455 results about "Consistency analysis" patented technology

The invention relates to the technical field of grinding wheel monitoring, in particular to a centerless grinding machine full-life-cycle grinding wheel state monitoring system and method.According to the centerless grinding machine full-life-cycle grinding wheel state monitoring system and method, through combined difference extraction of a main shaft current mean value fluctuation ratio and a power gradient continuous variation value and assisted by transverse comparison of periodic response intervals, effective recognition of time period boundaries of working condition states is achieved; according to the method, operation stage division does not depend on static threshold judgment any more, a track trend is established through linkage judgment of an amplitude kick point and a slope extreme value, a dynamic evolution path of signal response is clearer, the identification resolution of abnormal changes and local deviation trends is improved, response synchronous identification of parameter state changes is achieved, and the identification accuracy is improved. In multi-signal collaborative analysis, directivity comparison between a temperature rise mutation fragment and a current residual error response is carried out, so that the consistency analysis capability of response logic between different monitoring paths is enhanced, and the real-time performance, stability and anti-interference capability of state identification are improved.

The invention belongs to the technical field of digital content security, and discloses a multi-mode AI content security risk traceability and identification detection system. Through obtaining multi-source heterogeneous data of content creation, editing, distribution and presentation of a full link, a content full link feature fingerprint is constructed, and cross-modal consistency analysis and link continuity verification are realized. According to the method, traceability map construction is introduced, potential tampering points are used as map nodes, content risks are quantified through tampering probability weights and risk transfer intensity, and tampering sources and propagation paths are accurately identified. The method has comprehensiveness and accuracy, deep analysis and risk assessment can be carried out on the multi-modal content, and the tampered content is effectively recognized and synthesized.

The invention relates to the technical field of artificial intelligence and information processing, and particularly discloses a multi-modal file intelligent classification and label generation method and system. The method comprises the steps of obtaining text paragraphs, image segments and video key frame data in a file, performing format recognition and region separation, and generating multi-modal content structure data; semantic features are extracted based on the data, and fused semantic representation is constructed; generating a main label, a sub-label and a keyword set by using the fused semantic vector, and constructing a multi-level label structure; and further performing label redundancy elimination and structure optimization to generate a label atlas, and performing consistency analysis and feedback optimization through the label atlas and the semantic representation structure. Compared with the prior art, the method has the advantages that various modal information can be effectively fused, the accuracy, hierarchical structure and semantic consistency of archive label generation are improved, and the method has high intelligence, self-adaption and sustainable optimization capabilities and is suitable for various scenes such as archive management, content auditing and semantic archiving.

The invention discloses a high-precision static aeroelastic model optimization design method based on a model correction technology, and relates to the technical field of aircraft design, and the method comprises the following steps: S1, firstly constructing an initial model, and carrying out statics pre-analysis to verify integrity; s2, executing SOL 101 statics analysis based on the initial model and outputting a physical field result; s3, carrying out consistency analysis in combination with test data and generating a correction decision; s4, screening high-priority correction parameters through local or global sensitivity analysis; s5, correcting model parameters by adopting a mixed algorithm of a gradient method and an agent model, and verifying precision and generalization ability; s6, the corrected model is output as a Nastran file and a reduced-order model in a standardized mode, and a parameter change log is recorded; s7, executing static aeroelastic coupling and flutter analysis, and feeding back a result to drive optimization iteration; s8, constructing a multidisciplinary coupling optimization model in combination with aeroelastic and flutter results to realize collaborative optimization; and S9, finally performing engineering standardization packaging on the optimization model and outputting a verification report.

The invention relates to the technical field of building structure health monitoring, and particularly discloses a building group safety inspection method based on external structure size displacement detection, and the method comprises the steps: obtaining three-dimensional laser scanning point cloud data of a target building group at a plurality of time points, adding timestamp information, and constructing a time sequence point cloud data set; initial registration is carried out by adopting a feature matching and motion recovery structure technology, and the registration precision and stability in a dynamic environment are improved in combination with a global optimization model fused with space-time consistency constraints; identifying and eliminating pseudo displacement point clusters through track consistency analysis, and extracting a static background structure; finally, key part deformation identification is carried out on the differential point cloud data, and a structure health state evaluation report is generated. According to the invention, full-process automatic processing from data acquisition, optimization registration to intelligent evaluation is realized, the dynamic interference influence is effectively inhibited, the precision and reliability of structural deformation monitoring are improved, and technical support is provided for long-term safety inspection of building groups.

The invention discloses a software requirement modeling method and device based on a natural language, equipment and a medium, and relates to the field of software requirement modeling. According to the software demand modeling method and device based on the natural language, the equipment and the medium, through automatic demand analysis and model generation, the manual workload is greatly reduced, and meanwhile, errors caused by manual understanding deviation are reduced; close connection among the steps is ensured by sharing intermediate representation and a unified data model, output of the previous step provides structured information for input of the next step, and information loss or distortion is avoided; a demand provider is allowed to participate in a model confirmation process through an iterative demand acquisition and modeling framework of man-machine cooperation, and the quality of a demand model is continuously improved; by means of the model consistency analysis technology based on the data flow dependency relationship, the problem of inconsistency between the requirement specification and the software model can be automatically detected, and the software product quality is improved.

The invention relates to the technical field of personnel examination scoring, in particular to an end-to-end-based multi-agent personnel examination scoring method, which comprises the steps of generating fusion features based on image data of an examinee answer sheet, inputting the fusion features into a heterogeneous OCR engine for processing, and outputting an examinee answer text; establishing a knowledge base, analyzing a question requirement text, and screening out a reference answer text from the knowledge base; constructing a plurality of dimension scoring agents, determining an original state based on the question requirement text and the reference answer text, training each dimension scoring agent through the original state, inputting the examinee answer text into the dimension scoring agents, outputting dimension scoring scores, and forming dimension scoring vectors; carrying out self-consistency analysis by integrating the dimension score vector and the original state, and outputting a final score; the whole-process closed-loop processing from paper answer sheet scanning to high-precision, automatic and interpretable scoring is realized, and the marking efficiency, fairness and credibility are improved.

The invention belongs to the technical field of pathological diagnosis, and discloses an artificial intelligence-based lung cancer pathological section analysis and system, which introduces identification basis visual information generated by an artificial intelligence model, and combines the correction operation of a plurality of pathologists on a model identification result and the acquisition of correction reasons, so that the pathological section analysis of the lung cancer is realized. Further performing consistency analysis on the correction results to generate uniform data, and finally performing incremental training on an artificial intelligence model by using the data, thereby constructing a closed-loop feedback optimization mechanism combining artificial intelligence and expert knowledge. The model performance problem caused by insufficient training data coverage, expert labeling efficiency and result inconsistency of an artificial intelligence model in pathological diagnosis is solved, and model learning and performance improvement are achieved.

The invention discloses a pump set vibration monitoring method and system based on distributed sensing. The method comprises the steps that vibration collection signals and real-time working condition parameters of distributed sensing nodes are obtained, multi-node clock synchronization correction is executed, and synchronous vibration data frames are formed; time-frequency feature extraction is carried out on the multi-channel vibration data set, abnormal channels are identified through inter-channel consistency analysis, a local fault correlation frequency band is extracted, and a vibration feature vector is constructed; associating the vibration feature vector with a real-time working condition parameter to form a working condition-feature mapping table, identifying a feature mutation rotating speed point for the feature baseline, adaptively dividing a rotating speed interval to generate an adaptive working condition threshold value, and implementing out-of-limit detection to generate an abnormal trigger identifier; determining a traceability analysis window based on the abnormal trigger identifier, and executing multi-measuring-point coherence calculation and energy attenuation gradient analysis to construct an energy transfer link diagram; and finally, vibration source position positioning is performed to form fault source probability distribution, a fault mode label is matched, pump set vibration monitoring is completed, and quantitative positioning of a fault source is realized.

The invention discloses a multifunctional safety helmet management system and method based on the Internet of Things, relates to the field of safety production, and solves the problems that a traditional safety helmet is single in safety management function, insufficient in data processing precision and the like. A multi-dimensional state data sequence is continuously collected through a three-axis acceleration sensor, a temperature and humidity sensor, a positioning sensor, a vital sign sensor and the like integrated on the safety helmet terminal; terminal monitoring characteristics including an acceleration module value, a position drift distance and a physical sign fluctuation index are constructed, data reliability is evaluated through weighted fusion of dynamic fluctuation values, and an abnormal terminal is isolated. And carrying out space-time calibration on the reliable data to generate a unified coordinate system trajectory, analyzing and identifying abnormal behaviors through group trajectory consistency, and constructing a regional safety risk map in combination with a signal blind area coverage rate, thereby realizing safety risk level prediction based on historical data and real-time trajectory matching. According to the invention, comprehensive real-time monitoring of the state of the operator is realized, and the intelligent level of safety production management is improved.

The invention discloses a multi-agent cooperative control system based on adaptive learning, and belongs to the technical field of multi-agent system control, and the system specifically comprises the steps: collecting and analyzing the wind field data of the position of each agent; distinguishing two typical working conditions of a global uniform wind field and a local disturbance wind field based on a consistency analysis result; for a global uniform wind field, a model prediction control method is adopted to generate a wind field compensation strategy for keeping formation stability; for a local disturbance wind field, an accurate airflow disturbance state is obtained through environment three-dimensional reconstruction and fluid simulation, then the expected track deviation of each agent is predicted, and a collaborative avoidance instruction set is generated in combination with a relative position relationship. According to the method, adaptive cooperative control of multiple agents under different wind field working conditions is realized, the hidden conflict problem caused by local wind field disturbance is effectively solved, and the flight safety and task reliability of an agent cluster in a complex environment are remarkably improved.

The invention discloses a supervision method and device based on construction project quality detection and a medium, and relates to the technical field of project quality supervision, and the method comprises the steps: collecting construction site data, carrying out the preprocessing, and generating a site data set; performing real-time comparison and verification on the building information model and the field data set to obtain verification data, inputting the verification data into the building information model, performing construction consistency analysis and deviation identification, and generating a quality evaluation report; performing risk assessment and priority classification on the quality analysis data to obtain risk assessment data, and performing problem priority analysis and rectification scheme formulation on the risk assessment data to generate rectification execution data; and performing rectification effect analysis and overall quality evaluation according to the rectification execution data, and generating a project quality summary report. The real-time performance and the accuracy of construction quality monitoring are improved, the construction deviation is reduced to the maximum extent, the quality management is optimized, and the smooth proceeding of a project is guaranteed.

A system and method for querying, processing, and ranking governmental data across heterogeneous databases may include integrating large language models (LLMs) and multi-agent orchestration to enhance accuracy and mitigate bias. The system receives a natural language query, processes the query using an agent orchestration LLM to generate search query instructions, and executes specialized data record processing agents to retrieve data from diverse sources, including relational, vector, and graph databases. A plurality of candidate natural language responses is generated and validated by data verification LLMs based on relevance and accuracy metrics to reduce hallucinations. The system further employs cross-source validation, statistical and linguistic consistency analyses, and weighted scoring to refine responses, which may include textual summaries, tables, or downloadable files presented via a graphical user interface. Accordingly, the approach ensures precise and contextually relevant results, particularly for applications involving sensitive or regulated data such as legislative and governmental records.

The invention discloses a dynamic and steady state characteristic evaluation method for a main fuel oil system of an aero-engine, which is used for carrying out systematic evaluation on dynamic and steady state performance of the main fuel oil system in different design stages. Respectively establishing differential evaluation mechanisms of three stages of design scheme demonstration, principle prototype development and product shaping and batch production; multi-dimensional evaluation of system response characteristics, control performance and robustness is realized by constructing a nonlinear system model and a linearized frequency domain model and combining typical working condition simulation and a principle prototype test; in the batch production stage, a standardized input working condition and a simplified index system are adopted, and batch production prototype performance consistency analysis and rapid quality judgment are achieved. According to the method, systematic evaluation of the aero-engine main fuel system in the full design stage can be achieved, a comprehensive evaluation system combining a model and a test is constructed, the design efficiency and reliability are improved, and the evaluation precision and credibility are improved.

The invention discloses a document understanding and question-answering method and system based on multiple modes and multiple agents, and the method comprises the steps: firstly carrying out the preprocessing of a document, generating a text paragraph and a page image, and then employing a retrieval enhancement generation frame to retrieve and query related contexts from two channels of a text and the page image, obtaining a text candidate set and an image candidate set; performing preliminary fusion by using five types of functional agents and forming a candidate conclusion, forming cross-modal key information to limit a subsequent analysis range, performing fine-grained examination and analysis in text and image modalities, and outputting intra-modal conclusions with position indications such as page numbers, paragraphs and regions; and finally, performing consistency analysis and weighted fusion on the multi-source result to generate a final answer. According to the method, the text and the visual clues can be integrated at the same time, the complex multi-modal reasoning capability is improved, and the accuracy in tasks such as document question and answer is improved.

The invention discloses a data-enhanced fine-grained multi-mode false information detection method and system, and aims to improve the accuracy of image-text false news detection. The method comprises the following steps: acquiring a news text and associated pictures thereof, extracting a text core entity semantic sequence and a visual entity semantic sequence by respectively utilizing a pre-training language model and a visual entity recognition model, and performing knowledge enhancement on original word-level text representation and low-level visual features through an attention mechanism; calculating a correlation matrix between the enhanced text and the visual features, dividing consistent and inconsistent regions, and respectively extracting consistent and inconsistent features; and finally, fusing the two types of features and global text representation to generate classification features so as to judge the authenticity of the news. Through double-channel knowledge enhancement and fine-grained cross-modal consistency analysis, the detection performance is remarkably improved, and the method is suitable for scenes such as social media and news platforms.

The invention provides a medicine bottle array detection system based on vision and sensing fusion, and relates to the technical field of data processing, and the system comprises the steps: obtaining the spatial distribution data of a vision unit and the posture state data of a sensing unit, fusing the position parameters and state parameters of each bottle body, building a multi-dimensional data node under a unified time index, calculating the spatial aggregation degree of the medicine bottle array to obtain an array quantity, combining the aggregation change of each time point into an evolution chain table, carrying out joint operation on the difference result and the state parameter of adjacent nodes in the evolution chain table, calculating the dynamic coupling degree of the medicine bottle array to obtain a sequence potential energy value, and dividing the sequence potential energy values of the different numerical value intervals into a plurality of level nodes, and performing consistency analysis and anomaly detection on features of the different level nodes to obtain detection result data. By detecting the state of the medicine bottles and the arraying direction, bottle toppling early warning is achieved.

The invention relates to a multi-competency intelligent scoring method and system, and belongs to the technical field of intelligent evaluation and talent evaluation. The method comprises the following steps: acquiring multi-source response data of a target evaluation object, executing evidence sufficiency and consistency analysis for each competency dimension, generating a judgment state identifier, and constructing a structural description; performing responsibility distribution on the evaluation evidence, mapping the evaluation evidence into a corresponding evidence model and generating a priority constraint relationship; performing time sequence consistency and stability analysis on the evidence model, and constructing a time sequence constraint rule to prohibit unconstrained score backtracking; and carrying out resolution processing on the continuous undetermined dimension, generating a scoring result through a preset risk scoring rule and a conservative determination strategy, and synchronously generating a scoring basis path and confidence information. According to the method, standard management and control of multi-source evidences and accurate constraint of the whole scoring process are realized, the scoring accuracy and traceability are effectively improved, and reliable support is provided for multi-scene talent evaluation decision.

The invention discloses an image measurement method for precise size measurement. The method comprises the following steps: step 1, selecting a laser scanner and an optical image measurement instrument to form a measurement array according to geometrical characteristics of a workpiece; 2, calibrating and verifying the measurement array, obtaining a basic error curve of the equipment through a standard gauge block, and collecting real-time environmental parameters after verification is passed; 3, calculating an environment interference coefficient Kenv, and starting measurement at the moment; 4, monitoring equipment acceleration sensor data in real time, and generating an equipment stability index Si; 5, when Si is larger than S < safety >, measurement is executed, and a result is output; and step 6, carrying out consistency analysis on multi-device results, if the results are consistent, outputting a final value, otherwise, triggering dynamic re-calibration. According to the invention, multi-dimensional cooperative control can be realized, the precision bottleneck of traditional image measurement in a dynamic environment is broken through, and the method is suitable for precision manufacturing scenes with high requirements on measurement stability and reliability.

The invention discloses an RAG query method, system, medium and product capable of inhibiting a hallucination problem of a generative large model, and relates to the field of RAG query, the method comprises the following steps: obtaining a preliminarily generated text obtained by answering a user initial problem by a preset generative large model; extracting the preliminarily generated text to obtain a key verification problem; performing multiple rounds of questions and answers on the key verification question by using the generative large model to obtain multiple rounds of answers; performing consistency analysis on the multiple rounds of answers to obtain a consistency analysis result; a round of questions and answers with the highest comprehensive score in multiple rounds of answers are directly output at the high grade; when the key verification question is in the middle level, performing multiple rounds of question answering on the key verification question again; when the level is low, RAG retrieval and knowledge fusion are carried out on key verification questions, and questions are asked again; and carrying out illusion identification, correction and text optimization on the answers obtained by asking the questions again to obtain high-quality answers and outputting the high-quality answers. According to the invention, illusion can be accurately positioned, and high-quality answers can be obtained.

A method and system for estimating dimensions of vehicle exterior defects using multiple cameras arranged in a predefined configuration. The method comprises receiving images from multiple strategically positioned image sensors including side cameras parallel to a vehicle height axis, diagonal cameras at an inclined angle, and roof top cameras perpendicular to the height axis. An angle to detected defects is computed based on image sensor parameters. Different distance calculations are applied based on vehicle section location, with specialized formulas for windshield, back window, and roof components. Defect sizes are computed by determining multiple defect dimensions, with at least one dimension being adjusted by an angular correction factor derived from the relationship between camera angle and vehicle surface orientation. The system implements comprehensive validation through cross-referencing between cameras, comparison with known specifications, and measurement consistency analysis across multiple frames.

The invention relates to the technical field of material detection, and discloses an identification analysis and method for recessive degradation of a flexible conductive composite material, and the system comprises a perturbation excitation module, a response collection module, a time sequence feature extraction module, a micro-response trend consistency analysis module, and a state evaluation and early warning module. Multiple periods of small-signal capacitance excitation are applied to the material, pi-pi stacking slippage and interface polarization behaviors in a conductive network are excited, electrical response data are collected to construct a time sequence feature vector, and the deviation degree of the evolution trend is further calculated. And based on the trend deviation index, performing health state scoring and triggering early warning, thereby realizing early recognition and evaluation of material recessive degradation.

The invention discloses a brake pedal verification method, device and equipment based on a two-way pedal and a storage medium, relates to the technical field of vehicle brake control, and discloses the brake pedal verification method based on the two-way pedal. Comprising the steps that a brake lamp switch signal, an allowable deviation threshold value and a first sensor signal and a second sensor signal of a two-way pedal position sensor are obtained; performing processing according to the first sensor signal and the second sensor signal to obtain a target deviation value, and performing consistency analysis according to the target deviation value and the allowable deviation threshold to obtain a consistency analysis result; performing fault tracing on the consistency analysis result according to the brake lamp switch signal to obtain a fault positioning result; and fault isolation is carried out based on the fault positioning result, so that brake pedal verification based on the two-way pedal is completed. The technical effect of guaranteeing the signal reliability of the two-way pedal position sensor and the function continuity of the braking system is achieved.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses an identification method, device and equipment based on semantic space consistency, and a medium, and the method comprises the steps: obtaining and preprocessing a target image, a positioning text region and an object region, and generating region positioning information; identifying and correcting the text region to generate a target text vector, extracting an object region image feature and normalizing to generate a target image vector, and mapping the two to the same semantic space for consistency analysis to generate a fusion confidence coefficient and a preliminary identification result; and retrieving, comparing and outputting final identification information and the fusion confidence coefficient in a preset knowledge base based on the fusion confidence coefficient and the preliminary identification result. According to the method, complementary fusion of the text and the image is realized through semantic space mapping, and standardized verification is completed by combining with knowledge base comparison, so that the problem that a single recognition mode is easy to make mistakes is effectively solved, and the accuracy and reliability of a result are improved.

The invention discloses a logic chip mask defect detection method, and relates to the technical field of integrated circuit manufacturing, and the method comprises the following steps: S1, constructing a scattering response model of sub-wavelength inorganic particles on the surface of a mask, and constructing a scattering response model of sub-wavelength inorganic particles on the surface of the mask under a set multi-angle polarized light incidence condition; non-linear disturbance influence of inorganic particles with different particle sizes on the reflected light phase in each incident polarization state is simulated, and a scattering response template containing standard phase disturbance characteristics is generated; and S2, based on a scattering response template, carrying out pixel-by-pixel matching analysis on the acquired multi-angle polarization phase diagram on the surface of the mask, identifying a local area matched with the template, and marking the local area as a suspected scattering interference area. According to the method, through construction of the scattering response template and multi-angle polarization consistency analysis, accurate distinguishing of artifacts and real defects is achieved, the recognition precision and stability under complex interference are improved in combination with structure retention type phase reconstruction and dynamic threshold recognition, and mask quality control and photoetching yield improvement are facilitated.

The invention relates to the technical field of image recognition, and discloses a glass fiber board production quality detection method and system, and the method comprises the steps: collecting a continuous infrared thermal image sequence through an infrared thermal imaging device; constructing a temperature difference image set; identifying a primitive region with an abnormal diffusion characteristic; further performing fitting enhancement and significance detection on the abnormal primitive region; and performing defect classification and quality judgment based on the regional feature vector. Compared with the prior art, the technical problems that in the prior art, high-precision parting judgment cannot be achieved under the conditions that the surface texture of a glass fiber board is complex, hot-pressing disturbance exists, particularly, hot diffusion behaviors of dry filaments, degumming and cavitation bubble defects are similar, and the false detection rate of a conventional algorithm is high are solved. Due to the fact that a multi-channel thermal diffusion consistency analysis mechanism and parallel discrimination logic based on feature vectors are introduced, infrared primitive anomaly enhancement detection and defect classification recognition under the complex background are achieved, and the accuracy of glass fiber board production quality detection is improved.

The invention discloses an automatic charging processing method and device for a charging robot, and relates to the technical field of robot energy management, and the method comprises the following steps: constructing an acoustic array, collecting high-frequency background sound wave signals in a working area of the charging robot in real time, and extracting sound spectrum energy distribution; and identifying an interference frequency band coinciding with the working frequency of the ultrasonic sensor, and calculating the intensity level of the interference frequency band according to the sound spectrum energy intensity and the duration time in the interference frequency band. According to the method, a closed-loop system of interference perception-risk assessment-control response is constructed, and dynamic adjustment of perception confidence and output of blindness risk indexes are realized through multi-modal identification consistency analysis and historical deviation tracking. Once the threshold value is exceeded, the system executes frequency hopping and strategy optimization, frequency band shielding is effectively avoided, the sensing stability, path accuracy and operation safety of the charging robot in the sound interference environment are improved, and good application prospects are achieved.