47 results about "Load vector" patented technology

A method and system for analyzing a vehicle winch design includes a preprocessor determining contact locations for winch components from a mesh model. The preprocessor determines load vectors at a winch assembly and counter-vectors at a fairlead based on a relative position of a winch wire and a hook retention location based on a winch load rating. A non-linear analysis system determines plastic strains, deflections, and clearances under the winch load rating based on the contact locations, load vector and counter vector, and communicates the plastic strains, deflections, and clearances to a post processing system. The post processing system compares the plastic strains to strain limit at a post processor, compares the deflection to a deflection limit, compares clearances to a clearance limit and generating a display based on comparing the plastic strains, compares the deflection to the deflection limit and compares clearances to the clearance limit.

This invention relates to the field of structural fatigue life prediction technology, and discloses a method and system for predicting the fatigue life of a hinged coupling, comprising: Step 1, acquiring torque and input shaft angular position data, mapping time to angular position and dividing it equally to obtain angular domain torque; Step 2, constructing a load vector based on the angular domain torque and mapping matrix, and converting it into bending stress and torsional stress; Step 3, determining the equivalent stress, principal stress surface direction angle, and rotation rate; Step 4, calculating and correcting the average equivalent stress per revolution; Step 5, calculating the load concentration factor based on the assembly misalignment angle and angular position, generating a dual-sector weight core, and combining it with the rotation rate to obtain a follow-up amplification factor; Step 6, integrating the corrected stress, weight core, and amplification factor to obtain the cumulative damage per revolution; Step 7, determining the life by accumulating multi-revolution damage, and estimating the remaining life revolutions and time if no failure occurs. This invention achieves accurate prediction of the fatigue life of hinged couplings under complex working conditions.

The embodiment of the invention discloses a container load drift method between cluster nodes and a computer program product. The method comprises the following steps: determining a drift node and a drifted node in a first node and a second node based on a drift trigger type of the first node in response to the fact that a node load of the first node in a cluster is not in a load threshold range; in the drift node, a target container is determined based on matching degree sorting of each container load and the load difference value; determining a target node in the second nodes based on the matching degree between the load demand vector of the target container and the residual load vector of the drifted node; and performing load drift on the target container between the first node and the target node. In the embodiment of the invention, the container drift is carried out with the minimum drift distance, the shortest drift time and the lowest energy consumption, the load balancing can be automatically carried out on the cluster nodes, the failure rate caused by the abnormal load is reduced, and the reliability and the utilization rate of the cluster are improved.

The application belongs to the field of computational mechanics, and discloses a scale order reduction near-field finite element calculation acceleration method and implementation method for structure fracture analysis.The acceleration method comprises the following steps: firstly, geometric modeling is performed on a target structure; secondly, the split finite element is recorded as a fine scale element and constitutes a fine scale grid; thirdly, based on a spatial neighborhood relationship, the fine scale element is collected into a coarse scale element and constitutes a coarse scale grid; fourthly, an equivalent shape function of the coarse scale element is obtained; fifthly, the overall stiffness matrix and the load vector of the coarse scale grid are calculated; sixthly, the overall node displacement of the coarse scale and fine scale grid is solved; seventhly, it is judged whether the current loading step or time step reaches the maximum loading step or time step; if yes, the displacement nephogram and equivalent damage nephogram of the target structure are output; if not, the key state of all fine scale near-field elements is updated; and finally, the implementation method is that the acceleration method is taken as a core calculation module to be implemented in different scenes.The application significantly improves the calculation efficiency of near-field dynamics in large-scale simulation analysis.

The invention relates to the field of edge processing, and discloses a campus dormitory intelligent door lock gateway system and method based on edge processing, and the method comprises the steps: obtaining a door lock processing queue length, a passage trigger count and a door body occupation duration, mapping the door lock processing queue length, the passage trigger count and the door body occupation duration into a door area operation load vector, and determining a state evolution sequence of a door area operation load; identifying a transition interval in which the gate area operation load is converted from a steady state to a congestion state, and forming a corresponding processing period; based on the time adjacency relation of the passing request and the door body occupation continuity, generating an aggregation passing unit representing the overall passing behavior; constructing a risk state mechanism coupled with a gate area operation load state, executing constrained risk state transition judgment on the aggregation passing unit, and determining a risk state level; the passing requests in the processing cycle are bound to the corresponding verification path instances in the door lock gateway according to the risk state hierarchy, and a verification set associated with the selected verification path is formed. The method has the advantage that the stability is improved.

The application discloses a kind of prediction methods of building three-dimensional vibration response, comprising the following steps: step one, the dynamic stiffness matrix of the column, beam, floor and shear wall four components in the frame-shear wall structure of building is obtained, according to spatial geometric coordinate relationship is assembled, obtains the dynamic stiffness matrix [D] of building G ;Step two, according to external force load vector [F] G And the dynamic stiffness matrix [D] G Of building, the displacement response vector [X] G Of building is obtained;Step three, according to the displacement response vector [X] G Of building obtained, according to building displacement response, the strategy of installing damping support in the bottom of building is used to carry out damping. According to the technical scheme provided by the application, the strategy of installing damping support in the bottom of building can be used to carry out damping according to building displacement response.

This invention provides a method for determining aerodynamic loads on a model based on sparse strain measurement of a support rod, belonging to the field of aerodynamic testing technology. It solves the problem in existing wind tunnel tests where it is difficult to obtain high-precision, real-time aerodynamic loads and actual attitude changes of the model when a master balance cannot be set up. The method first determines the load space of the model under test, selects multiple load sample points, and establishes a strain-load database, which records the calculated strain values ​​at multiple preset strain measurement points on the support rod corresponding to each load sample point. Then, it trains a mapper that calculates the strain sequence to the corresponding load vector, enabling it to inversely deduce the current aerodynamic load on the model under test and the model attitude angle caused by support rod deformation based on the sparse strain sequence obtained from wind tunnel tests. This invention utilizes support rod deformation to measure the aerodynamic forces of the model, reducing trial-and-error costs, shortening the test cycle, and providing a new approach to obtaining model aerodynamic forces for masterless balance-type tests.

The present disclosure relates to a load balancing method for a distributed system, an electronic device, and a non-transitory computer-readable storage medium. The method includes: determining a multi-dimensional load vector of each of service nodes based on dimensional resource usage indicators of each of service replicas carried on the each of the service nodes in the distributed system in multiple dimensions; classifying the service nodes into multiple load intervals based on the multi-dimensional load vector and a target load vector of each of the service nodes; determining multiple candidate scheduling strategies and corresponding load balancing gains based on the multiple load intervals; and selecting, from the multiple candidate scheduling strategies, a candidate scheduling strategy with a largest load balancing gain as a target scheduling strategy, and executing the target scheduling strategy.

The invention relates to the technical field of task scheduling, in particular to a store patrol task dynamic allocation method based on load balancing. Comprising the steps of generating a task vector through a shop patrol task processing request; generating a node load vector through the mobile terminal state data; constructing a directed attribute graph, calculating transfer parameters, generating a space transfer matrix, and constructing a feature tensor; inputting the feature tensor into an evaluation network for processing, and outputting a score matrix; outputting candidate sites through a search algorithm; calculating a load variance variable quantity and an out-of-limit probability according to the candidate sites; inputting the load variance variable quantity and the out-of-limit probability into a multi-objective optimization function for calculation, and outputting a distribution strategy; and analyzing the distribution strategy, and generating a scheduling instruction containing a node routing sequence. According to the method, chain structured fusion is carried out through probability deduction of high-dimensional data, search pruning of physical boundaries and multi-target game of global dimensions, and long-term stability and dynamic balance of cluster load distribution are facilitated.

The invention discloses a multi-stage self-supporting constraint topological optimization method and system combining projection and a virtual pyramid. The method comprises the following steps: initializing a design domain and generating a non-uniform gradient initial density field; applying a total load vector formed by superposing a bearing working condition and a guide load, and delimiting a key protection area; calculating the projection support quantity of each grid unit and applying punishment; constructing a multi-layer virtual pyramid support domain which extends downwards in a conical manner, calculating a virtual pyramid support quantity and applying cross-layer penalty; superposing the two penalty terms to the original sensitivity to obtain corrected sensitivity; and iteratively updating the design variables and carrying out protective correction on the key region until convergence and outputting an optimized structure. Through a multi-stage self-supporting constraint mechanism, the overhanging defect in a traditional topological optimization structure is effectively eliminated, addition of a large number of external supports in additive manufacturing is avoided, material consumption and post-treatment difficulty are remarkably reduced, and collaborative improvement of mechanical properties and manufacturability is achieved.

A data processing method including receiving obtaining multidimensional data including a plurality of parameters of a wafer, generating a principal component and a loading vector based on the multidimensional data, wherein the principal component represents dimensionally reduced characteristics of the of the multidimensional data and the loading vector represents a weight of the principal component to the multidimensional data, generating a guide line based on a first group of parameters among the plurality of parameters and a second group of parameters among the plurality of parameters, and generating an analysis result of a parameter among the plurality of parameters of the wafer based on the guide line and the loading vector.

This invention relates to the field of intelligent asset supervision technology, specifically to an asset management method and system based on big data, comprising the following steps: collecting time-series data of operational status and environmental stress parameters using a sensor array; constructing a multidimensional feature correlation matrix based on covariance analysis and calculating a dynamic loss index; spatially mapping this index with the task load vector to be assigned to generate an asset-task matching score; and finally comparing the score with a dynamic judgment benchmark value to output an adaptive allocation instruction. In this invention, by capturing the multidimensional characteristic fluctuations of physical entities in real time, a nonlinear loss assessment system reflecting the actual load pressure is established, solving the problem of delayed asset status perception caused by the reliance on static ledgers in traditional methods. The dynamic adaptation algorithm accurately calculates the fit between asset capabilities and task requirements, maximizing resource allocation efficiency while ensuring equipment operational safety, effectively extending the service life of high-value assets, and reducing operation and maintenance costs.

This application discloses a high-speed data acquisition and processing method and system for PLC based on FPGA. First, it constructs a detailed real-time heat map and load vector by real-time sensing of multi-point temperature, data input rate, and task queue status on the FPGA chip. Based on this real-time information, it accurately predicts future power consumption and potential hotspot areas to optimize the modeling of internal thermal coupling effects and overcome the shortcomings of traditional models that underestimate peak power consumption. Finally, based on the prediction results, it intelligently generates task execution plans and refined clock gating masks, achieving proactive and adaptive management of FPGA resources. This approach significantly improves the operational stability and reliability of FPGA in high-speed data acquisition and processing scenarios, thus laying a solid foundation for precise industrial control and intelligent decision-making.

This invention discloses a multimodal perception-enhanced simulation method and system for heavy-duty transport vehicle operations, relating to the field of traffic simulation technology. The method includes: constructing a multimodal digital twin scene and extracting a three-dimensional scene state matrix; based on the three-dimensional scene state matrix and a multi-body flexible coupled dynamic model of the heavy-duty transport vehicle, outputting real-time pose, cargo flexible deformation field, and tire load vector; obtaining enhanced unified bird's-eye view perception features based on the three-dimensional scene state matrix and real-time pose; using an improved von Neumann optimization algorithm to iteratively solve for the enhanced unified bird's-eye view perception features, cargo flexible deformation field, and tire load vector, outputting the optimal operation simulation control decision; and continuously monitoring real-time data to perform operation simulation and safety situation assessment. This invention solves the problems of perception distortion in heavy-duty transport simulation, inaccurate calculation of rigid-flexible coupling, and the tendency for control decisions to fall into deadlock under complex constraints in existing technologies.

The application belongs to the technical field of strain field inversion of structural health monitoring, and provides a displacement reconstruction method introducing tensor component hybrid theory and a measuring point layout optimization method, comprising: first, establishing a four-node inverse shell element mapping function, deducing an element strain-displacement conversion relationship, then introducing a tensor component hybrid theory to construct a transverse shear strain function meeting a coordinated deformation, then based on a weighted least square criterion, using measured strain data to preliminarily reconstruct a displacement field, then expanding sparse measuring point strain data through a radial basis function to generate virtual strain data, optimizing a pseudo stiffness matrix and a pseudo load vector, and improving the displacement reconstruction accuracy, finally taking the displacement reconstruction error and the number of strain measuring points as fitness functions, using a non-dominated sorting algorithm to optimize the measuring point layout, and obtaining an optimal scheme considering the accuracy and the layout efficiency. The application can improve the displacement reconstruction accuracy under sparse measuring points, and considers the reconstruction accuracy and the layout efficiency.

This invention provides a method, equipment, and medium for predictive calculation of hanging basket structures based on multi-source data. It establishes a standardized parameter library by collecting hanging basket design parameters, actual processing data, and real-time on-site monitoring data. A complete structural mechanics model of the hanging basket is built, the overall structural stiffness matrix is ​​calculated, initial design loads are applied, and static equilibrium equations are solved. The structural stiffness matrix is ​​corrected using actual processing data, and the actual load vector is corrected using unloaded static data. Based on the corrected stiffness matrix and load vector, the structural mechanics equations are resolved, and deviations are calculated using construction dynamic data as constraints. If the deviation exceeds a threshold, the structural parameters are iteratively corrected, and the solution is re-solved and compared. This invention achieves high-precision simulation and real-time tracking of the hanging basket's stress state by integrating multi-source data from design, processing, and on-site data and introducing a dynamic correction mechanism, ultimately achieving precise control over structural safety and construction alignment.

The invention relates to the technical field of mechanical engineering, and discloses a tooth surface contact stress calculation method for a multistage parallel shaft gear transmission system. Compared with the prior art that the gear surface contact stress is calculated only according to the gear structure, the influence of the system structure flexibility on the gear meshing characteristic is neglected, and consequently the calculation of the gear surface contact stress is inaccurate, the technical scheme is combined with the structural characteristics of the system, and the multi-stage parallel shaft gear transmission system is dispersed into a plurality of basic units; a stiffness matrix of a system is established by calculating a stiffness matrix of each basic unit, then a statics equilibrium equation set of the system is established according to working condition information and a load vector, the meshing misalignment amount of a gear pair is obtained by solving the statics equilibrium equation set of the system, and the tooth surface contact stress is calculated according to the meshing misalignment amount. According to the technical scheme, the influence of a flexible structure on the system is comprehensively considered, and more accurate calculation of the tooth surface contact stress of the multistage parallel shaft gear transmission system, which is more suitable for practical application, is realized.

The application discloses a kind of based on multi-scale decomposition and Hampel filter power user adjustable load feature extraction method, system, storage medium and computing device.The method is first based on Fourier transform to the frequency spectrum analysis of load data, identify the main frequency component therein to extract periodic component, and based on variational mode decomposition to the trend component obtained after the residual signal decomposition of stripping periodic component;Robust denoising is carried out to periodic component based on dynamic window Hampel filter;Combining the production scale factor provided by trend component and the adjustable load vector obtained after periodic component denoising, the adjustable load multidimensional feature vector reflecting user demand response potential is constructed.The different scale components obtained by the decomposition of load data in time domain and frequency domain are processed and information is fused in cooperation, to provide high reliability feature input for demand response potential evaluation.

The invention discloses a load balancing optimization method and system for cloud computing resources, and the method comprises the steps: collecting monitoring nodes for a cloud computing cluster, collecting multi-dimensional node resource use indexes for the monitoring nodes according to a preset period, and calculating a load vector of each monitoring node through the multi-dimensional node resource use indexes; performing long-time update span and fixed time window calculation on multi-dimensional node resource use indexes periodically acquired by the monitoring nodes to obtain a historical load vector sequence and a real-time load vector sequence; constructing an elastic capability interval for the historical load vector sequence and the real-time load vector sequence; a batch of to-be-detected tasks are preset and coded, and a scheduling scheme is formed; and for each scheduling scheme, dividing the level intervals of the monitoring nodes according to the elastic capability intervals, and allocating the monitoring nodes according to different level intervals to obtain an optimal scheduling scheme. According to the scheme, service degradation or fault risks caused by node overload can be remarkably reduced, and elastic and efficient cloud computing resource scheduling is achieved.

This application relates to a method and system for solving conjugate gradient finite element models based on sparse convolution preprocessing. The method includes establishing a structural finite element model, generating a structural stiffness matrix A and a load vector b, and constructing a linear equation system Ax=b, where A is a sparse symmetric positive definite matrix. A preprocessing sub-generator is constructed by training different structures using a sparse convolutional neural network. The stiffness matrix A is input into the preprocessing sub-generator to obtain a preprocessing factor. A symmetric positive definite preprocessor is constructed based on the preprocessing factor. The linear equation system Ax=b is solved using the preprocessed conjugate gradient method to obtain the displacement response vector x. This application optimizes the condition number of the preprocessed matrix to improve convergence speed and reduce solution time. It adapts the sparse convolutional U-net structure to large-scale sparse matrices, improving training efficiency and forming a unified and scalable preprocessing framework for structural engineering, providing a general and efficient preprocessing strategy for large-scale finite element model analysis.

The invention discloses a generalized Hamilton symplectic neural network dynamic response analysis method for an engineering structure. A sinchinger propagation operator is embedded in forward propagation of a neural network, so that the geometric structure and energy consistency of the system is kept; on this basis, a conservative dissipative double-branch network structure is constructed, a conservative branch keeps a track by using a symplectic propagation generation structure, and a dissipative branch independently depicts damping and external load effects, so that unified modeling of conservative and non-conservative systems is realized. An equation residual error and an energy regular term are constructed through an automatic differential technology, and unsupervised training can be realized without real trajectory data. According to the method, a coupling interface of a finite element generalized Hamilton neural network is established, mass, damping, stiffness matrixes and load vectors obtained through finite element analysis are mapped into a generalized Hamilton form, and high-precision dynamic response prediction of complex engineering structures such as stiffened wallboards is achieved.

The application relates to the field of structural lightweight design, in particular to a design method of an extremely light high-strength damage-resistant lattice structure, which comprises lattice structure classification and division, simulation analysis and lattice structure thickness optimization, is divided according to whether the directional vectors of each rod of the lattice structure are parallel, whether the included angles between the directional vectors and the load vectors are equal or complementary, and based on the rod thicknesses of different base rods and reinforcing rods, corresponding series design schemes are formulated for the obtained rod types, grid CAE analysis is carried out on the design schemes to obtain stress-strain curves, the yield strengths under the design schemes of different rod types are obtained, the promotion limit factor of the relative yield strength is calculated, the optimal lattice structure thickness optimization scheme is obtained by using the promotion limit factor of the relative yield strength, and finally the thickness and length distribution of the lattice structure are obtained.

This invention discloses a real-time probabilistic inversion method for TBM (Tunnel Boring Machine) extrusion load based on a surrogate model. First, the extrusion load vector and its prior value range are defined for the TBM shield tunneling environment. A surrogate model is constructed and iteratively updated based on a small number of high-fidelity numerical simulation samples to establish a rapid mapping relationship between the extrusion load and the shield structure response. Then, on-site measured shield monitoring data are acquired, and a likelihood function is constructed by combining sensor observation errors and surrogate model prediction errors. Finally, within a Bayesian probabilistic inversion framework, a Markov chain-Monte Carlo algorithm is used to call the surrogate model for sampling, obtaining the posterior probability density distribution, optimal estimate, and confidence interval of the extrusion load, and calculating the shield structure failure probability accordingly. This invention can meet the real-time requirements of inversion calculations and provide a quantitative assessment of the uncertainty of the inversion results, offering a scientific basis for safety decisions when TBMs traverse strata with large extrusion deformation.

The invention provides a Pushover lateral load dynamic updating method considering multi-stage damage, which comprises the following steps: setting damage parameters for quantifying the damage state of a structural member, dividing multi-stage damage grades, and determining a damage parameter critical value corresponding to each damage grade; calculating an initial lateral load vector of the structure, and determining target displacement of Pushover analysis; the method comprises the following steps: a, executing Pushover analysis by adopting a current lateral load vector, and monitoring damage parameters of a component and pushing and covering displacement of a structure in real time; b, when a damage parameter reaches a critical value of any damage level and pushing displacement does not reach target displacement, automatically triggering lateral load updating, and dynamically calculating updated lateral load distribution based on a secant stiffness matrix and a node displacement vector of the structure in a current damage state; and taking the updated lateral load distribution as a new current lateral load vector, repeating the steps a and b, continuing to execute Pushover analysis until the pushing displacement reaches the target displacement or the structure is damaged, and outputting a Pushover curve of the structure.

This invention relates to wind turbine de-icing, specifically to a control method and robot for a rotating blade de-icing robot. The control method includes: acquiring the centrifugal force vector, gravity vector, and airflow load vector acting on the robot, and then superimposing them to synthesize a comprehensive load vector; calculating the slippage trend and overturning moment center of the robot body relative to the working surface based on the spatial orientation of the comprehensive load vector; and performing dynamic adhesion compensation based on the slippage trend and overturning moment center: if a slippage trend is determined, the adsorption force of the adhesion units located in the region opposite to the slippage trend is directionally increased to generate a constraint torque that dynamically balances with the external dynamic load, thereby balancing the robot's adhesion on the working surface. This solution overcomes the limitation of traditional de-icing robots, which can only sense static gravity, by superimposing centrifugal force, gravity, and airflow load vectors, and dynamically adjusts the robot body's adhesion state by enhancing the adsorption force to generate a balancing torque.

The present application relates to the technical field of structural engineering and fan foundation design, and specifically relates to a load distribution calculation method for a foundation pile column node, which comprises defining an input load vector of a main control point and a corresponding spatial six-degree-of-freedom generalized displacement; decoupling the foundation pile column node into two parallel subsystems in terms of physics and stiffness, deriving a single-pile spatial stiffness matrix based on the m method of the Winkler foundation model; constructing a first equivalent stiffness matrix and a second equivalent stiffness matrix; superimposing the matrices of the first equivalent stiffness matrix and the second equivalent stiffness matrix to obtain a global spatial stiffness matrix of the foundation composite system; and calculating a dynamic load distribution ratio of the parallel subsystems. The present application is used to accurately describe the nonlinear interaction between the pile foundation and the foundation, to provide more accurate pile foundation stiffness calculation and load distribution results, and to improve the accuracy and reliability of the load distribution calculation.

The invention belongs to the technical field of structural finite element data processing, and particularly relates to an iterative solution method and device for a finite element equation set of a whole machine structure. The method comprises the steps of obtaining a complete machine structure sparse positive definite stiffness matrix and a load vector applied to a complete machine structure, and constructing a complete machine structure finite element equation set used for representing the relation among the complete machine structure sparse positive definite stiffness matrix, the load vector and a displacement vector; performing degree-of-freedom elimination on the sparse positive definite stiffness matrix of the whole machine structure to obtain an independent degree-of-freedom matrix; performing bandwidth optimization sorting on the independent degree-of-freedom matrix to obtain a sorted stiffness matrix; processing the sorted stiffness matrix based on an algebraic multi-grid preprocessor to obtain a preprocessed sub-matrix; and calculating a displacement vector by adopting a conjugate gradient iteration method according to the pre-processing sub-matrix. According to the method, the problem that the sparse matrix of the aviation structure is not converged in iterative solution can be effectively solved, and the solution efficiency is remarkably improved while the calculation precision is ensured.

The invention relates to the technical field of computers. The edge-side real-time voice method, device, equipment and medium for the high-concurrency class are provided, and the method comprises the following steps: carrying out resource index acquisition and broadcast processing on edge nodes based on a dynamic cooperative network, and generating a real-time load vector set; target edge node overload detection and cooperative node selection processing are carried out based on the real-time load vector set, and a cooperative migration decision is generated; performing classroom migration processing through voice context synchronization and a two-channel transmission mechanism to generate a cooperative node activation state; and performing clock synchronization and time sequence identification processing on the migrated cooperative nodes based on the active states of the cooperative nodes, and generating a time sequence alignment sound mixing stream, so as to achieve the technical effects of improving the dynamic adaptability of edge node load balancing, reducing the voice migration interruption rate and the state loss risk, and optimizing the cross-node flow mixing time sequence synchronization precision.

The invention discloses a distributed database enabling pressure test method and system, and belongs to the field of aviation retail, and the method comprises the steps: collecting heterogeneous audit logs from a production business system, and storing the heterogeneous audit logs in a data storage library: carrying out the multi-dimensional analysis of the audit logs, and extracting business semantic features; restoring a business scene based on the business semantic features, and converting the business scene into a load vector; applying the load vector to the tested distributed database system through the voltage test node cluster; and collecting performance data of the tested distributed database system under the pressure test, performing intelligent analysis based on the performance data, and generating a test result. According to the method, full-link, closed-loop and intelligent pressure testing of the distributed database cluster in a complex service environment is realized through multi-dimensional log analysis, service scene restoration, abnormal path injection and adaptive load scheduling technologies.

Disclosed herein are vector index registers for storing or loading indexes of true and / or false results of comparison operations in vector processors. Each of the vector index registers store multiple addresses for accessing multiple positions in operand vectors.