency, determining the geometric type information and the dimension information of the to-be-converted spatial data by analyzing the to-be-converted spatial data, determining the target type information, and performing format conversion on the to-be-converted spatial data. Different types of to-be-converted spatial data are converted in different modes, format conversion is directly performed on the to-be-converted spatial data based on the target type information and the dimension information to obtain the target spatial data, conversion into an intermediate structure body is not needed, the conversion efficiency is improved, the spatial data conversion complexity is reduced, and the user experience is improved. And data conversion can be directly realized.

The invention relates to a construction method of a coefficient prediction model, a coefficient prediction method and a storage medium, and the construction method comprises the steps: carrying out the modeling of a bridge prestressed beam through finite element numerical software, simulating a tensioning process, constructing a bridge parameter coefficient array, dividing the bridge parameter coefficient array into a training data set and a verification data set, performing data standardization and tensor data conversion, and constructing a data loader; an AND-based full-connection multi-layer multi-task neural network is constructed, and a standardizing device, a forward propagation function, a loss function, a learning rate scheduler and an optimizer are arranged; and carrying out model training, packaging a prediction function, and integrating a standardizing device and the trained prediction model. The prediction method comprises the step of predicting the friction resistance loss coefficient and the pipeline deviation coefficient according to the prediction model. According to the method and the device, coefficient prediction can be quickly, efficiently and accurately realized by only needing several on-site easy-to-measure parameters.

The present invention relates to the technical field of power systems. Disclosed is a relay protection external operation information intelligent management system, comprising: an input module, a data snapshot module, a data acquisition module, a data conversion module, a data storage module, a fault analysis module, a report generation module, a signaling alarm module, a data analysis module 0, and a real-time data calling module. The relay protection external operation information intelligent management system provided by the present invention provides multiple reliable data interaction modes, including wired transmission, wireless transmission and calling of other systems, for relay protection external operation information, and collects and analyzes the relay protection external operation information before a fault so as to provide powerful support for fault analysis of dispatchers and secondary personnel, thereby avoiding erroneous analysis and determination on the fault. The present invention achieves better effects in the aspects of applicability, network occupation and system cooperation.