18 results about "Static response" patented technology

The invention discloses a multivariate monitoring data fusion method and system for a slope tunnel model test, particularly relates to the technical field of geotechnical engineering physical model test, and aims to solve the problem that dynamic stress waves in an existing model test integrating static and dynamic measurement cause static monitoring signal distortion and further influence the model state evaluation accuracy. Coupling interference in static signals is identified by synchronously collecting dynamic excitation and static response signals; obtaining signal samples before and after a model state sudden change event to perform frequency domain comparative analysis, identifying characteristic frequency components related to sudden change, and evaluating a coupling interference dominant frequency band; separating an effective static response component from the original static signal based on the frequency band; and finally, fusing the effective component with a soil dynamic parameter derived from dynamic excitation to generate comprehensive stability evaluation data. Dynamic interference is effectively suppressed, the authenticity of static signals is improved, and the reliability of model stability state evaluation is improved.

The invention belongs to the technical field of hydraulic engineering digital twinning, and provides an arch dam static response rapid calculation method which comprises the following steps: sampling and simulating based on a finite element model in an offline stage to obtain a displacement field snapshot matrix, extracting a dominant mode through intrinsic orthogonal decomposition to construct a reduced-order subspace, and calculating a mode coefficient; and training a radial basis function neural network to establish a nonlinear mapping relation by taking the working condition parameters as input and the modal coefficient as output, and finally, inputting the target working condition parameters into the trained network to predict the modal coefficient in an online stage, and quickly reconstructing a complete displacement field response through linear combination with the POD modal. The method achieves the quick and accurate prediction of the static physical field of the arch dam, and remarkably improves the calculation efficiency of the displacement field of the arch dam.

The invention relates to the technical field of solid mechanical modeling, and solves the technical problem that an existing unified mechanism modeling strategy neglects geometric nonlinear characteristics of local weak-rigidity parts of an assembly, so that the static response prediction precision of the assembly is not high. The assembly deformation stress cooperative control-oriented aircraft rigid-flexible hybrid structure multi-level analysis method comprises the following steps: carrying out linear and nonlinear response analysis on finite element models of rigid framework parts and weakly rigid thin-wall parts, and establishing a linear mapping model and a nonlinear explicit mapping model; combining the two models to obtain a deformation stress analysis model; and obtaining a clamp holding force-displacement stress mapping model for representing the mapping relationship between the multi-point holding force of the assembly and the node displacement and the node stress based on the deformation stress analysis model. According to the method, the problems of lack of explanation and few mechanisms of a variable stiffness structure model are solved, and efficient prediction and damage early warning of the internal stress of the component are realized.

The application discloses a kind of multivariate monitoring data fusion method and system of side slope tunnel model test, is specifically related to geotechnical engineering physical model test technical field, for solving the problem that dynamic stress wave in the model test of existing integrated static and dynamic measurement causes static monitoring signal distortion, and then influence model state assessment accuracy;By synchronously collecting dynamic excitation and static response signal, identify the coupling interference in static signal;Frequency domain comparative analysis is carried out using signal sample before and after model state mutation event acquisition, identify the characteristic frequency component related to mutation, and evaluate the dominant frequency band of coupling interference;Based on the frequency band, separate the effective static response component from the original static signal;Finally, this effective component and the soil dynamic parameter derived from dynamic excitation are fused, to generate comprehensive stability evaluation data to realize;Effectively suppress dynamic interference, improve the authenticity of static signal, improve the reliability of model stability state assessment.

The invention discloses a truss structure nonlinear buckling stability optimization design method based on a finite mass point method and automatic differentiation, and the method comprises the steps: constructing a parameterized truss model, and taking the cross-sectional area and / or node coordinates of a rod piece in the parameterized truss model as design variables; constructing an optimization objective function for determining the nonlinear buckling stability performance of the structure as an objective; and on the basis of the parameterized truss model, constructing a corresponding finite mass point method analysis model, and performing iterative optimization on the optimization objective function in the process of simulating nonlinear static response to buckling in the finite mass point method analysis model in combination with automatic differential software, so as to output a final design variable as the optimal truss structure design. The method provided by the invention can effectively solve the problem of buckling stability optimization of the truss structure which becomes abnormally complex due to geometric nonlinearity and path dependence characteristics.

The invention relates to a nonlinear structure reduced-order model construction method based on sparse recognition and a mixed mode, belongs to the technical field of structural dynamics analysis and aeroelastic mechanics analysis, and solves the problem that complex motion caused by geometric nonlinearity under large deformation cannot be accurately described in the prior art. Comprising the following steps: S1, establishing a nonlinear finite element model of a target large flexible wing to obtain a training data set; s2, solving a mixed modal basis based on the displacement residual error and SVD (Singular Value Decomposition); s3, establishing a nonlinear stiffness coefficient solving problem model, introducing LASSO regression to establish an LASSO regression optimization objective function, and solving to obtain a sparse nonlinear stiffness coefficient; s4, based on the sparse nonlinear stiffness coefficient and the structural kinetic equation, establishing a nonlinear structure reduced-order model; and S5, applying the nonlinear structure reduced-order model to statics response solution and dynamics response solution of the large flexible wing to obtain statics response and dynamics response results.

The invention discloses an intelligent elevator predictive maintenance method and system based on an AI large model, and relates to the technical field of intelligent equipment operation and maintenance and fault diagnosis. Extracting characteristic indexes of the multi-modal operation data, inputting the characteristic indexes into a pre-trained AI large model, and outputting a fault prediction result of the elevator; and based on the elevator fault prediction result, grading early warning is conducted on elevator faults, and an elevator maintenance strategy is generated according to early warning information. According to the method, comprehensive perception of the running state of the elevator is achieved, accurate recognition and early warning of potential faults are achieved, and prediction sensitivity and accuracy are remarkably improved; and grading early warning is performed based on the prediction result, and a maintenance strategy is generated, so that maintenance conversion from static response to dynamic matching is realized, the maintenance resource scheduling efficiency and the system operation reliability are effectively improved, and the targets of intelligentization, foresight and high efficiency of elevator operation and maintenance are integrally achieved.

The application discloses a kind of based on vehicle movement loading small and medium-sized bridge bearing capacity evaluation method, belong to bridge bearing capacity evaluation technical field, comprising the following steps: S1: time history response acquisition;S2: time history response preprocessing;S3: influence line identification;S4: bearing capacity evaluation.The application utilizes single heavy vehicle movement loading to obtain bridge time history response;Then the structural dynamic component in bridge time history response is stripped using variational mode decomposition, and then a bridge influence line identification mathematical model is constructed according to sampling frequency and vehicle wheelbase, so as to eliminate the vehicle multi-axle effect in bridge time history response;And the stable solution of bridge influence line is solved using Tikhonov regularization method;Then by carrying out virtual loading on bridge influence line, reconstructing bridge virtual static response, and using traditional check coefficient method to evaluate bridge bearing capacity, the bridge bearing capacity evaluation rate is effectively improved, and the bridge structure damage caused by high loading efficiency is avoided.

This invention provides a measurement method, measuring device, measuring system, and measuring program, capable of calculating the static and dynamic responses of a moving body on a structure with high precision. In this measurement method, first measurement data based on observation data is filtered to generate second measurement data; a first deflection of the structure is calculated based on an approximation of the structure's deflection, observation information, and environmental information; the first deflection is filtered to calculate a second deflection; a third deflection is calculated based on a first-order coefficient and a zero-order coefficient calculated from the second measurement data and the second deflection, and the second deflection; an offset is calculated based on the zero-order coefficient, the second deflection, and the third deflection; a first static response is calculated by adding the product of the first-order coefficient and the first deflection to the offset; and a first dynamic response is calculated by subtracting the first static response from the first measurement data.

The invention discloses an engineering structure topological optimization method and system for rapid solution under transient stress constraint, which takes the square of the average dynamic flexibility of the whole structure as a target function, and adopts a modal displacement method for quasi-static response compensation in order to solve the problem of huge calculated amount consumption of transient dynamic analysis. Stress control considering transient analysis is realized, and in order to control the calculation efficiency, transient stress after P-norm aggregation is adopted for constraint; and based on an adjoint method, deriving the sensitivity of a target function and the transient stress after P-norm aggregation, and solving an optimization problem by adopting an optimization algorithm based on a moving asymptote method. An optimization example shows that the method can effectively meet the stress constraint requirement while reducing the transient dynamics analysis calculation amount.

This invention provides a method, device, system, and storage medium for assessing the load-bearing capacity of bridges, relating to the field of bridge load-bearing capacity assessment technology. The method includes: acquiring structural response data of the target bridge from the moment a valid test vehicle crosses the bridge to the moment it exits; performing signal decomposition on the structural response data to obtain the quasi-static response of the target bridge based on the decomposition results; alternately inverting the influence line of the target bridge and the axle load of the valid test vehicle based on the quasi-static response to obtain the inverted influence line and the inverted axle load; calculating the fitted deflection value and fitted strain value of the target bridge based on the inverted influence line, the inverted axle load, and a preset loading scheme in the load test; calculating the deflection verification coefficient and the strain verification coefficient based on the fitted deflection value and the fitted strain value; and obtaining the load-bearing capacity assessment result of the target bridge based on the deflection verification coefficient and the strain verification coefficient. This invention enables automated and rapid assessment of bridge load-bearing capacity.

This invention provides a measurement method, a measurement device, a measurement system, and a storage medium. The method enables the calculation of the static response of a moving body on a structure with relatively low computational complexity. The method includes: generating first measurement data based on observation data from observation points on the structure; filtering the first measurement data to generate second measurement data; calculating a first deflection of the structure; filtering the first deflection to calculate a second deflection; approximating the second measurement data with a linear function of the second deflection and calculating first-order and zero-order coefficients; calculating a third deflection based on the first-order and zero-order coefficients and the second deflection; calculating an offset based on the zero-order coefficient, the second deflection, and the third deflection; and adding the product of the first-order coefficient and the first deflection to the offset to calculate the static response.

The invention belongs to the technical field of aerospace, underwater explosion and topological optimization, and particularly relates to an anti-explosion impact structure optimization method considering material damage, which comprises the following steps of: firstly, acquiring a dynamic response field of a structure through accurate nonlinear dynamic response analysis, judging a failure block and failure time of the structure according to the dynamic response field, and finishing displacement field repair; decoupling the response of the nonlinear dynamics in each time step into a series of linear statics responses; structural sensitivity calculation is carried out in a linear statics framework, and optimization design is realized through flexibility minimization under a statics equivalent working condition; and through repeated iteration and execution of accurate nonlinear dynamic response analysis and the equivalent statics optimization process, the optimization design of the anti-explosion impact structure is finally completed. According to the invention, a user can be helped to quickly explore and obtain a novel structure with high rigidity, light weight and excellent impact resistance in a wide design space.

The embodiment of the invention provides a power electronic interface load equivalent model construction method considering harmonic characteristics. The method comprises the steps that a fault recorder is adopted to record voltage and current instantaneous values, and steady-state operation, static response and dynamic response data are separated; calculating an equivalent static load model based on the static response; identifying an equivalent dynamic load model based on the dynamic response; analyzing harmonic composition, obtaining the amplitude proportion and initial phase relation of each harmonic, and calculating a harmonic initial phase and fundamental wave initial phase function; and comprehensively establishing a power electronic interface load electromagnetic transient equivalent model. According to the technical scheme provided by the invention, the harmonic characteristics of the power load can be fully considered in the full-electromagnetic transient simulation of the power system, and the method has important significance for improving the accuracy of the full-electromagnetic transient simulation of the power system.

The invention discloses a bridge bearing capacity evaluation method based on a dynamic load test and an intelligent algorithm. The method comprises the following steps: S1, carrying out collection and data preprocessing on vibration characteristic information of an existing bridge; s2, to-be-corrected design parameters of the structural analysis model are screened out; s3, calculating a target variable corresponding to each input sample to obtain an output sample, further forming a training sample with the input sample, constructing an intelligent algorithm proxy model by using the dynamic characteristic data, and correcting the initial structure analysis model through the training sample; s4, on the basis of the corrected finite element model, calculating target variables corresponding to the input samples again to obtain output samples; s5, calculating corresponding behaviors of the corresponding static force by using the relationship between the static force and the dynamic response; s6, evaluating the bearing capacity of the bridge through static response by using the verification coefficient; and S7, on the basis of the corrected finite element model, assuming that the structure is damaged and the material performance is reduced, and evaluating the influence on the structure deformation.

This invention relates to a method, apparatus, system, and program for deriving the dynamic response of a structure. Previously, it was impossible to determine the dynamic response at a specified location. The dynamic response at a specified location is derived based on the standardized deflection caused by the vibration components of the dynamic response, the amplitude ratio (a first deflection representing the distribution of vibration amplitude at the observation point) to the standardized deflection representing the distribution of vibration amplitude at the specified location (a second deflection), the vibration components at the specified location derived from the vibration components and the amplitude ratio, and the static response at the specified location derived from time-series data and estimated values.

This application belongs to the field of digital twin technology for water conservancy engineering, and provides a method for rapid calculation of the static response of arch dams. The method includes: in an offline stage, sampling and simulating the displacement field snapshot matrix based on a finite element model to obtain the matrix; extracting the dominant modes through intrinsic orthogonal decomposition to construct a reduced-order subspace and calculating the modal coefficients; then, using the operating parameters as input and the modal coefficients as output, training a radial basis function neural network to establish a nonlinear mapping relationship; finally, in the online stage, inputting the target operating parameters into the trained network to predict the modal coefficients, and rapidly reconstructing the complete displacement field response through a linear combination with the POD modes. This application achieves rapid and accurate prediction of the static physical field of arch dams, significantly improving the calculation efficiency of the arch dam displacement field.

In various example embodiments, model calibration techniques are used to identify one or more external structural loads on a structure. Initially, material or geometry attributes of elements of a model are adjusted to minimize discrepancy between measured responses and modeled responses. Thereafter, the model is used to search for external structural loads that minimize discrepancy between the measured responses and the modeled responses. Discrepancy may be measured by an error function that looks to dynamic responses and / or static responses. A solution that minimizes discrepancy may be determined using a genetic algorithm that generates a set of proposed external structural loads, applies the set to the model to produce the modeled responses, computes an error function that measures the difference between the measured responses and the modeled responses, and evolves the solutions to minimize an error produced by the error function, with such operation proceeding until a stopping criteria is reached.