33 results about "Integrity assessment" patented technology

The invention discloses a multi-dimensional security data threat detection method and device based on a large model and a storage medium, and belongs to the technical field of network security, and the method comprises the steps: obtaining multi-dimensional heterogeneous security data, and generating a plurality of basic event descriptions; performing semantic processing on the basic event description to obtain a standardized event description, inputting a pre-trained large language model to perform single-point threat research and judgment, and outputting an event threat evaluation result; splicing the standardized event descriptions of the same target entity into a behavior sequence text, inputting the behavior sequence text into a large language model for multi-stage attack feature analysis, and outputting an attack chain integrity evaluation result; determining a comprehensive threat level based on the event threat assessment result, the attack chain integrity assessment result and the affected asset attribute; and generating a security event analysis report, and extracting the security entities and the association relationships thereof from the report to update the security knowledge graph. The technical breakthrough from traditional'event seeing 'to real'event understanding' is realized.

The invention provides a data processing method which can be applied to the technical field of big data and the technical field of artificial intelligence. The method comprises the following steps: acquiring a target data stream, and extracting multi-dimensional features based on the target data stream; performing integrity evaluation on the multi-dimensional features to obtain a data risk level; performing tampering detection on the multi-dimensional features to obtain a tampering detection result; and performing data processing operation on the target data stream based on the data risk level and the tampering detection result.

The invention belongs to the technical field of big data, and discloses a drawing quality evaluation management system and method based on big data. Comprising the following steps: extracting meta-information of a drawing, and extracting a category identifier by utilizing file name data and professional data in the meta-information to obtain a category of the drawing; carrying out marking; key information of the drawing is obtained, and a designer risk factor, a standard conformity risk factor and a version difference risk factor are calculated; calculating an integrity evaluation value of the drawing; dividing the drawings into defect drawings and standard drawings by utilizing the integrity evaluation values of the drawings; dividing a defect drawing into a first-level defect and a second-level defect; for a first-level defect, starting a multi-dimensional feature missing rate quality evaluation method to calculate a quality score of the defect drawing; for the standard drawing, calculating a quality score of the standard drawing according to the basic quality score and the proportion matching degree; and accurate data support is provided for drawing design and examination.

The invention provides a compliance governance evidence chain integrity analysis method based on block chain evidence storage, and relates to the technical field of block chains, and the method specifically comprises the steps: S1, collecting related transaction records and evidence storage data in block chain evidence storage records of an evidence chain through a block chain network; s2, managing the life cycle of the evidence chain data; s3, performing hash value comparative analysis on the block chain evidence storage record of the evidence chain to determine the integrity of the evidence chain; s4, carrying out traceability analysis through the evidence chain data; according to the method, the accuracy of data consistency verification can be improved, the normalization and safety of data life cycle management are enhanced, traceability analysis is performed through the causal relationship graph, and the reliability of data traceability evaluation is improved; and through multi-dimensional data analysis and standardized format output, generating an integrity evaluation report.

The invention provides a multi-modal signal acquisition and defect detection system for foundation pile integrity evaluation, and relates to the technical field of foundation pile integrity evaluation. The system is composed of a signal acquisition device and a defect detection system. The signal acquisition device comprises a supporting system, a lifting system and an auxiliary system, and is used for mounting an acceleration sensor, an ultrasonic transducer or an optical sensor required by defect detection. The defect detection system comprises a defect judgment module and a multi-modal data fusion unit. And the defect judgment module is used for performing low-strain defect detection, ultrasonic defect detection and optical defect detection on signals acquired by the sensors. And the multi-modal data fusion unit fuses the defect detection results, and performs comprehensive judgment on the foundation pile defects by adopting a priority classification and weighting calculation mechanism. According to the system, the defects of the foundation pile can be accurately detected, and integrity evaluation of the foundation pile is completed.

The invention discloses an underwriting risk assessment report generation method and system, and the method comprises the steps: obtaining the text data, insurance vehicle video streams and external environment data of an insured person in real time, and extracting a physical defect feature set of each vehicle video stream; performing cross-modal fusion on the text features, the physical defect feature set and the initial environmental risk factor score through an attention mechanism layer to generate a fusion feature vector, and decoding the fusion feature vector to obtain a target surface damage quantized value, a target part corrosion area proportion and a target environmental risk factor score; and through a preset target large language model, generating a structural integrity assessment item, a mechanical fault probability prediction item and an environment damage risk trend item one by one in an autoregression mode until all assessment items are generated, and obtaining an underwriting risk assessment report. According to the method, the physical state change of the insurance object can be dynamically captured, so that the timeliness and interpretability of risk assessment are improved.

The invention provides a concrete structure integrity evaluation method and device based on wave velocity image diagnosis, and is applied to the technical field of geophysical exploration, and the method comprises the steps: obtaining a vibration signal, monitored by a vibration sensor in real time, of a concrete structure; when the vibration signal exceeds a preset vibration threshold value, determining the vibration signal as a target vibration signal; identifying the target vibration signal, and when the target vibration signal is an internal micro-seismic signal of the concrete structure, determining the arrival time of a first arrival wave of the target vibration signal; on the basis of a speed model generated by preorder iteration, arrival time inversion positioning is carried out on arrival time of the first arrival waves, and focus coordinates of the target vibration signals are obtained; constructing a dynamic speed model based on the arrival time of the first arrival wave and the focus coordinates; and performing real-time evaluation and damage trend analysis on the interior of the concrete structure based on the dynamic speed model. According to the invention, high-precision real-time monitoring of the wave velocity distribution of the concrete structure can be realized.

The present invention relates to the technical field of wellbore risk assessment, and in particular to a method for quantitatively assessing the wellbore integrity risk of a carbon dioxide injection well, comprising: constructing a hierarchical model for injection well integrity assessment; determining the weight coefficient of each risk indicator; evaluating each risk indicator separately; calculating the total risk level score and determining the risk level. The present invention can comprehensively consider a variety of risk factors and achieve a detailed assessment of wellbore integrity through the determination of a hierarchical model and weight coefficients. The acquisition of real-time data and parameter correction ensure the accuracy and timeliness of the evaluation results. In addition, the method can identify high-risk areas in advance, achieve early warning and timely governance, and effectively solve the problem of low evaluation accuracy caused by the high subjectivity of the integrity analysis and evaluation method in the prior art, which makes it impossible to conduct a more objective quantitative evaluation of the wellbore integrity risk.

The application discloses a kind of multi-scale modeling and fracture simulation method for compressed air energy storage cover layer integrity evaluation, steps include: constructing multi-scale heterogeneous geomechanics model;Establish the fatigue damage constitutive relationship under rock loading and unloading condition;Establish fracture simulation control equation;Multi-scale calculation strategy and local adaptive grid are constructed;Cyclic loading condition simulation and integrity quantitative evaluation are carried out.The application is designed for the core damage mode of CAES gas storage low pressure fatigue, compared with general structure analysis software, the pertinence and accuracy of cover layer integrity evaluation are higher, the heterogeneous geological characteristics of cover layer are truly reflected, the process of crack initiation and propagation in cover layer under cyclic injection and production conditions is accurately simulated, and the advanced prediction and quantitative evaluation of cover layer integrity failure risk are realized.

This invention belongs to the field of road assembly technology and discloses a method, device, equipment, and storage medium for evaluating the integrity of concrete pavement. The method includes: obtaining a bending fatigue remaining life factor based on stiffness information; obtaining a bidirectional load transfer capacity factor for the assembled surface based on the difference in longitudinal and transverse loading displacements and the weights of the longitudinal and transverse load transfer coefficients; obtaining a structural interlayer vertical deformation coordination factor based on the assembled surface displacement, support layer displacement, and displacement tolerance; and obtaining a dynamic integrity index based on multiple factors for integrity evaluation. This invention quantifies pavement performance from three key dimensions—fatigue life, load transfer, and interlayer deformation—by calculating the bending fatigue remaining life factor, the bidirectional load transfer capacity factor for the assembled surface, and the structural interlayer vertical deformation coordination factor. It not only reflects the instantaneous state but also adjusts with changes in load and environment, enabling real-time evaluation during construction acceptance and long-term monitoring, thus improving the timeliness and accuracy of the evaluation.

Abstract A system for visually monitoring a wind turbine blade attachment region is disclosed. The system comprises at least one imaging sensor and a processor configured to extract visual reference features from captured image data and register the data to a spatial reference frame. Based on this spatial reference frame, the system identifies at least one unique component within the attachment region, such as pitch bearings and fasteners, to determine their precise location, orientation, and condition. The processor is configured to detect mechanical degradation, including positional displacements such as fastener rotation indicative of structural loosening, and surface anomalies such as cracking or lubricant leakage. The system may be further configured for independent blade pitch angle calculation, calibration of inertial measurement units using the visually derived reference frame, and temporal comparison of registered image data. Condition data and fault alerts may be output to an external interface for remote monitoring. Abstract 20 26 20 20 12 17 M ar 2 02 6 A b s t r a c t 2 0 2 6 2 0 2 0 1 2 1 7 M a r 2 0 2 6 A b s t r a c t 2 0 2 6 2 0 2 0 1 2 1 7 M a r 2 0 2 6

The application discloses a kind of underwriting risk assessment report generation method and system, comprising: the text data of the insured person, insurance vehicle video stream and external environment data are acquired in real time, and the physical defect feature set of each vehicle video stream is extracted;Text features, the physical defect feature set and initial environmental risk factor score are fused through attention mechanism layer across modalities, generate fusion feature vector, and the target surface damage quantitative value, target component rust area proportion and target environmental risk factor score obtained by decoding the fusion feature vector;Through the target large language model of pre-setting, in autoregressive manner item by item generate structure integrity evaluation item, mechanical failure probability prediction item and environmental damage risk trend item, until all evaluation items are generated, obtain the underwriting risk assessment report.The present application can dynamically capture the physical state change of insurance object, and then improve the timeliness and explainability of risk assessment.

The application provides a kind of deep sea umbilical cable sea trial scene structural integrity real-time detection system and method, related to ocean engineering technical field, the system includes core detection module, environmental adaptive module, data fusion processing module, integrated protection installation module, the method includes: sea trial preparation: confirm umbilical cable specification and research vessel winch layout;System installation and calibration: system axis and umbilical cable deployment path alignment, installation, calibration core detection module;Sea trial deployment monitoring: real-time data analysis based on mutation threshold algorithm, scientific decision-making;Real-time data processing and storage: real-time display of outer diameter curve, store data, screen suspicious areas;Umbilical cable recovery monitoring: secondary verification umbilical cable structure state, compare deployment data to generate difference report;System removal and maintenance, analysis to generate integrity assessment report.The application can detect the outer diameter, surface defects in the process of umbilical cable sea trial deployment and recovery in real time.

The present invention discloses an autonomous integrity assessment method for multi-source fusion positioning in a complex environment, comprising the following steps: A. constructing a GNSS PPP-RTK / INS tightly combined positioning method with a priori zero-value deviation constraints; B. constructing a zero-value deviation integrity discrimination equation; C. constructing a position and attitude joint lateral integrity assessment method, and then, based on a sensor attitude anomaly flag, adopting a PPP-RTK / INS / laser SLAM multi-source fusion estimation based on a graph optimization fusion positioning method to obtain the fused position and attitude of the intelligent rescue equipment after GNSS PPP-RTK / INS / laser SLAM; D. using a zero-value deviation-based correctness assessment equation to discriminate the correctness of the current zero-value deviation update, and updating the inertial navigation acceleration zero-value deviation and angular velocity zero-value deviation based on the zero-value deviation update correctness flag. The present invention fully utilizes the characteristics of the short-term stability of the inertial navigation zero-value deviation and the convergence of the postures of the carrier positioning sensors, ultimately achieving continuous, reliable and high-precision positioning of the intelligent rescue equipment.

This invention belongs to the field of data quality analysis, specifically disclosing a dataset quality analysis and evaluation method. It first performs an integrity assessment on the current dataset, initiating data confidence analysis only after the number of data groups meets the required standard. This ensures that the confidence assessment is based on structurally complete data, avoiding misjudgments due to missing data and improving analysis reliability. Simultaneously, during data confidence analysis, it constructs adjacent datasets for each data group, implementing dynamic comparison between the current data and its local temporal neighborhood. Furthermore, it combines historical reference datasets for longitudinal comparison with historical fluctuation ranges, integrating local consistency and historical comparability for dual verification. This significantly improves the sensitivity and accuracy of anomaly detection. Finally, when determining usability based on dataset integrity and confidence assessment results, a closed-loop feedback path is established with the acquisition end, enabling adaptive adjustment of the acquisition strategy based on risk location results.

The present invention discloses a ship management method and system based on digital twin scene construction. The method includes: acquiring multi-source scene data of the target waters in real time and constructing a corresponding digital twin model for ship management; conducting an integrity assessment on the constructed digital twin model and compensating for defects based on the assessment results to obtain an optimized digital twin model; further collecting ship density and weather condition data for each sub-area of ​​the target waters, constructing a network transmission delay prediction model, analyzing relevant data based on the model, and generating a network delay coefficient distribution map for the target waters; determining the real-time update lag of each sub-unit of the optimization model based on the delay distribution map, and correcting the ship position information in the digital twin model accordingly. This method can significantly improve the real-time performance and accuracy of the digital twin model and enhance the efficiency and safety of ship operation management in complex water environments.

The invention relates to a mining area road abnormity assessment method based on road surface data, and relates to the technical field of mining safety monitoring, and the method comprises the steps: collecting a road video stream in real time, and carrying out the frame analysis and preprocessing; extracting pavement textures, edge contours and three-dimensional geometric structure features; constructing an evaluation index set containing the flatness index, the retaining wall integrity coefficient and the notch density; recognizing retaining wall collapse, pavement gaps and structural deformation through a feature key point three-dimensional coordinate positioning technology; using a pre-training deep learning model to output a risk score; and generating a road integrity evaluation report containing the GIS positioning map and the risk thermodynamic diagram according to a fusion result. The system adopts a collaborative architecture of an edge computing unit and a central server, and integrates a 4K camera group, an FPGA acceleration module and a multi-source data fusion interface. According to the application, the limitation that the traditional monitoring technology depends on a single-point physical sensor is broken through, millimeter-level analysis and minute-level response of road microscopic deformation are realized, and the intelligent level of safety management of a mining area is remarkably improved.

The invention provides a real-time detection system and method for structural integrity of a deep-sea umbilical cable in a sea test scene, and relates to the technical field of ocean engineering.The system comprises a core detection module, an environment self-adaption module, a data fusion processing module and an integrated protection installation module; the method comprises the following steps: sea test preparation: confirming the specification of an umbilical cable and the layout of a scientific investigation ship winch; system installation and calibration: aligning a system axis with an umbilical cable laying path, and installing and calibrating a core detection module; carrying out sea trial deployment monitoring: analyzing data in real time based on a sudden change threshold algorithm, and carrying out scientific decision making; real-time data processing and storage: displaying an outer diameter curve in real time, storing data, and screening suspicious areas; umbilical cable recovery monitoring: verifying the structure state of the umbilical cable for the second time, and comparing laying data to generate a difference report; and dismantling and maintaining the system, and analyzing to generate an integrity evaluation report. According to the invention, the external diameter and surface defects of the umbilical cable in the marine test laying and recovery process can be detected in real time.

This application discloses a metacognitive reasoning and dynamic adaptive intent understanding system based on human-computer collaboration, belonging to the field of artificial intelligence technology. It includes: an input processing module that receives user input; a two-stage knowledge retrieval module that uses the MN-BERT model to classify user intents by difficulty to narrow down the retrieval scope, and then uses a Rerank model to refine the candidate intent set and filter out relevant intents; an LLM reasoning module that, based on the retrieval results, uses a large language model to perform metacognitive reasoning, locates the final target intent, and intelligently infers and completes the required parameters; an intent integrity assessment module that evaluates the completeness of the reasoning results; if incomplete, a multi-turn dialogue guidance module is triggered, which dynamically generates guidance questions through LLM and interacts with the user to complete the information; and a continuous learning and knowledge base update module that continuously collects interaction data, optimizes the model, and updates the knowledge base. This system solves the problems of balancing intent retrieval efficiency and accuracy, insufficient depth of reasoning for complex intents, and rigid interactive guidance.

A system for providing an interface that allows access to a system used to collect oil and gas pipeline integrity related data sets, inspection and survey reports to process the integrity status and to determine the remaining lifetime of each point of a pipeline on a sophisticated mapping platform. This system allows a user to access databases to access information needed for all pipeline integrity analysis. The system integrates the databases to allow easy access and centralized storage of all needed information for pipeline integrity assessment to deploy the results in an augmented reality platform. The system includes artificial intelligence to compare two or more consecutive In-Line Inspection reports to determine the internal and external corrosion rate in the oil and gas pipeline.

The invention discloses an underwater gravity navigation integrity evaluation method based on deep learning and time sequence modeling, and the method comprises the steps: firstly, achieving the matching positioning of an inertial navigation position and actually measured gravity data through the combination of a TERCOM algorithm and MSD correlation, and eliminating gross error points through confidence evaluation; for a data breakpoint area, B spline interpolation is adopted to carry out preliminary compensation. Furthermore, a DNN-LSTM cascade model is constructed, inertial navigation position increment and gravity data increment are input into a deep neural network, modeling is performed in combination with time sequence characteristics of a long and short-term memory network, and fine dynamic compensation of a gravity matching position is realized. According to the method, the continuity and precision of navigation position output and the system robustness are effectively improved, and the method is suitable for high-reliability autonomous navigation in a complex underwater environment.

The present invention discloses a distribution network line loss assessment method, apparatus, device, and storage medium. The method includes standardizing target distribution network data to obtain multidimensional standardized data; analyzing the multidimensional standardized data to identify abnormal data points, extracting features from the abnormal data points, and obtaining spatiotemporal characteristic factors; performing high-dimensional mapping on the multidimensional standardized data to obtain NTK similarity; weightedly fusing the spatiotemporal characteristic factors with the NTK similarity to obtain a final similarity; performing nearest neighbor screening on the abnormal data points to obtain nearest neighbor data; repairing the nearest neighbor data based on the final similarity to obtain a first data set; performing integrity assessment, consistency assessment, and accuracy assessment on the first data set to obtain a comprehensive assessment result; and calculating line losses on the first data set based on the comprehensive assessment result. The method of the present invention improves the accuracy of distribution network line loss calculation.

The present invention provides a stroke risk warning method and system based on digital twins, relating to the technical field of stroke risk warning. The method comprises the following steps: acquisition assessment; acquisition update delay assessment; acquisition update integrity assessment; and stroke risk prediction. The present invention analyzes acquisition control data and determines whether to perform acquisition update delay assessment and acquisition update integrity assessment. If acquisition update delay assessment is performed, it determines whether to perform acquisition update delay optimization. If acquisition update integrity assessment is performed, it determines whether to perform acquisition update integrity optimization. Finally, the stroke risk prediction level is obtained, thereby achieving the effect of improving the accuracy of stroke risk warning data and solving the problem of low accuracy of stroke risk warning data in the prior art.

The invention provides a multi-dimensional dynamic risk map-based intelligent and inexpensive assessment early warning method, which comprises the following steps of: acquiring multi-modal data from an internal system and an external platform of an enterprise through an API (Application Program Interface), and providing input for subsequent data fusion; fusing the multi-modal data by adopting a multi-modal variational auto-encoder, dynamically adjusting the feature weight through online Bayesian updating, and generating unified potential representation and risk score; constructing a space-time diagram based on the potential representation and the risk score, generating space-time risk features through a space-time diagram neural network, constructing a dynamic knowledge graph, and predicting a risk causal path by adopting a structural causal model; and visualizing the space-time risk characteristics and the risk causal paths through a three-level data cockpit, generating a risk distribution thermodynamic diagram, and pushing early warning information including risk scores, the risk causal paths and the positions of the thermodynamic diagram through a mobile terminal application. The scheme can be used for realizing low-cost early warning and evaluation through multiple dimensions.

The present invention discloses an artificial intelligence-based pipeline integrity assessment method and device. The method comprises: acquiring magnetic induction detection signal data from the pipeline and processing the magnetic induction detection signal data; inputting the magnetic induction detection signal data into an integrity assessment model to determine the pipeline defect location, repair level, defect type, and whether there is metal or tree interference; the integrity assessment model is pre-trained and tested. Based on the magnetic induction detection signal data, the present invention proposes an intelligent pipeline integrity assessment method that is highly accurate, adaptable, and unaffected by human subjective factors. This method effectively improves the accuracy of pipeline assessments, effectively avoids blind repairs, and significantly improves economic efficiency, reduces labor costs, and enhances pipeline safety.

The invention discloses a substation monitoring equipment integrity evaluation method based on fuzzy synthesis. According to the method, firstly, construction of a transformer substation monitoring equipment integrity evaluation index system is studied; a plurality of related standards such as technical specifications of equipment such as a monitoring host, a measurement and control device and a gateway machine of the transformer substation monitoring system are integrated, necessary and universal equipment integrity monitoring indexes in the state monitoring process of the monitoring equipment are compared and selected, and an equipment integrity evaluation index system of the transformer substation monitoring system is constructed. Secondly, how to apply the multilevel fuzzy synthesis method to integrity evaluation of the monitoring equipment is researched, and an integrity evaluation result of the equipment is obtained; furthermore, the feasibility of the method is researched and verified. And forming a closed-loop verification chain in an expert argument mode by adopting a subjective and objective combined verification system through a Kendall harmony coefficient and an acceptance degree index.

The invention discloses a power distribution network line loss evaluation method, device and equipment and a storage medium, and the method comprises the steps: carrying out the standardization processing of target power distribution network data, and obtaining multi-dimensional standardized data; analyzing the multi-dimensional standardized data, identifying abnormal data points, and performing feature extraction on the abnormal data points to obtain spatial-temporal feature factors; performing high-dimensional mapping on the multi-dimensional standardized data to obtain NTK similarity; performing weighted fusion on the spatial-temporal characteristic factor and the NTK similarity to obtain a final similarity; performing neighbor screening on the abnormal data points to obtain neighbor data; repairing the neighbor data according to the final similarity to obtain a first data set; performing integrity evaluation, consistency evaluation and accuracy evaluation on the first data set to obtain a comprehensive evaluation result; and performing line loss calculation on the first data set based on the comprehensive evaluation result. According to the method, the accuracy of power distribution network line loss calculation is improved.

The embodiment of the invention provides a method and system for testing the fire resistance of a fiber-wound hydrogen cylinder and related equipment, and belongs to the technical field of hydrogen storage cylinders. The method comprises the steps that a fire test is conducted on a target gas cylinder through a fire source, temperature data of a preset position of the target gas cylinder and pressure data of hydrogen pressure are obtained, and the preset position at least comprises a composite material layer; in the burning process, when the pressure data is continuously reduced and characteristic flames generated by leakage of the target gas cylinder are monitored, it is determined that the target gas cylinder leaks, and form data of the characteristic flames are monitored and recorded; when the pressure data of the target gas cylinder is reduced to a preset pressure value, it is determined that the burning test is finished, and corresponding burning time is obtained; and performing integrity evaluation on the target gas cylinder after the burning test is finished, and determining the fire resistance according to an evaluation result, the burning time, the form data, the temperature data and the pressure data. The embodiment of the invention aims to improve the accuracy of evaluating the fire resistance of the carbon fiber wound hydrogen storage cylinder.

The embodiments of the present disclosure provide a data asset completion method, apparatus, device and medium, which relate to the field of big data technology. The method includes: performing domain division on the table metadata assets of the system data assets, obtaining the domain type to which each table metadata asset belongs, and the table metadata assets include table metadata and field metadata; performing integrity assessment on each table metadata asset, marking the missing table metadata assets, and obtaining marked table metadata assets; matching the marked table metadata assets with the data to be matched based on the domain type, and completing the marked table metadata assets based on the matching results, and the data to be matched includes a data asset dictionary. According to the technical solution of the embodiments of the present disclosure, accurate identification of data asset domains and automatic completion of missing data can be achieved, which greatly improves the readability and availability of key information in data assets.