103 results about "Modal analysis" patented technology

This invention relates to the field of data processing and discloses a method, system, and electronic device for generating multimodal data from multiple dimensions. The method includes: acquiring raw data from at least two dimensions; integrating and synchronizing the raw data from each dimension; annotating the data characteristics of different dimensions using corresponding analysis methods; extracting semantic information and structured features of each dimension to obtain annotation results for each dimension; analyzing each annotation result using a corresponding analysis model to obtain modal analysis results; assigning appropriate weights to each modal analysis result based on the credibility, historical accuracy, and importance of the raw data; fusing the modal analysis results using a weighted fusion method to generate multimodal data; and generating final multimodal data after iteration. This application achieves the technical effects of multimodal data alignment, annotation, fusion, and generation of new data.

The present application relates to the technical field of data processing, and specifically discloses an electronic insurance policy intelligent verification and repair method, system, device and medium. The present application extracts structured insurance policy data through multi-modal analysis, performs hierarchical processing in combination with a large model semantic verification and confidence evaluation model, respectively executes automatic repair or generates a manual processing task carrying repair guide information according to different confidence levels, and iteratively optimizes the large model and the confidence evaluation model based on repair process data and results, thereby solving the problems of low artificial sampling efficiency, high failure and leakage rate of rule templates facing non-standard insurance policies, uncontrollable output of general large models, and lack of confidence calibration and closed-loop repair capabilities, and achieving dual improvement of electronic insurance policy verification accuracy and automation processing efficiency.

This invention discloses an automated data security assessment method and system based on intelligent agents, belonging to the field of data security technology. It includes defining and constructing multiple intelligent agents, determining agent attributes, and generating capability profiles for the agents based on these attributes, providing a reliable foundation for subsequent modal analysis and resource scheduling. Multimodal analysis is performed on data assets, and resource scheduling and allocation are performed based on the agent capability profiles. Output conflicts are handled through a confidence-flow arbitration mechanism. Traditional automated tools often generate numerous false positives or false negatives due to rigid rules. This system no longer simply takes the union or intersection of values, but uses a dynamically flowing confidence algorithm for automatic adjudication. The risks of data assets are quantified based on attack graphs and Bayesian networks. Reasonable scheduling and coordination of multiple intelligent agents resolve conflicts between them, improving the efficiency and reliability of automated data security assessment and meeting complex and ever-changing security assessment needs.

The application discloses a bridge structure stability intelligent detection method and system based on DAS, and relates to the technical field of bridge health monitoring. A distributed optical fiber sensing device is used to obtain vibration signals at multiple positions of a bridge, a multi-channel vibration data matrix is established after denoising processing of the vibration signals, a random subspace identification method is used for modal analysis, and real-time modal parameters of the bridge structure are obtained. According to the reference modal parameters, modal characteristic data is calculated and input into a pre-trained detection model to obtain a bridge state detection result. The application uses DAS to realize multi-point high-density monitoring, improves analysis accuracy by combining denoising and modal recognition technology, realizes automatic and intelligent detection of the bridge structure stability through an intelligent model, reduces manual intervention, and improves monitoring efficiency.

This application discloses a pipeline monitoring system and method, relating to the field of water conservancy engineering technology. The system includes: data acquisition devices installed on the inner wall concrete protective layer of a prestressed steel cylinder pipeline to collect pipeline data; a hybrid transmission network obtained by combining LoRa and NB-IoT technologies based on regional signal transmission characteristics; and the transmission of multi-dimensional monitoring parameters to a cloud analysis platform for pipeline health assessment. This application overcomes the bottleneck of underground scene data acquisition by using multi-parameter coupled sensing of the data acquisition device and piezoelectric energy acquisition technology, acquiring rich multi-dimensional data; reliable data transmission in complex underground environments is achieved based on dynamically switched clustered wireless networks; and the cloud analysis platform, based on multi-dimensional monitoring parameters and integrating a multi-modal analysis engine, provides a full life-cycle health status profile for the pipeline, improving the accuracy of pipeline monitoring.

This invention proposes a method for multi-target recognition, tracking, and vibration extraction of bridge cable-stayed bridge videos based on unmanned aerial vehicles (UAVs). The method includes: Step 1: Constructing a refined tilted and slender target detection model for bridge cable-stayed bridges based on the YOLOv11 model; Step 2: Proposing a multi-target tracking algorithm that integrates the tilted and slender target detection model and the StrongSORT algorithm; Step 3: Improving the displacement extraction method by combining SIFT / ORB feature point matching and sub-pixel refinement techniques; Step 4: Designing a UAV motion correction algorithm based on variational mode decomposition and time-frequency domain joint screening; Step 5: Constructing a joint working mode analysis algorithm that combines natural excitation technology and random subspace recognition algorithm. This method achieves high-precision extraction of cable-stayed bridge vibration signals and identification of cable-stayed bridge modal parameters, providing technical support for health monitoring of long-span cable-stayed bridges.

This application relates to the field of vehicle-related technology, and discloses a method, apparatus, equipment, and vehicle for vibration modal analysis of a vehicle spoiler. The Z-axis dimension of the target portion in the X-direction cross-section of the spoiler is smaller than the Z-axis dimensions of its two side portions. The method includes: substituting the free end overhang length, intermediate cavity height, elastic modulus, and material density of the spoiler into a preset simplified estimation formula for calculation, and outputting a first-order vibration modal estimation value; the intermediate cavity height is the Z-direction cross-sectional height at the narrowest cavity of the spoiler; the preset simplified estimation formula satisfies that: the square of the first-order vibration modal estimation value is directly proportional to the product of the elastic modulus and the square of the intermediate cavity height, and inversely proportional to the product of the material density and the fourth power of the free end overhang length; based on the first-order vibration modal estimation value, the vibration modal analysis result of the spoiler is determined. Applying the technical solution of this application can solve the problems of high analysis resource consumption, low efficiency, and high cost currently existing.

This application discloses a time synchronization monitoring method, device, terminal equipment, and storage medium. The time synchronization monitoring method includes: collecting corresponding monitoring data signals for different locations of a preset building; performing modal analysis on the monitoring data signals to obtain several corresponding intrinsic mode function signals; fitting the errors between the intrinsic mode function signals to obtain the relative time error of the location; and eliminating the errors between the monitoring data signals based on the relative time error to obtain synchronized monitoring data. This method can solve the technical problem of time errors in monitoring data from different locations in the time synchronization monitoring of super high-rise buildings, reduce the monitoring cost of time synchronization, and synchronously analyze monitoring data from different locations, thereby providing a more accurate data foundation for structural damage identification and safety assessment.

The application relates to the technical field of artificial intelligence, in particular to an intelligent memory storage method based on multi-modal analysis and time sequence knowledge graph; the method is characterized in that multi-modal input information input by a user during interaction is textually analyzed to obtain a multi-modal text set; a text sequence formed by the multi-modal text set generated by multiple interactions is semantically disassembled to extract a knowledge unit set; a timestamp is added to the knowledge unit, the timestamp comprises an effective time interval of an event corresponding to an atomic fact extracted in the knowledge unit and a system recording time; a memory graph is constructed based on the knowledge unit with the timestamp, so as to search context information during subsequent interaction. The application has the effect of improving the accuracy of an intelligent agent in answering or helping a user to make a decision.

The application discloses a story interactive active questioning method and system based on cognitive characteristics of children, and relates to the technical field of artificial intelligence. The method comprises the following steps: obtaining story content; performing multi-modal analysis on the story content to obtain an analysis result; constructing a four-dimensional cognitive model of a child according to the analysis result and historical interaction data of the child; selecting a target problem level in preset multi-level problems according to the four-dimensional cognitive model; generating an adaptive question corresponding to the target problem level; and updating the four-dimensional cognitive model and the multi-level problems according to the answer and emotional feedback of the child to the adaptive question. The application first analyzes the story content and then generates a corresponding adaptive question in combination with the cognition of the child, so that the generated story question matches the cognition of the child, the problems beyond the cognition of the child are reduced, the adaptability is improved, and the learning and understanding effect of the child is improved.

The application discloses a large-scale quay crane structure seismic excitation damping coefficient calculation method, and belongs to the technical field of port large-scale track structure earthquake resistance; the method comprises the following steps: constructing a finite element simulation model of the quay crane structure; establishing a Rayleigh damping equation based on the finite element simulation model; extracting the first-order natural frequency of structure vibration under X direction excitation through modal analysis, and extracting the main frequency of the seismic wave through spectrum analysis on the input seismic wave; determining the damping ratio ξ of the finite element simulation model; determining two basic frequencies of the Rayleigh damping equation according to the first-order natural frequency and the main frequency of the seismic wave, wherein the first basic frequency is ω1, the second basic frequency is ω2, and n is an odd number greater than 1; and calculating the damping coefficient c according to the damping ratio and the two basic frequencies; the application considers the dynamic characteristics of the quay crane structure and the spectrum characteristics of the seismic wave, improves the accuracy of the damping coefficient calculation, and makes the seismic response simulation result more reliable.

This application provides a design method, apparatus, device, storage medium, and program product for a tailgate structure. The method includes: obtaining an initial tailgate structure and a preset tailgate performance optimization target; constructing a performance analysis model of the initial tailgate structure; the performance analysis model includes at least a modal analysis model and at least one attribute performance analysis model; the tailgate performance optimization target includes at least a preset modal target value and at least one attribute performance target value; using the preset modal target value and at least one attribute performance target value as constraints, and based on the modal analysis model and at least one attribute performance analysis model, determining the optimization parameters of the initial tailgate structure; and using the optimization parameters to perform structural optimization on the initial tailgate structure to obtain the optimized tailgate structure. This application enables the acquisition of a low-modal tailgate, thereby reducing road noise and ear pressure in the vehicle.

The application discloses a kind of aerodynamic damping analysis method based on influence coefficient method and vibration phase correction, it is related to the technical field of aerodynamic damping analysis of turbomachinery.The technical solution points include the following steps: according to the aerodynamic profile and structural model of blade, fluid domain model and solid domain model are established respectively;Carry out steady flow field analysis on fluid domain model, and provide initial field for non-steady flow field calculation;Modal analysis is carried out on solid domain model, and the natural frequency and modal shape of blade under rotating condition are obtained;Designate intermediate blade to vibrate according to the modal shape and natural frequency obtained, and carry out non-steady flow field analysis with steady flow field result as initial field;After calculation convergence, extract the aerodynamic force on blade surface, and calculate the aerodynamic work on blade under different pitch diameters.The application can give the situation under all pitch diameters by once non-steady flow field calculation, without multiple calculation of non-steady flow field under different pitch diameters, more quickly and efficiently, save calculation resources.

A method, system, medium, and equipment for synchronous extraction and analysis of ultrasonic-vibration multimodal data of on-load tap changers of transformers are disclosed. The method employs a piezoelectric ultrasonic-vibration fusion sensor to simultaneously sense ultrasonic signals generated by discharge and vibration signals generated by mechanical vibration. Wavelet packet decomposition is performed on the composite electrical signal to adaptively separate the ultrasonic signal components and vibration signal components. Ultrasonic features of the ultrasonic signal components, including time-domain, frequency-domain, and time-frequency features, and vibration features of the vibration signal components, including time-domain, frequency-domain, and time-frequency features, are extracted separately. Kernel canonical correlation analysis is used to obtain the nonlinear correlation between the ultrasonic and vibration features, and cross-modal joint features are extracted. A deep neural network fusion diagnostic model is constructed, and the cross-modal joint features are input into a classifier for state identification, outputting the health status of the on-load tap changer.

The application discloses a communication product configuration method based on multi-modal analysis and vector matching, and particularly relates to the technical field of intelligent configuration of communication products, and is used for solving the problem that the efficiency of manually reading documents and manually selecting and configuring is low, errors are easy to occur, and it is difficult to trace back when the customer demand is proposed in the form of multi-source and multi-format documents, the field caliber is complex, and the rule constraints are numerous in the group and government and enterprise customer scenarios of operators. By taking the field dictionary and structured constraints as the basis, the multi-source and multi-format communication product demand document is sequentially converted into demand parameters, demand configuration graphs and multi-channel feature vectors, and vector matching of rule perception such as field mandatory, mutual exclusion of rights and interests, region, contract period and cost is performed on the hierarchical near neighbor graph index in combination with the template graph, so that the communication product configuration scheme meeting the business constraints is automatically output under the unified caliber, the workload of manually reading documents and selecting by experience is significantly reduced, and the accuracy and consistency of the configuration result in the complex scenario are improved.

This application provides a Doppler laser mode shape measurement method and apparatus, comprising: S1, calibrating a laser vibrometer; S2, using the laser vibrometer to emit a laser, such that the emitted laser beam is precisely focused and perpendicularly irradiated onto the test point on the surface of the object being measured; S3, acquiring a time-domain vibration displacement signal; S4, preprocessing the time-domain vibration displacement signal, synchronizing the force signal, and acquiring an effective time-domain vibration displacement signal; S5, processing the preprocessed effective time-domain vibration displacement signal to acquire vibration velocity, vibration displacement, and vibration frequency; S6, visualizing the vibration velocity, vibration displacement, and vibration frequency obtained from modal analysis.

The application relates to a wine cellar fire control strategy acquisition method and device, computer equipment, a medium and a product. The method comprises the following steps: acquiring multi-modal data in a wine cellar environment, compensating for drift of the multi-modal data to obtain target data, extracting visual spatial features of the target data through a target detection network model, extracting time sequence features of the target data through a machine learning network model, fusing the visual spatial features and the time sequence features to obtain fused features, performing fusion analysis on the fused features through a multi-modal analysis model to obtain fire risk grades and fire source positioning information, constructing a fire spread model according to the fire source positioning information and spatial structure information, acquiring a fire spread area according to the fire spread model, and acquiring a wine cellar fire control strategy according to the fire risk grades and the fire spread area. The method can improve detection accuracy.

The invention provides an artificial intelligence-based system for generating personalized medical information through the integration of multi-modal data across pre-hospitalization, hospitalization, and post-hospitalization phases. The system employs encoder modules to process diverse input modalities, including audio recordings, video streams, biomedical images, text-based clinical records, and physiological signals. These encoded representations are integrated into a unified latent space using a large language model (LLM) trained on medical datasets comprising historical patient cases, anatomical knowledge, and treatment guidelines. The LLM enables cross-modal analysis to generate personalized outputs via decoder modules, which transform the latent space representation into actionable formats like text-based summaries, visualizations, audio explanations, and treatment suggestions. A key innovation is real-time intraoperative feedback via encoder-decoder modules detecting anatomical structures and deviations from standard protocols. The system also includes a federated learning module to aggregate model updates across medical centers while preserving patient privacy through deidentification protocols.

The application provides a multi-dimensional cognitive state vector simulation agent digital textbook dynamic adaptability evaluation method, and relates to the technical field of artificial intelligence assisted education. The method comprises the following steps: extracting teaching entities and semantic relationships between the entities in a source file of a digital textbook to be evaluated through a multi-modal analysis model, and constructing a knowledge graph; initializing multiple groups of virtual learning agents based on a pre-trained large language model, and configuring differentiated cognitive state vectors for each group of virtual learning agents; driving each group of virtual learning agents to traverse the teaching knowledge graph according to a topological sorting by using a knowledge boundary mask mechanism, obtaining understanding feedback of each node by each group of virtual learning agents, and generating confusion degrees and thought chains in the understanding feedback process; calculating a cognitive block index and an adaptability distribution curve of the source file of the digital textbook by using a weighted summation algorithm, and generating an evaluation report. The application simulates human cognitive processes by using a large language model agent, and evaluates the quality and adaptability of a digital textbook.

This invention relates to a method for separating vibration and flow noise in the underwater noise spectrum of a ship propeller, comprising: constructing a "frequency label" for vibration noise by fabricating two propeller models with identical geometry but significantly different material properties; a dual-model difference stage: calculating the absolute difference in the noise spectra of the two models and generating a vibration noise mask based on modal analysis results; a blind source separation stage: for the residual signal after difference, using an improved Independent Component Analysis (ICA) algorithm to further separate residual interference by utilizing the statistical independence of vibration noise; introducing a convolution kernel function in this stage to enhance the algorithm's adaptability to time-delayed signals; and introducing Cepstrum analysis technology to perform phase correction on the complex spectrum of the replacement frequency band. This method solves the significant shortcomings of existing noise control technologies in the coupling separation of vibration and flow noise, enabling the separation of the components of underwater noise from ship propellers, obtaining the noise components caused by blade vibration and the flow noise components separately.

The application discloses a kind of based on big language model's pollutant multi-modal information extraction method and system, belong to environmental information processing technical field, face to include text, table, image's pollutant related academic papers and monitoring report, design six big core steps of end-to-end processing procedure of six big core steps of multi-modal analysis-attribute system construction-stage extraction-cross modal fusion-quality control-structured output, in combination with big language model workflow scheduling, terminology normalization, cross-modal consistency check and quality control mechanism, realize the standardization and high-precision extraction of pollutant information, while generating structured data with evidence chain.The application does not need a large number of artificial rule configuration, can realize text-table-image collaborative analysis and cross-validation, reduce model calling redundancy, improve complex information extraction accuracy, enhance data comparability and traceability, suitable for multi-type environmental pollutant literature and monitoring data automatic processing and pollution spatiotemporal information management.

The application discloses a kind of methods for quickly building building structure simulation model. Including the following steps: S1: obtaining the characteristic information of building layout, defining and initializing adjustable parameter range;S2: building building structure overall information matrix;S3: defining various structure load action;S4: modal analysis and stiffness matching are carried out to structure;S5: establishing structure calculation model, and carrying out reinforcement design;S6: the safety, economy statistical index of classified selection output model is selected, and the optimal structure scheme is selected according to weight. To solve the problem that the overall stiffness of the model established automatically does not have a unified target, resulting in the overall index result of model calculation being far from the specification requirement, the workload is large, the problem of needing to adjust the model repeatedly for trial calculation again in later period, realize the quick construction of building structure simulation model, improve the efficiency of model establishment.

The application is suitable for the technical field of oil pan design, and particularly relates to an oil pan modal and multi-rigidity collaborative design method, device and equipment. The method comprises the following steps: establishing an oil pan finite element model; performing modal analysis according to the finite element model to obtain the minimum order natural frequency of the oil pan; performing rigidity analysis according to the finite element model to obtain the static rigidity of multiple key points of the oil pan; obtaining a modal margin based on the minimum order natural frequency of the oil pan and the maximum excitation frequency of the engine; obtaining n rigidity margins based on the static rigidity of the multiple key points of the oil pan and the corresponding key point rigidity requirement values; jointly evaluating a design state according to the modal margin and the n rigidity margins, and modifying the finite element model according to the design state; and iterating the modified finite element model until the joint evaluation result meets the standard to obtain a final design. In the method, the problem of low design efficiency and unbalanced performance of the existing design method of the automobile oil pan can be solved.

The application provides a flight path analysis model and a training method, a flight path analysis method and equipment and a medium, and belongs to the technical field of artificial intelligence. The model comprises: a flight path coding network, which is used for receiving a flight path sequence of an aircraft and extracting first flight path hidden features; a physical consistency constraint network, which is used for predicting physical state features and performing constraint based on a motion feasible region, and then fusing to generate second flight path hidden features; a multi-modal adaptation network, which is used for cross-modal fusion of the second flight path hidden features and analysis instruction features to obtain multi-modal input features; and a large language model network, which receives the input features to perform semantic reasoning and generates a flight path analysis result text. The application guarantees that the features conform to the physical motion law through the physical constraint network, and realizes deep alignment of the flight path and language through the cross-modal network, thereby breaking through the single-modal analysis bottleneck and significantly improving the high-order analysis capability of flight path situation understanding and reasoning in a complex low-altitude scene.

The application relates to the technical field of computer information processing, in particular to a multi-modal video structured analysis and intelligent playing system and method based on a semantic time axis, aiming at the problems of insufficient video structured analysis capability, separation of playing and knowledge content, low processing efficiency and the like, a distributed asynchronous task architecture is constructed, audio and video preprocessing, speech recognition, time sequence semantic segmentation, subtitle generation and summary extraction are completed through a multi-modal analysis engine, and structured knowledge data accurately bound with a video time axis are generated. After automatic verification and manual review are completed through a quality control module, the structured knowledge base realizes associated storage of original videos and structured data and multi-dimensional index construction, and an intelligent interactive player realizes chapter navigation, subtitle synchronization and knowledge card linkage display in dependence on the semantic time axis. The application realizes standardized and structured conversion of unstructured videos, improves video processing efficiency and resource utilization, and reduces user knowledge acquisition cost.

The application provides a large model-based intelligent work order processing method, system, device and medium, and relates to the technical field of computer data processing and artificial intelligence. The method comprises the following steps: acquiring work order data containing text and images, calling a large language model and a visual large model to extract structured fault features; after the fault features are vectorized, searching in a multi-type knowledge base, and constructing prompt words through a three-level weighted fusion mechanism to input the large model to generate an optimal processing scheme; meanwhile, combining historical maintenance data and a variance threshold algorithm to predict accessories and dispatch. In addition, the system supports front-end interception and real-time push of self-service solutions. Through multi-modal analysis, structured knowledge fusion and large model proxy mechanism, the application breaks through the limitations of traditional keyword search, realizes accurate fault recommendation, on-demand preposition of accessories and simple work order intelligent interception, and significantly improves after-sales efficiency and customer experience.

The application belongs to the technical field of digital management of construction data, and discloses a construction data instant generation and whole-process collaborative management platform, which comprises a field instant digital recording module, a template collection and intelligent auxiliary input of construction data are realized through a mobile terminal, an automatic structured processing module, original unstructured data is automatically converted into structured data by using a rule engine and a multi-modal analysis technology, a consistency dynamic checking module, the compliance and logical consistency of data are checked in real time through a built-in specification knowledge base, historical data comparison and a multi-party cross-validation mechanism, a transparent handover tracking module, whole-process traceable management of data from collection to archiving is realized through version control, process visualization and electronic signature storage. The application realizes instant generation, automatic processing, dynamic checking and transparent handover of construction data, and significantly improves the efficiency, accuracy, standardization and traceability of data management.