125 results about "Error identification" patented technology

The invention relates to an error collaborative calibration method, system and device based on a high-precision rotary table, and the method comprises the steps: obtaining the installation positioning data of a tilt angle sensor, carrying out the installation offset calibration of the high-precision rotary table, and obtaining an installation parameter set; according to the installation parameter set, controlling the high-precision turntable to carry out partition inclination angle scanning on the inclination angle sensor to obtain calibration response data; performing multi-source error identification on the calibration response data to obtain a collaborative error parameter set; and obtaining a dynamic simulation instruction template according to the tilt angle sensor, and performing instruction construction on the dynamic simulation instruction template and the collaborative error parameter set to obtain a turntable swing instruction set. Tracking errors caused by static calibration parameters can be avoided, and the execution precision of the rotary table in complex motion control is improved.

The invention discloses a complex text OCR (Optical Character Recognition) error recognition and repair method based on a large language model, and relates to the technical field of text processing, the method comprises the following steps: step 1, a text preprocessing module recognizes and excludes a non-text area in a preliminary text result generated by OCR to ensure that residual content is pure text input, and a text preprocessing module is used for preprocessing the residual content; obtaining a text result of the plain text data; step 2, an error recognition module performs entity recognition on a text result of the plain text data by using a large language model, and provides revision suggestions for recognized suspected errors; 3, the database provides knowledge recall for the recognized entities and errors, and supplementation is provided for follow-up repair; and 4, correcting errors in a text result of the plain text data by an error repairing module through the acquired context information and supplementary data provided by the database, and outputting a document.

The invention provides a self-error-correction retrieval enhancement agent system. Firstly, error detection is carried out on RAG generation content through a trained retrieval enhancement error correction model, then error features are input into an agent model to carry out automatic planning of a solution, and finally a closed-loop process of error correction is completed through an execution engine. In the aspect of the implementation method, the scheme constructs a three-stage data mining normal form including error response sampling, key feature labeling and error type labeling, and the error recognition precision of the error correction model is effectively improved. Furthermore, a'generation-detection-correction-evaluation 'closed-loop optimization loop is formed, and the effect that the RAG capability is autonomously enhanced by utilizing the evaluation-guided proxy workflow under the condition that the RAG system does not need manual intervention is achieved.

The invention relates to the technical field of multi-degree-of-freedom motion control and self-stabilization platforms, in particular to an error compensation control method for a self-stabilization holder under multi-branch-chain redundancy collaboration, which comprises the following steps of: acquiring a pose and a disturbance signal based on branch chain physical topology, constructing a disturbance propagation path, and identifying a main error source branch chain and a secondary error branch chain; performing orthogonal decomposition on the error component of the main error source branch chain, and mapping the error of each secondary error branch chain to a unified error coordinate system; extracting time domain features of the direction and amplitude error, and generating a corresponding compensation signal; distributing a branch chain weight according to the disturbance intensity ratio, and constructing a redundant branch chain cooperative control instruction; synchronously driving each branch chain to execute compensation, and verifying whether the attitude error is converged or not; and if not, correcting the error identification parameter and the disturbance model, and feeding back to the control cycle. According to the invention, multi-branch chain high-dynamic coordination and error self-learning compensation can be realized, and the attitude stability and anti-disturbance capability of the holder are improved.

Disclosed are methods, systems, devices, circuits. and other implementations, including a method for error identification and correction that includes obtaining from a memory device coded input data, the coded input data previously encoded by multiplying a source data element by a pre-determined multiplier, and stored in the memory device, and performing a decoding operation on the coded input data obtained from the memory device, with the decoding operation including at least a modulo operation, to derive a resultant decoded data element and a remainder portion. The method further includes determining whether the coded input data includes a corrupted portion based on a value of the remainder portion.

The invention discloses a digital twinborn-oriented power grid dynamic ontology modeling method and system, relates to the technical field of power grid dynamic ontology, and aims to solve the problem of inaccurate power grid dynamic modeling. According to the invention, through the power grid dynamic model after visualization processing, a worker can see the operation data of the power grid more visually, so that potential problems and risks can be found more easily. Therefore, the staff can make decisions in time and take corresponding measures to guarantee safe and stable operation of the power grid, after the interaction technology is added, the staff can perform interaction operation with the visual model through input equipment such as a mouse and a keyboard, the test result is analyzed by using a data analysis tool, and the test result is analyzed by using the data analysis tool. And error data in the model can be efficiently identified and diagnosed. According to the intelligent method, the accuracy and efficiency of error recognition are improved, and rapid positioning and problem solving are facilitated.

The invention relates to the technical field of instrument calibration, in particular to a radio altimeter automatic calibration method, which comprises the following steps of generating a radio altimeter adaptive calibration result through stability identification, error comparison, mutation detection and rhythm regulation and control. According to the method, based on time difference fluctuation quantization and variation amplitude statistics, accurate recognition of the periodic state stability is realized, the ranging result screening precision is enhanced by limiting the error fluctuation range, and the error recognition sensitivity and pertinence are improved in combination with a plurality of groups of comparison mechanisms of ground reference data; dynamic extraction and recognition of the sudden change rate of the ranging error are superposed, the capability of timely capturing abnormal ranging behaviors is enhanced, the rhythm is dynamically adjusted and corrected, and continuous rate acquisition in a compression period is executed, so that the judgment efficiency of a recovery trend is improved, and the response control process of the ranging error is optimized. The continuity and adaptability of a height calibration process are effectively improved, and stable support for data accuracy in a changeable flight environment is ensured.

The invention discloses an engineering measurement error dynamic correction method based on multi-sensor data fusion, and relates to the technical field of engineering measurement. Three error sources of sensor physical characteristics, environmental interference and manual operation are defined as estimable state variables, and differentiation processing is performed according to different characteristics of errors: a dynamic model is established to embed the sensor and environmental errors into a state space, so that real-time compensation based on the model is realized; according to the scheme, a gross error recognition mechanism based on data-driven statistical characteristics is established, real-time diagnosis and processing are carried out on personal errors, joint optimal estimation is carried out on unified state vectors by adopting a recursive estimation algorithm, and high-precision corrected physical quantities and estimated values of all error states are synchronously output. The measurement precision and reliability are obviously improved; by means of robust processing of gross errors, stability of the system in a non-ideal environment and online self-diagnosis and health monitoring of the measurement system are enhanced.

The invention discloses a circuit breaker data error identification and correction method and system, and belongs to the technical field of circuit breaker abnormal data identification, and the method comprises the steps: collecting the electrical data and equipment state data of a circuit breaker in the operation process, and obtaining an original data sequence; performing frequency multi-scale decomposition on the original data sequence through wavelet transform, and extracting a feature vector of the original data sequence; based on the feature vector, performing error identification on the original data sequence through a preset error identification model, and outputting an error identification result and a corresponding error type; and a correction algorithm corresponding to the error type is selected to correct the error identification result, and a corrected data sequence is obtained. Therefore, by implementing the application, the problems that in the prior art, the collected electrical data has a relatively large error and the error cannot be accurately corrected can be solved.

The invention discloses a UTM cloud-based multi-source unmanned aerial vehicle flight record analysis method and system, and the method comprises the steps: building data connection with at least two unmanned aerial vehicle flight control systems of different manufacturers through a multi-source flight control connection module, and analyzing and collecting flight record data; uploading the flight record data to a cloud storage module in real time for centralized storage; performing multi-dimensional analysis on the flight record data through an intelligent analysis module, wherein the multi-dimensional analysis comprises the following steps: monitoring a flight state in real time to identify an abnormal flight event; when abnormality is detected, historical and real-time flight record data are called, and whether the cause is manual operation error or not is judged through data correlation analysis; wherein in the recognition process, external environment parameters are introduced to serve as correction factors to carry out normalization processing on basic indexes and composite indexes, and an anomaly judgment threshold value is dynamically adjusted through a Bayesian optimization algorithm; in the judgment process, an operation error probability score is output based on a three-dimensional operation baseline model and an operation error recognition model trained by a random forest classifier.

The invention discloses a protection secondary circuit measurement error identification method fusing Chebyshev distance and a modified cosine similarity algorithm, and relates to the technical field of transformer substation protection device secondary circuits, and the method comprises the steps: selecting at least three groups of measurement data sequences with physical correlation based on the actual transformer substation topology, and carrying out the preprocessing; fusing a distance value sequence which is obtained by calculating the Chebyshev distance and the corrected cosine similarity and is used for representing the discreteness of the measured data by using an entropy weight method, and comparing the EBM-CDMCS distance value obtained by fusing with a distance threshold value formed by the measured data under a normal working condition as a judgment index; evaluation and positioning of measurement errors possibly existing in protection of the secondary circuit are realized. Verification is carried out by taking two simulation examples of mutual correction of currents of different coils of the same CT and mutual correction of three-phase currents of the same measuring point as examples, and simulation results show that the algorithm can effectively identify more than 5% of measurement errors of the protection secondary loop and accurately position error sections.

The invention provides an intelligent identification method and equipment for a simulation error dominant area of a power system, relates to the technical field of power systems, and solves the problems of unstable aggregation result, limited partitioning hierarchy, insufficient dynamic feature expression, lack of credibility feedback and the like in simulation error identification of the power system in the prior art. According to the scheme, a power grid weighted adjacency matrix is constructed; performing spectrum serialization and preliminary node rearrangement; community priority partitioning and intra-block optimization are carried out; performing hybrid dynamic simulation and credibility evaluation; and multi-level block recursion and error locking are carried out. According to the method, the weighted adjacency matrix with line impedance or admittance as the weight is constructed, so that mathematical layering and node coupling feature mapping of the power grid are realized; the method comprises the following steps of: extracting a sub-matrix from an error salient region, repeatedly executing spectrum aggregation and community division, realizing automatic locking of an error dominant node, forming a closed loop structure of spectrum aggregation-decoupling-simulation-feedback in combination with hybrid simulation feedback, and realizing multi-level error identification from global to local.

The invention discloses a high-precision guide rail double-tool iterative assembly method which comprises the following steps: coarsely adjusting the flatness of a mounting surface through an electronic level meter, accurately measuring the straightness of a guide rail through an autocollimator, establishing an error separation model for directional correction, and forming a'detection-correction-reinspection 'closed loop. The problems that a traditional method is fuzzy in error recognition and low in trimming efficiency are solved, the method is suitable for high-precision assembling and adjusting of the precise mechanical guide rail, and the assembling precision and efficiency are remarkably improved.

Disclosed herein is a technique for mitigating errors tied to software applications. According to some embodiments, the technique can be implemented by a server device, and include the steps of (1) identifying at least one error associated with a user of a software application, (2) identifying at least one client device associated with the user and on which the software application is installed, and (3) providing, to the at least one client device, an indication of the at least one error to cause the software application to, in conjunction with being loaded and / or displayed on the at least one client device: display a user interface that includes information derived from the indication, wherein the user interface is sandboxed from the software application in a manner that prevents the software application from observing activity that occurs within the user interface.

The invention discloses a five-axis machine tool geometric error identification method based on single-axis and multi-axis measurement, and belongs to the field of numerical control machine tool precision detection. Error kinematics and multi-axis motion models are established based on a multi-body system theory, and error identification models of a linear axis and a rotating axis are respectively constructed. On the aspect of a linear axis, an identification method based on measurement of a positioning error and a straightness error is provided, two measurement / identification schemes of single-axis motion and two-axis linkage are designed, and 18 linear axis geometric error parameters related to the position and 3 linear axis geometric error parameters irrelevant to the position are obtained through calculation. In the aspect of a rotating shaft, 12 rotating shaft geometric error parameters related to the position and 4 rotating shaft geometric error parameters irrelevant to the position are obtained on the basis of an existing linear shaft result based on a measurement and identification scheme of a double-ball-rod instrument in three directions and six positions. According to the method, positioning and straightness error detection are completed in combination with auxiliary equipment such as a laser interferometer and a double-ball-rod instrument, and the method has good universality.

The invention relates to a method for preventing CAN (controller area network) wake-up false identification after vehicle repair and part replacement of a vehicle-mounted controller, the vehicle-mounted controller uses a TJA1043 chip and is connected to a CAN bus, and the method comprises the following steps: after the vehicle-mounted controller is powered on and started, false triggering wake-up judgment is executed; if the judgment result is effective awakening, controlling the vehicle-mounted controller to enter a normal working mode; and if the judgment result is false triggering awakening, the vehicle-mounted controller enters the dormancy or shutdown state again. By adopting the method, the system, the device, the processor and the storage medium for preventing CAN wake-up error identification after vehicle repair and part replacement of the vehicle-mounted controller, under the condition that a TJA103 chip is not changed, the CAN wake-up error identification can be prevented for all controllers managed by an Autosar network and an instrument controller which is defined as OSEC network management and is provided with a perpetual calendar; a scheme for solving INH output false triggering of a cold start TJA1043 chip is provided, contradictions caused by cost are solved, and software misjudgment when a storage battery on a controller is normally powered is solved by using a system method.

The invention relates to a clamping error identification method for precision assembly and electronic equipment, and the method comprises the steps: firstly constructing an assembly system model, initializing a force sensing module, and when a part is clamped, identifying a clamping position error and carrying out gravity compensation through analyzing a mapping relation between force sensing data and a part barycentric coordinate; then, in the contact stage of the part and the reference shaft, a contact force line equation is established, contact point coordinates are solved, and a clamping attitude error is obtained through further calculation; and finally, the robot carries out real-time motion compensation under an impedance control strategy based on the identified position and attitude errors, and the assembly quality is evaluated after assembly is completed until all the parts in the batch are assembled. On-line dynamic recognition and closed-loop correction of position and posture deviation in the clamping process are achieved through force sensing information, and the assembly precision and the self-adaptive capacity of the system are remarkably improved.

The invention provides a product copywriting optimization method and device, equipment, a medium and a product. The product copywriting optimization method comprises the following steps: collecting a copywriting and preprocessing the copywriting to obtain copywriting data; evaluating the copywriting data, and generating an error list and an error evaluation report; repairing the copywriting according to the error list; wherein the document data evaluation comprises the following steps of: respectively judging whether errors exist in each document segment in the document data by using a retrieval enhancement generation (RAG) technology on the basis of a preset standardized word bank; judging whether errors exist in the copywriting fragments or not by using an inference model; and generating an error list and an error evaluation report. The method and the device have the advantages that automatic identification and accurate replacement of copywriting errors with clear rules are realized, manual verification is replaced, and verification efficiency and accuracy are improved; the real-time performance is good, error recognition and correction can be synchronously completed during online, and time loss caused by recognition and uploading after online is avoided; independent platform deployment is not needed, cost is low, and maintenance is easy.

The invention relates to the field of experiment guidance, and particularly provides a virtual experiment environment guidance information generation method and system, a terminal and a medium, and the method comprises the steps: capturing operation data of a student in a virtual experiment environment in real time to extract operation intention features, carrying out the compliance check of parameter setting, and carrying out the recognition and judgment of an equipment state and an experiment result, the method comprises the following steps: firstly, carrying out scene analysis on a scene, forming a uniform situation representation vector, carrying out rule matching through a predefined rule based on the vector, predicting and identifying operation errors, logic errors, safety violations and potential experiment risks through a machine learning model, and outputting a final diagnosis result by adopting a conflict resolution mechanism; and according to the error type, the risk level, the historical performance of the student and the learning preference, dynamically generating and outputting guidance information in a text, vision, voice or animation form. According to the invention, the accuracy and comprehensiveness of error recognition are improved, the safety protection capability of the experiment process is enhanced, and real-time and accurate guidance of student operation is realized.

The application discloses a vehicle-mounted display screen recovery method and device, a storage medium and a vehicle, relates to the technical field of vehicle-mounted intelligent cockpits, and comprises the following steps: in response to display link abnormality of a vehicle-mounted display screen, reporting error identification of the display link abnormality to a user state service of a vehicle-mounted system; controlling the user state service to create a vehicle-mounted display screen self-recovery transaction according to the error identification, executing a self-recovery program corresponding to the vehicle-mounted display screen self-recovery transaction; determining that the self-recovery program does not recover the display link of the vehicle-mounted display screen, and restarting to recover the vehicle-mounted display screen. Self-healing is prior to whole-machine restart, and invalid attempts are reduced through adaptive backoff, so that the restart frequency can be reduced, thereby reducing the start-up delay, data consistency and energy consumption cost caused by restart, improving the stability and maintenance efficiency of the system, and improving the availability, reliability and maintainability of the display link.

The invention provides a state estimation and error identification method and device for an autonomous navigation system, and the method comprises the following steps: obtaining an observability evaluation index of the system by using an observability criterion; according to the observability evaluation index of the system, obtaining the accurate compensation degree of the measurement error of the optical sensor, and determining the achievable state estimation accuracy of the autonomous navigation system; constructing an observability optimization function; analyzing a coupling relationship between a measurement error and a system state based on an observability optimization function, and establishing an error response model; according to the error response model, constructing a system state parameter joint optimization model through the observability evaluation index of the navigation system; and optimizing the system state parameter joint optimization model and realizing on-orbit identification of errors and system states. The accuracy of observability judgment of the navigation system is improved, observation information and calculation resource allocation can be autonomously optimized, and the problem of state estimation under the weak observation condition is solved.

The present invention belongs to the technical field of power plant gross error identification and discloses a method, system, device, and medium for identifying gross errors in power plant system measurements. The method comprises the following steps: obtaining power plant system measurement data for which gross errors are to be identified; and performing predictions based on the obtained power plant system measurement data using a trained prediction model for the gross errors of the power plant system to obtain a gross error identification result. This invention specifically provides a method for intelligently identifying gross errors in power plant system measurements based on a multi-classification support vector machine (SVM). The method is capable of quickly and accurately identifying gross errors in the system and directly determining the location of fault points.

The invention provides a multi-gross error recognition RAIM method based on DBSCAN clustering, and the method comprises the steps: processing received satellite observation data through employing a QR parity check method, and constructing an observation sample; performing standardization processing on the observation sample; a DBSCAN clustering analysis algorithm is used for analysis, abnormal clusters different from normal data distribution modes are recognized, observation values corresponding to the abnormal clusters are judged as gross errors, and then the gross errors are removed from observation samples; performing iterative processing on the observation sample after the gross error is removed until an observation value meets a preset inspection condition, and outputting a positioning calculation result; and if the observation value still does not meet the test condition after a preset number of iterations, judging that the data of the epoch is unreliable, and abandoning the epoch. According to the method, DBSCAN clustering is integrated into the RAIM algorithm, the advantages of the DBSCAN clustering in the process of processing noise-containing spatial data can be fully utilized, noise interference is effectively eliminated, and then the detection capacity of the RAIM algorithm in a multi-gross-error scene is improved.

The present invention relates to the field of instrument calibration technology, and specifically to a radio altimeter automatic calibration method, comprising the following steps: generating a radio altimeter adaptive calibration result through stability identification, error comparison, mutation detection, and rhythm regulation. In the present invention, based on the quantification of time difference fluctuations and the statistics of variation amplitude, accurate identification of periodic state stability is achieved, the accuracy of ranging result screening is enhanced by limiting the error fluctuation range, a multi-group comparison mechanism with ground reference data is combined to improve the sensitivity and pertinence of error identification, and the dynamic extraction and identification of ranging error mutation rates are superimposed to enhance the ability to capture abnormal ranging behavior in a timely manner. By dynamically adjusting the correction rhythm and performing continuous rate acquisition within a compressed period, the efficiency of judging the recovery trend is improved, the response control process of ranging errors is optimized, and the continuity and adaptability of the altitude calibration process are effectively improved, ensuring stable support for data accuracy in a changing flight environment.

The present application relates to the field of data acquisition, and more particularly to a total station measurement data acquisition method and system, comprising: obtaining an original measurement data set with a time sequence label by performing three-dimensional coordinate calculation and arrangement on original total station measurement data; obtaining an adaptive neighborhood radius of each point by comprehensively analyzing the local neighborhood distance of the original measurement data points; obtaining a shared local structure tensor between point pairs by fusing and constructing the local structure tensor of the measurement points; obtaining a shape-adaptive symmetric anisotropic distance measurement by performing principal axis direction deviation analysis on the shared local structure tensor; and obtaining a gross error point identification result and eliminating abnormal measurement data by jointly judging the shape-adaptive distance and the neighborhood radius, thereby solving the problem of inaccurate gross error identification caused by uneven distribution density of measurement points and data anisotropy.

The present invention is for, in applying a target object exploration according to a RPA scenario based on a previous UI screen to the current UI screen, if a specific target object cannot be searched or an error occurs due to a change on a target app / web at the current time point, automatically extracting information on the most suitable corresponding object on the current UI screen, thereby automatically recovering from the target object exploration execution failure of the previous scenario. A method of the present invention may comprise: an error recognition step for detecting the occurrence of an error resulting from the application, to the current UI screen, of a target object exploration based on object exploration information of a RPA scenario created on the basis of a previous UI screen; an image information LLM inquiry step for generating a first prompt including a first image including at least a portion of the previous UI screen including a target object, and a second image including at least a portion of the current UI screen, and instructing a generative AI to return information of an object corresponding to the target object on the current UI screen; and an object exploration step for performing target object exploration on the current UI screen.

The application discloses a classroom instant interaction feedback analysis method and system based on a portable multimedia display device, relates to the field of educational information technology, and discloses the classroom instant interaction feedback analysis method and system based on the portable multimedia display device, which automatically acquires student answer data, performs logical analysis, verification correction, cluster analysis and common error identification, and generates visual feedback in real time, solves the problems of low artificial review efficiency and incapability of accurately positioning common errors in the prior art, can automatically analyze the solution logic of open questions, identify common errors, and provide real-time visual feedback, improves classroom interaction efficiency and teaching accuracy, and thus improves teaching quality.

The invention discloses a geocoding error identification method based on external semantics and space consistency constraint, and belongs to the technical field of geocoding. The method comprises the following steps: firstly, carrying out word segmentation on a text address and judging whether the text address is a road complete type address or a road missing type address; coding coordinates are obtained through a geocoding platform, and road network data are combined to generate a road set R with the first three distances; the road missing address directly takes the mean value of the distance from the coordinate to the R as an error; the road complete type address is further divided into a matching failure type address or a road matching type address, the matching failure type address takes a corresponding distance or a mean value according to the road matching condition, and the road matching type address deduces an error through POI spatial clustering. The method is based on external semantics and spatial consistency constraints, and is used for identifying errors of coding coordinates after a geocoding platform executes geocoding operation on a text address.

Techniques for automatic error mitigation in database systems using alternate plans are provided. After receiving a database statement, an error is detected as a result of compiling the database statement. In response to detecting the error, one or more alternate plans that were used to process the database statement or another database statement that is similar to the database statement are identified. A particular alternate plan of the one or more alternate plans is selected. A result of the database statement is generated based on processing the particular alternate plan.

This invention provides a real-time feedback-based intelligent dynamic compensation control method and system for CNC machine tools, relating to the field of machine tool control technology. It involves real-time acquisition of multi-source state data during the CNC machine tool machining process, and using a trained hybrid dynamic error identification model to perform real-time identification of multi-source dynamic errors on the pre-processed standardized state dataset. An adaptive dynamic compensation strategy is generated based on the real-time identification results. The compensation strategy drives the servo motors of each axis to achieve real-time dynamic compensation of the machining process. This invention achieves accurate identification of machine tool errors through a hybrid dynamic error identification model, and effectively mines the complex nonlinear mapping relationship of dynamic errors by fully exploring long-sequence, short-sequence, and local correlation features, thus improving the model's robustness and generalization ability. Furthermore, by employing a basic threshold and a trend-corrected adaptive threshold, this invention can achieve synchronous and accurate compensation of single-axis errors and multi-axis coupled errors, further improving compensation accuracy.