95 results about "Automatic Data Processing" patented technology

The invention relates to the technical field of calibration test, and particularly discloses a strapdown inertial navigation automatic calibration test method of a temperature control biaxial rate position turntable. Comprising the following steps: S1, multi-dimensional error modeling and layered calibration architecture: constructing a comprehensive error model containing a sensor scale factor error, an installation non-orthogonal error, a zero offset error, a cross axis coupling error and a temperature related error; s2, a wide temperature range self-adaptive compensation mechanism: carrying out heat preservation at a preset temperature point and executing turntable positioning and rate movement; s3, performing automatic data processing and parameter estimation; and S4, performing real-time error correction and dynamic verification: performing real-time error correction based on the estimated parameters, and evaluating navigation performance indexes such as position, speed and attitude precision. Through technical innovation, high-precision, automatic and wide-temperature-range calibration of the strapdown inertial navigation system is realized, and the method is suitable for aerospace, intelligent equipment and other scenes with strict navigation precision requirements, and has remarkable engineering application value and market competitiveness.

The invention discloses a large model enhanced telephone fraud high-risk user identification method and system, and relates to the technical field of artificial intelligence and information security. The objective of the invention is to improve the accuracy of telephone fraud identification by means of multi-level automatic data processing, multi-model training optimization and multi-model probability fusion, and can significantly reduce the calculation cost and resource consumption. According to the technical key points, a multi-dimensional feature system is constructed by analyzing call data of a user; through multi-model training optimization, high-risk probabilities of different models for different users are obtained, multi-level features of user behaviors are deeply mined, and a machine learning model, a deep learning model and a large language model are covered; the output probability values of a plurality of models are combined through a Stacking voting integration method, and the advantage of each model is utilized to prevent a single model from falling into a local optimal solution. According to the method, advantages and characteristics of different models are effectively integrated, and the overall performance and robustness of an identification system are remarkably improved. According to the method, the fraud identification accuracy is improved, and the calculation cost and the resource consumption are remarkably reduced.

The invention discloses a spring probe system for rapid registration of articular cartilage based on 3D printing, and relates to the technical field of medical imaging and orthopedic surgery navigation. The problem that the joint registration precision is insufficient due to the fact that cartilage cannot be developed in traditional CT imaging is solved. Through personalized customization of the 3D printing guide plate, convenient installation of positioning holes, adjustability of the spring probe assembly and real-time data monitoring, and automatic data processing of the intelligent registration module, manual operation is reduced, the operation efficiency is improved, the spring probe assembly is reasonable in structure and adjustable in elastic force, stable operation of the system in an operation is guaranteed, and the operation safety is improved. Multi-position CT scanning is combined with an advanced image processing and registration technology, an accurate initial model is constructed, a spring probe assembly collects data and is combined with an elastic deformation compensation model to correct registration errors in real time, the registration accuracy is improved, reliable support is provided for orthopedic surgery navigation, the surgery success rate can be improved, and patient wounds and surgery risks are reduced.

The invention relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, and a multi-task prediction model based on multi-source historical business chain data training graph neural network and Transform fusion. A plurality of groups of lane layout and event configuration schemes are generated in combination with user real-time operation captured by a design interface, an optimal scheme is screened through simulation evaluation and then is visually displayed, finally, visual lane modeling is executed according to user feedback, and through automatic data processing, high-precision model prediction, real-time interaction optimization and visual modeling, the optimal lane layout and event configuration scheme is obtained. According to the method, the service chain design efficiency and quality are improved, meanwhile, artificial experience deviation is avoided through model prediction based on historical data, the comprehensive requirements of complex equipment development for real-time performance, reliability and resource efficiency are met, and efficient technical support is provided for landing of model-based system engineering in the field of complex equipment.

The invention belongs to the technical field of IT type project cost financial management, and discloses an IT type project cost financial independent accounting system, which comprises a project management module, a receivable management module, a payable management module, a purchase management module, a financial system data exchange module, a human resource data exchange module and an early warning management module. According to the system, integrated management is adopted, project cost is monitored in real time and dynamically adjusted, the system collects and updates cost data in real time, rapid adjustment is carried out once deviation is found, it is ensured that the cost is controlled within a prediction range, project management flexibility and response speed are improved, cost hyper-branched risks are reduced, and meanwhile through automatic data processing and accounting processes, the project management efficiency is improved. The cost accounting accuracy and efficiency are remarkably improved, personal errors are avoided, manual calculation is simplified, a project manager can efficiently master the cost condition, powerful data support is provided for project decision making, and the scientificity and effectiveness of project management are ensured.

The present invention discloses a method for generating a rotor fault diagnosis model based on multiple transform domains and a diagnosis method. The former includes: collecting vibration signal data of a modular rotor fault of a gas turbine in multiple categories to construct a training and test data set; transforming each data to the short-time Fourier time-frequency domain using the STFT transform domain, transforming it to the Morlet wavelet time-frequency domain using the Morlet wavelet transform domain, and transforming it to the complex network phase space domain using the complex network recurrence plot method; inputting the training data set transformed by the three transform domains into a preset model, and using the CNN network layer for feature extraction; using the LSTM network to perform feature structure learning on the output features, and training to obtain a rotor fault model; using the test data set transformed by the three transform domains to verify and adjust the rotor fault model to obtain a rotor fault diagnosis model for fault detection. The present invention can realize automatic data processing, reduce manual input, and improve the efficiency and accuracy of fault diagnosis.

The invention discloses an online car-hailing driver fatigue driving pre-judgment method and system. The invention relates to the technical field of online car hailing. And collecting driver departure data O and driver order receiving data M which are arranged according to a time sequence. O = [O1, O2,..., ON]; m = [M1, M2,..., MN]; o1, O2,..., ON and M1, M2,..., MN are historical data of driver departure data O and driver order receiving data M respectively. Executing exponential smoothing according to the trend and the seasonality of the driver departure data O and the driver order receiving data M in the time sequence; by adopting the Holt-Wittes seasonal model, the method can accurately capture the periodicity and tendency characteristics of the driving and order receiving behaviors of the driver, and significantly improves the prediction accuracy. The automatic data processing and prediction process greatly shortens the prediction period, improves the operation efficiency, and enables the platform to respond to the potential risk of fatigue driving of the driver more quickly.

The invention relates to the technical field of automatic data processing of integrated circuit design, in particular to an automatic parasitic parameter result analysis system based on an FUZZ test. The fuzzy test engine module adopts syntax tree variation to generate a test case library comprising illegal characters, extreme values and logic loops, the exception response module captures illegal operations in an analysis and simulation stage through the probe detection unit, and the correction decision unit executes data restoration or generates an exception report. And the incremental updating unit synchronizes the abnormal features to a model self-optimization module rule base. And the dynamic adaptation module converts the multi-process parasitic parameters into a standardized simulation model through the process parameter abstraction layer. All the modules form a closed-loop system for test case generation, anomaly detection and repair and rule dynamic optimization, automatic processing of an unexpected input scene is achieved, and robustness and multi-process compatibility of parasitic parameter analysis are improved.

According to the rocket flight result rapid evaluation method, rocket flight data can be processed, an interpretation report is automatically generated, and working state rapid interpretation of pre-cooling before launching of a liquid rocket engine, fault diagnosis before ignition and in the flight process is achieved. According to the rapid judgment method for the rocket flight result, the analysis efficiency can be remarkably improved, and the time from the end of rocket flight to the obtaining of the engine analysis result is greatly shortened through automatic data processing, analysis process and rapid report generation. According to the evaluation method, the standard interpretation report is automatically generated, the problems of low manual analysis efficiency, incomplete analysis and the like are solved, and powerful support is provided for evaluation and improvement of rocket launching tasks.

The present application relates to the technical field of automatic data processing, in particular to a dynamic resume evaluation method based on a multi-modal large model. The method comprises: receiving a file containing the resume information of an applicant and a portfolio containing one or more visual works of the applicant; based on the file containing the resume information of the applicant, analyzing the file using a resume analysis module to generate a resume score; based on the portfolio of the applicant, analyzing the portfolio using a portfolio analysis module to generate a portfolio score; based on the file containing the resume information of the applicant and the portfolio of the applicant, calculating a consistency score using a consistency analysis module; and fusing the resume, portfolio and consistency scores to generate a final matching degree score to determine the matching degree of the applicant and the post. The present application solves the problem that traditional methods cannot evaluate visual materials and verify the authenticity of resumes, and provides a more accurate, objective and comprehensive candidate screening scheme.

The application relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, wherein a multi-task prediction model of a graph neural network and a Transformer fusion is trained based on multi-source historical business chain data, a plurality of groups of lane layout and event configuration schemes are generated in combination with real-time operations of a user captured by a design interface, the optimal scheme is selected through simulation evaluation and filtering, and visual display is performed, and finally, visual lane modeling is executed according to user feedback, through automatic data processing, high-precision model prediction, real-time interactive optimization and visual modeling, the design efficiency and quality of a business chain are improved, meanwhile, model prediction based on historical data avoids artificial experience deviation, meets the comprehensive requirements of real-time performance, reliability and resource efficiency for complex equipment development, and provides efficient technical support for the landing of model-based system engineering in the field of complex equipment.

The invention discloses an overflow method substrate glass indentation detection device and a real-time monitoring method thereof, and belongs to the technical field of overflow pull-down method substrate glass manufacturing. The device is composed of a real-time monitoring device, a fixing and position adjusting device, a cooling shell and the like, the indentation width change of annealing furnace opening substrate glass is monitored in real time through image analysis, and automatic processing and early warning of data are achieved in combination with a DCS. The device is light in design, anti-interference and suitable for a high-temperature environment, and a cooling shell ensures stable operation of equipment. The invention provides a safe and efficient detection method, solves the pollution risk and safety problem caused by manual detection, improves the production yield and efficiency, reduces the cost, is suitable for a TFT-LCD substrate glass production line, and has important application value and wide prospects.

The present application relates to a semiconductor factory production data analysis and presentation method and system based on multi-agent cooperation. First, access to multi-source heterogeneous production data and standardization processing. Subsequently, a plurality of serial special ability agents are executed in turn: data agent classifies and stores data; aggregation analysis agent performs cross-system calculation to generate comprehensive indicators; scene recognition agent matches real-time data with preset rules to identify the current running scene; key parameter recommendation agent outputs a sorted key parameter list according to the scene. Finally, the scene, indicators and parameter list are integrated and visualized through a leadership cockpit with natural language interaction function, and can respond to user queries to trigger reanalysis. Through agent cooperation, the present application realizes automatic data processing, scene recognition and dynamic key parameter recommendation, and solves the technical problem of quickly focusing on core production problems from isolated data.

The invention relates to the technical field of aeroengines, and discloses a method and system for diagnosing gas path faults in the starting process of an aeroengine. The method and system for diagnosing gas path faults in the starting process of an aeroengine are used to obtain a mapping relationship between an assessment parameter and a converted speed in a historical starting process, construct an envelope of the assessment parameter, and judge whether the assessment parameter at the converted speed during the test exceeds the envelope, so as to judge whether the engine starting test is a normal start. The method and system for diagnosing gas path faults in the starting process of an aeroengine of the invention can realize automatic data processing, reduce data processing time and debugging times, and provide a basis for adjusting the starter power in a speed range or optimizing the starting fuel supply law.

The application provides a complex document intelligent extraction method, system and device based on a multi-modal large model and a storage medium, and relates to the technical field of automatic data processing and information extraction. The disclosed technology provides an efficient, accurate and self-optimizing information extraction solution, which includes a combination of technologies: a two-stage extraction strategy using preliminary screening and deep information extraction balances the efficiency and depth of information extraction; a cross-page dependency graph construction mechanism solves the problem of information fragmentation; a context-aware overall information extraction method ensures that the model reasons in a complete visual context; dynamic task decomposition and dimension reduction techniques are also used to address performance challenges caused by complex tasks; and a prompt word self-optimization closed loop based on artificial feedback is used to achieve continuous learning and precision improvement of the system.

Computerized systems and methods are described for managing vendor-independent configuration-on-order (CTO) and offer-on-order (QTO) processes. A real-time data grid (RTDM) is provided for aggregating, normalizing, and normalizing real-time data from different sources. A single pane view user interface (SPoG UI) facilitates dynamic interaction and visibility to vendor performance. An advanced analysis and machine learning (AAML) module analyzes product compatibility, optimizes a pricing strategy and predicts a market trend. A vendor independent CTO / QTO integration module (VACIM) includes a process standardization engine and a vendor data conversion gateway to ensure consistency of different vendors. According to the method, automatic data processing and data conversion gateway integration are carried out to ensure data consistency, and decision making is carried out by adopting a rule engine driven by machine learning, so that a retailer process is simplified in an extensible and high-adaptability framework, the expandability is enhanced, and a pricing strategy is optimized.

The application relates to a TTV automatic test system and a test method, which comprise a single-channel heating power module, a single-channel temperature acquisition module, a 100-channel power control array, a 100-channel temperature acquisition module array, a system control industrial computer; the single-channel heating power module realizes independent heating control on a single heating unit of a test product; the single-channel temperature acquisition module independently acquires temperature signals of corresponding areas; the 100-channel power control array and the 100-channel temperature acquisition module array realize centralized management and synchronous control on more than 3000 heating channels and temperature acquisition channels. Through multi-channel power array control, array type temperature acquisition and industrial bus centralized control architecture, the application realizes controllable and adjustable heating power, real-time temperature acquisition and automatic data processing, improves data acquisition density, supports millisecond-level transient temperature acquisition, improves test efficiency and reduces test cost.

The invention discloses an SF6 multi-component mixed gas liquefaction temperature detection method and system based on a laser scattering method. The system comprises a high-pressure visual cavity, a temperature and pressure control system, a laser light source, an optical signal detection system and a data acquisition and processing unit. The design of the high-voltage visual cavity simulates the working condition of actual electrical equipment, and the measurement result has higher engineering reference value; non-contact measurement is realized by means of optical detection, and subjectivity of manual observation in a traditional method is avoided; the automatic data processing flow improves the measurement efficiency and repeatability, and is especially suitable for continuous monitoring requirements of multi-element mixed gas. The method provides a reliable technical scheme for solving the practical problem of SF6 mixed gas liquefaction temperature monitoring in power equipment.

The invention discloses a steel wire rope intelligent detection crawling robot and a detection method thereof. The steel wire rope intelligent detection crawling robot comprises a robot frame and a robot body. The robot body comprises a detection probe assembly, a plurality of crawling roller assemblies, a driving control unit, a data processing unit, a power supply unit module, an encoder assembly and a safety rope ring assembly, the driving control unit is used for controlling the crawling roller assemblies to crawl along a to-be-detected steel wire rope, and the detection probe assembly is used for conducting magnetic flux leakage detection on the to-be-detected steel wire rope; the data processing unit is used for collecting, analyzing and storing magnetic flux leakage detection data, the power supply unit module is used for supplying power, and the encoder assembly is used for obtaining crawling data of the robot body; the safety rope ring assembly is used for being connected with a safety rope to prevent the robot body from falling from the to-be-detected steel wire rope. Through intelligent detection, automatic data processing and data storage in the autonomous crawling process, intelligent detection of damage of the steel wire rope is achieved.

The invention discloses an intelligent prediction method and system for operation platform operation and maintenance data, and the method comprises the steps: firstly, widely collecting all kinds of operation platform operation and maintenance data closely related to a prediction object, and carrying out the cleaning and preprocessing of the collected data; secondly, for the processed data, automatically extracting features with key value for a prediction task from the original data through a machine learning algorithm; then, on the basis of the extracted data features and a specific prediction target, a prediction model is constructed on the basis of a machine learning algorithm; training the prediction model by using historical data to obtain a trained prediction model; inputting new operation and maintenance data into the trained prediction model for prediction and evaluation; and finally, performing real-time response processing on the generated prediction result. According to the scheme, the intelligent prediction model for the operation and maintenance data of the operation platform is formed based on fusion of automatic data processing and a machine learning model, and efficient and accurate prediction for the operation and maintenance data generated by the operation platform can be realized.

The invention provides a real-time monitoring and processing method and system for impact resistance test data of foam concrete and application, and relates to the technical field of material detection.The method comprises the steps that a high-speed camera collects a process image of a drop hammer impact foam concrete test block in real time, and image data is transmitted to a control end; the control end identifies the position of the drop hammer relative to the leveling rod in each frame of image in the process image, calculates the impact depth of the drop hammer and determines the impact time of the drop hammer; according to the impact depth and the impact time, the impact speed and the impact energy of the drop hammer are calculated; based on the change relation of the impact speed, the impact energy and the impact depth, an impact response curve is generated, and the impact resistance parameters of the foam concrete are output. According to the method, the impact process can be accurately monitored in real time, quantitative and objective impact resistance parameters are output through automatic data processing, and the problem that in the prior art, a method for quantitatively testing the impact resistance of foam concrete is lacked is solved.

The present invention relates to the field of data processing, and particularly to a method and device for automatic data processing and display based on an ERP system, which includes: obtaining source data in real time and extracting target data from the source data; determining whether the target data meets the configured conditions, and when the target data meets the configured conditions, classifying the attributes of the target data according to the attribute criteria to obtain real-time data subsets for each attribute; obtaining the historical total data subsets for each attribute, constructing a verification model based on the historical total data subsets, and inputting the real-time data subsets for each attribute into the corresponding verification models respectively, and analyzing whether there are errors in the real-time data subsets of each classified attribute through the corresponding verification models; when the verification models analyze that there are no errors in the real-time data subsets of each classified attribute, fusing the real-time data subsets of each classified attribute with the historical total data subsets of the corresponding classified attributes according to the statistical period; and displaying the statistical data based on the updated statistical data.

The invention relates to the technical field of visual media data backup, and discloses a visual media data backup method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the information of each high-speed write-in port and a common port through main equipment, and interacting with a specified terminal through a user-defined protocol, and then, on the basis of a write-in scheme generated by the reading instruction, a personalized processing scheme is formulated for each piece of to-be-backed-up data to ensure that the data is backed up. The method has the advantages that the data backup and transmission efficiency is improved through the user-defined protocol, the increasing image and video data requirements are met, compared with a traditional manual backup mode, the automatic data processing flow is provided, and the data loss or damage risk caused by manual operation is remarkably reduced.

The invention relates to the technical field of three-dimensional modeling, and particularly discloses a method and system for quickly generating a building three-dimensional white model, and the method comprises the following steps: obtaining an image region range, and determining a target region in a manner of manually dragging a base map of a map and inputting a place name or latitude and longitude coordinates by a user; extracting the contour of the building and obtaining space coordinate information, analyzing the remote sensing image of the target area by using an AI image recognition algorithm, automatically extracting the contour information of the building, and reading the corresponding space coordinate data to obtain the contour data of the building; and cleaning the contour data, endowing the contour data with a height value, and cleaning the extracted building contour data. Through an AI image recognition algorithm and an automatic data processing flow, the generation time of the building three-dimensional white mold is greatly shortened, and the problem that a traditional method is long in consumed time is solved.

The utility model discloses an overflow early warning device for a liquid-gas separator. The overflow early warning device comprises a liftable base, a mass flow monitoring assembly, a shunting assembly, a controller and an alarm, the novel overflow early warning device can be connected with an anti-overflow pipe outlet, a vibrating screen or a liquid-gas separator to form a complete drilling fluid circulating system, in the well drilling and completion operation process, all-weather and real-time monitoring of weak changes of outlet flow is achieved through the mass flow monitoring device, meanwhile, the whole set of drilling parameters and drilling fluid performance parameters on the drilling site are integrated, and the drilling efficiency is improved. Through automatic data processing of the controller, changes of different drilling parameters and drilling fluid performance parameters under different working conditions are discriminated, and when a set well leakage or overflow safety threshold value is reached, sound and light alarming is carried out, and early warning of the risk of well leakage or overflow is achieved.

The application provides a ship voyage track generation method based on STK and MATLAB combined simulation, comprising: setting a random seed, initializing an STK environment through MATLAB, and loading a set simulation scene; under the simulation scene, randomly selecting a ship model needing to be simulated, and setting a corresponding type, attribute and speed for each ship model; using a random algorithm to generate a starting point and an ending point of each ship model, using an interpolation method to generate continuous and diverse path points, and through dynamic propagation of the path points, updating a voyage track of the ship model in real time. The application not only improves the efficiency and practicability of the voyage track simulation, but also greatly improves the convenience and accuracy of the voyage track data analysis through automatic data processing and output functions, and is suitable for fields of ocean research, navigation safety evaluation, channel planning, military and education training and the like.

The invention belongs to the technical field of data processing, and particularly relates to a statistical report automatic data processing method which comprises the following steps: S1, a task engine: analyzing a user historical operation record through a manual or machine learning algorithm, and coding a table operation mode commonly used by a user; s2, a real-time monitoring and feedback mechanism: when the system executes an automatic task, when an exception is found, the system automatically pauses or reminds a user to intervene, so that the accuracy and the safety of data processing are ensured; and S3, expansibility and compatibility: the system supports mainstream spreadsheet software and form files in different formats, and provides an API interface at the same time, so that integration with other office systems is facilitated, and wider application scene coverage is realized. According to the method, the form task mode defined by the user can be automatically identified, and the repeated operation can be automatically executed or assisted to be efficiently completed by the user, so that the office efficiency is remarkably improved, human errors are reduced, and the employees can put more energy into more creative and decisive work.

The invention relates to an automatic data processing method and system. The method comprises the following steps: S1, constructing an ETL task generation rule base; s2, automatically generating an ETL task according to a user request; s3, deploying and executing an ETL task; and S4, performing configuration information persistence and state monitoring feedback. According to the method, the ETL task generation rule base can be constructed to realize logic rule solidification, the XML file is automatically generated, deployed and executed according to a user request, meanwhile, the information is persistently configured, the task state is monitored, automatic generation, execution and log monitoring of the ETL task are realized, end-to-end and whole-process ETL templating and automation are realized, and the efficiency is improved. The problems of repeated configuration, high technical threshold and lack of intelligent multiplexing in a traditional development mode are solved, and the method has the advantages of improving the development efficiency, reducing the error rate and enhancing the deployment standardization degree.

The invention relates to the technical field of data processing, in particular to an automatic data processing system and terminal equipment, and the system comprises a multi-source data collection module which is used for collecting a multi-source data by using a preset dynamic start-end time screening strategy and employee basic information obtained from a first structured database; screening historical attendance data obtained from the second structured database to obtain effective attendance data; the identification module is used for identifying the shift type of each employee in the effective attendance data according to the week characteristics and the on-off time characteristics; the data integration module is used for integrating each piece of employee information, the corresponding shift type and the corresponding effective attendance data in the employee basic information to obtain to-be-processed employee information; the determining module is used for determining follow-up personnel corresponding to each shift type in the target shift arrangement period from the to-be-processed employee information according to the position requirements and the multi-rule cooperation principle, and generating a shift arrangement table, and the problems of low shift arrangement efficiency, poor reasonability and poor adaptability can be solved.

The invention provides a complex document intelligent extraction method, system and device based on a multi-modal large model and a storage medium, and relates to the technical field of automatic data processing and information extraction. According to the technology disclosed by the invention, an efficient, accurate and self-optimized information extraction solution is provided, and the method comprises a group of technical combinations: a two-stage extraction strategy of preliminary screening and depth information extraction is utilized to balance the efficiency and depth of information extraction; the problem of information fragmentation is solved by utilizing a cross-page dependency graph construction mechanism; a context-aware overall information extraction method is utilized to ensure that the model carries out reasoning in a complete visual context; a dynamic task decomposition and dimension reduction technology is utilized to deal with performance challenges brought by complex tasks; and a cue word self-optimization closed loop based on manual feedback is utilized, so that continuous learning and precision improvement of the system are realized.