260 results about "Boundary constraints" patented technology

A lossless audio codec encodes / decodes a lossless variable bit rate (VBR) bitstream with random access point (RAP) capability to initiate lossless decoding at a specified segment within a frame and / or multiple prediction parameter set (MPPS) capability partitioned to mitigate transient effects. This is accomplished with an adaptive segmentation technique that fixes segment start points based on constraints imposed by the existence of a desired RAP and / or detected transient in the frame and selects a optimum segment duration in each frame to reduce encoded frame payload subject to an encoded segment payload constraint. In general, the boundary constraints specify that a desired RAP or detected transient must lie within a certain number of analysis blocks of a segment start point. In an exemplary embodiment in which segments within a frame are of the same duration and a power of two of the analysis block duration, the RAP and / or transient constraints set a maximum segment duration to ensure the desired conditions. RAP and MPPS are particularly applicable to improve overall performance for longer frame durations.

A computer implemented method determines a settlement price for a constituent contract of a plurality of spread instruments. The method includes obtaining market data indicative of bid-offer values for the plurality of spread instruments, generating synthetic market data for the constituent contract based on the bid-offer values and based on a respective settlement price for an active contract of each spread instrument of the plurality of spread instruments, determining boundary constraints on the settlement price for the constituent contract based on the synthetic market data, and computing the settlement price for the constituent contract based on the boundary constraints.

The invention provides a vehicle autonomous parking path programming method used for multiple parking scenes. The method is used for automatically parking a vehicle in a parking space through an autonomous parking system when the autonomous parking system detects the available parking space. The method includes the steps that target parking space information is detected, and a parking scene is determined; the initial state and target state of the to-be-parked vehicle are determined; a vehicle kinematics differential equation is established; state variables and control variables of the vehicle are segmented, equidistance sampling is performed on each segment according to certain time step, and to-be-optimized variables are obtained; an equality constraint, boundary constraints and inequality constraints of the to-be-optimized variables are formed; motion range constraints of the to-be-parked vehicle are formed according to the motion range limit in the parking process of the vehicle; an optimization objective is determined, and an objective function is established; and by means of a nonlinear programming solver, an optimal solution of a parking path is obtained. The vehicle autonomous parking path programming method is suitable for the multiple parking scenes, the design is reasonable, abundant information can be provided so as to control autonomous parking of the vehicle, and the security coefficient is high.

Secure communication between a resource-constrained device and remote network nodes over a network with the resource-constrained acting as a network node. The remote network nodes communicate with the resource-constrained device using un-modified network clients and servers. Executing on the resource-constrained device, a communications module implements one or more link layer communication protocols, operable to communicate with a host computer, operable to communicate with remote network nodes and operable to implement network security protocols thereby setting a security boundary inside the resource-constrained device.

The invention provides a remote sensing image building extraction method and system based on depth learning which comprises the steps of sample preparation, model training, precision evaluation, building prediction, merging and vectorization. The invention also relates to a remote sensing image building extraction system based on depth learning, a storage medium and an electronic device. Based onthe improved RCF boundary constraint model, the invention extracts the urban single building contour, the rural isolated building contour and the peripheral boundary of the rural building dense group,at the same time, a U-Net semantic segmentation model network structure is improved, and the improved U-Net is utilized to classify the images at pixel level. Finally, the two models are fused, and the depth learning model is trained by a large number of building sample label data, so that the network model by fusing the improved U-Net and the RCF is used to extract the buildings on the sub-meterGao Fen 2 remote sensing images, so that the automatic and effective building vector data extraction is realized, and the time cost and labor cost of manual rendering is greatly reduced.

The invention discloses an optimization design method for the sagging problem of a car door based on CAE structural analysis, which comprises the steps of: obtaining a design input condition from total arrangement and configuration of a car body; creating a CAD (Computer Aided Design) model by modeling software; dividing grids of the CAD model; simulating actual conditions to create a connection relationship; simulating a boundary constraint condition during an actual test of a car door assembly; carrying out solution analysis on a finite element model generated finally; comparing a result obtained by finite element simulation operation with an industry standard; if an obtained conclusion is lower than the industry standard, providing a structural optimization design; and if the obtained conclusion is higher than the industry standard, completing final design output. The method not only enhances the inspection accuracy, but also greatly reduces the period of a whole repair part so as to shorten the time of developing the whole car. Structural errors can be corrected in time by CAE analysis in early design, thereby reducing the cost of developing the whole car.

The invention discloses a reentry vehicle trajectory optimization method based on a variable-centroid rolling control mode. The reentry vehicle trajectory optimization method based on the variable-centroid rolling control mode is used for solving the technical problem that the robustness of an existing reentry vehicle trajectory control method is poor. According to the technical scheme, by establishing a one-dimensional variable-centroid rolling control reentry vehicle mathematical model, a one-dimensional variable-centroid rolling control reentry vehicle trajectory optimization model is established, and the one-dimensional variable-centroid rolling control reentry vehicle trajectory optimization model is solved. According to the method, all kinds of constraints in the reentry process of a reentry vehicle are taken into consideration, by introducing control constraints and one-dimensional variable-centroid control ability constraints, the one-dimensional variable-centroid rolling control reentry vehicle trajectory optimization model with a guidance system matched with a control system is established, meanwhile, the trajectory optimization model is solved through a simulated annealing algorithm, and thus the local convergence defect of a classic optimization method is overcome, a nominal trajectory suitable for the one-dimensional variable-centroid rolling control mode is acquired while process constraint and boundary constraint conditions are met, and the robustness of the guidance and control systems is improved.

Analysis evaluates formation fluid with a downhole tool disposed in a borehole. A plurality of possible constituents is defined for the formation fluid, and constraints are defined for the possible constituents. The constraints can include boundary constraints and constraints on the system's dynamics. The formation fluid is obtained from the borehole with the downhole tool over a plurality of time intervals, and density of the obtained formation fluid is obtained at the time intervals. To evaluate the fluid composition, a state probability distribution of the possible constituents of the obtained formation fluid at the current time interval is computed recursively from that at the previous time interval and by assimilating the current measured density of the obtained formation fluid in addition to the defined boundary / dynamic constraints. The probabilistic characterization of the state of the possible constituents allows, in turn, the probabilistic inference of formation properties such as contamination level and GOR.

The invention provides a binocular vision three-dimensional morphology measurement method based on time and space constraints, which belongs to the technical field of computer vision measurement. The binocular vision three-dimensional morphology measurement method based on time and space constraints is for the surface morphology of a large composite structure component, and uses a laser scanning binocular vision measurement system to carry out image acquisition and image processing. Edge information is extracted. The constraints are established. Time dimension information is combined to predict the position of a light strip. An appropriate interested extraction area is established. Laser light strip centers corresponding to left and right light stripe images are fast and accurately extracted. The light stripe center information in a boundary constraint is retained. The light stripe center information beyond the constraint is removed. The retained light strip center information and boundary information are matched and reconstructed. Ultimately, complete three-dimensional morphology information is restored. The method provided by the invention has the advantages of improved measurement efficiency, high measurement accuracy, complete detection information and fast operation speed, and can realize the three-dimensional morphology measurement of the surface of a large part.

An augmented Lagrangian genetic algorithm that may be used to generate solutions for optimization problems subject to linear, bound, and non-linear constraints is discussed. The augmented Lagrangian genetic algorithm uses an adaptive mutation operator to separately handle the linear, and bound constraints, and uses an augmented Lagrangian framework to handle non-linear constraints. The non-linear constraints are handled by creating a sub-problem without the linear and bound constraints and solving the sub-problem using Lagrange parameter estimates and a penalty factor. The exclusion of the linear constraints and boundary constraints from the sub-problem allows the sub-problem to be resolved in a more effective manner than is possible using conventional techniques.

The invention provides a multiple-unmanned aerial vehicle collaborative area searching method under the communication constrains. The method comprises the following steps of: firstly setting an initial position of multiple unmanned aerial vehicles, parameters of the communication constrain condition and search finishing time, selecting a point with the minimum cost as a next way-point position of all unmanned aerial vehicles, and judging whether the way point meets the boundary constraint condition; when one unmanned aerial vehicle flies to the way point meeting the boundary constraint condition, judging whether other unmanned aerial vehicles are in the communication distance range of the unmanned aerial vehicle, and exchanging probability graph data with the unmanned aerial vehicle with closest distance; and finally, calculating the area coverage rate and judging whether the search finishing time is reached. The multiple-unmanned aerial vehicle collaborative area searching method has the advantages that the influence of the communication constrain on the multiple-unmanned aerial vehicle cooperative system can be eliminated or weakened, the multiple unmanned aerial vehicles can finish the search task at minimum cost and the coverage rate of the search area is increased.

The invention discloses a method for reconstructing a scattered point cloud with boundary constraint. The method comprises the steps of: firstly mapping a three-dimensional scattered point cloud to a two-dimensional plane, obtaining a minimum bounding box for the obtained two-dimensional point collection and then dividing the bounding box into multiple rectangular grids, judging whether the grid is a boundary grid based on existence of a two-dimensional point in an adjacent grid of each grid, extracting a two-dimensional boundary point from each boundary grid and then obtaining boundary points of the three-dimensional scattered point cloud through the mapping relationship; removing the boundary points in the three-dimensional scattered point cloud and then simplifying rest point cloud by utilizing a fuzzy entropy iteration based point cloud simplified algorithm, and combining the simplified rest point cloud with the boundary points of the point cloud and then composing a simple point cloud; performing triangulation on the two-dimensional point collection corresponding to the simple point cloud by utilizing a Delaunay criterion based optimized algorithm and then mapping the triangulation result to a three-dimensional space to finally realize curved surface reconstruction of the three-dimensional scattered point cloud.

The invention provides a high-resolution SAR image classification method based on sparse features and conditional random fields. The method mainly solves the problems of low classification precision and non-accurate boundary retention in complicated scenes in the prior art. The method comprises the steps of: firstly, inputting high-resolution SAR images, selecting images to build a training data block set, and training system parameters of a sparse feature extraction algorithm; secondly, extracting SAR image block sparse features and training a logistics classifier to obtain the classificationposterior probability of the images and build a univariate potential energy function; thirdly, building a bivariate potential energy function by using a boundary constraint map obtained after fusionof a binary edge partition map and an edge strength map; forming a complete full connection conditional random field model by using the univariate potential energy function and the bivariate potentialenergy function and performing reasoning on the model to obtain a classification result. The method increases the classification precision of complicated scenes and edge details of high-resolution SAR images and can be used for SAR image terrain classification.

The invention discloses a space curved surface reconstruction method based on a boundary constraint. The space curved surface reconstruction method based on the boundary constraint mainly comprises the steps of (1) collecting original horizon data points and fault data points, and drawing a hanging wall polygon and a heading wall polygon; (2) obtaining height attributes, relation attributes and projection attributes of the original horizon data points and points on the fault polygons; (3) carrying out connection on the original horizon data points and the points of the fault polygons through triangle gridding with the constraint; (4) accomplishing splicing of internal areas and external areas of the hanging wall polygon and the heading wall polygon, namely, accomplishing reconstruction of a three-dimensional space curved surface. The space curved surface reconstruction method based on the boundary constraint solves the problem of reconstruction of the horizon curved surface of the complex terrain in the process of three-dimensional geologic modeling, provides a new idea for isoline drawing, geological block forming and the like, can be applicable to various discrete points or lateral line data, and low in requirement for data, can support various faults such as complex terrain structures such as normal faults, reverse faults and vertical faults, and has good adaptability.

The invention discloses a fluid-solid interaction simulation method based on video reconstruction and an SPH model. The fluid-solid interaction simulation method includes steps: 1), adopting a bright-dark recovery shape method to quickly reconstruct fluid surface geometric information in video, and acquiring a surface height field of each frame of input image; 2), combining the height fields with a shallow water equation, and calculating to acquire a speed field on the surface of fluid in a form of a minimizing energy equation; 3), using the surface geometric information as a boundary constraint condition to be discretized into a whole three-dimension body to acquire volume data; 4), guiding the volume data reconstructed in the video into an SPH simulation scene to serve as an initial condition of the simulation scene, and interacting with other virtual environment objects in the scene. By the fluid-solid interaction simulation method, high-accuracy data reconstruction can be realized, fluid surface details can be retained, bidirectional interaction simulation is performed on the basis of reconstructed data and a physical simulation model, fluid animation effect closer to real condition is acquired, algorithm complexity is low, and the method has high creativity compared with related algorithms.

Four-dimensional (4D) computed tomography (CT) is simulated by first generating a surface mesh from a single thoracic CT scan. Tetrahedralization is applied to the surface mesh to obtain a first volume mesh. Finite element analysis, using boundary constraints and load definitions, is applied to the first volume mesh to obtain a lung deformation according to an Ogden model. Constrained tetrahedralization, using control points, is applied to the lung deformation to obtain a second volume mesh, which is then deformed using mass-spring-damper simulation to produces the 4DCT.

The invention provides a turning machining parameter optimization method considering uncertain parameters. The method comprises the steps of obtaining a stability limit-state function according to preset initial vibration conditions and stability critical-state information of a turning machining system; adopting an AFOSM to obtain reliability indexes for evaluating the stability of the system; with MRR as preset constraint conditions of an optimization target, ,establishing an optimization model of the reliability of turning process parameters in the system, wherein the constraint conditions comprise reliability constraint conditions and stochastic design variable boundary constraint conditions; optimizing and processing the optimization model, and obtaining a target function value which is optimized and converged and meets the reliability constraint conditions, wherein certainty parameters, stochastic design variables and stochastic parameters which correspond to the target function value serve as output turning machining parameters. According to the method, the reliability can serve as an evaluation index and optimization condition, and the influences of uncertain factors on the turning process are analyzed in order to obtain the best turning machining parameters.

The invention belongs to the technical field of photoelectronics and material science application, and particularly relates to a method for extracting a material optical constant by using a terahertz spectral signal. The method comprises the following steps: 1, enabling a terahertz wave to vertically enter a slab sample with a thickness of 1, which is placed in air, to obtain a theoretical ratio A (Omega) of terahertz frequency spectrums of a sample signal and a reference signal according to a Fabry-Perot cavity mould; and 2, obtaining a global minimum between the theoretical ratio A (Omega) of terahertz frequency spectrums of the sample signal and the reference signal and an experiment ratio Ameas (Omega) by using a simulated annealing optimization algorithm, and obtaining an actual refractive index n (Omega) and an extinction coefficient k(Omega) which correspond to the minimum. According to the method, the material optical constant is extracted by combining the simulated annealing optimization algorithm by adopting an accurate formula, weak absorption approximation and material boundary constraints can be eliminated; and the method is suitable for materials with different thicknesses. The accuracy of the material optical constant extracted by adopting the method is high.

The invention discloses a method for establishing a stainless steel bar concrete mesoscopic numerical model. The method comprises the following steps: uncertain stainless steel bar concrete mesoscopicstructure composition, model establishment of each mesoscopic structure, constitutive relation of each mesoscopic component and determination of mesoscopic material parameters. Under the condition ofdetermining the mesoscopic material parameters of the coarse aggregate, the mortar, the mortar-coarse aggregate interface and the steel bar-mortar bonding interface, mesoscopic finite element analysis is carried out on the bonding performance of the stainless steel bar concrete. According to the method, based on a mesomechanics theory, detailed expression is carried out from the aspects of mesoscopic structure composition, constitutive relations of all mesoscopic components, determination of mesoscopic parameters, setting of boundary constraints and the like. A simplified method of a stainless steel bar solid structure in two-dimensional solid modeling is proposed, a parameter assignment method of a stainless steel bar-mortar matrix bonding layer microstructure material is studied, the influence of interface performance on bonding strength is analyzed, and the recommended value range of the tensile strength of a bonding layer is determined in combination with a calculation result.

The invention relates to a finite element-based intelligent analysis method for the strength of a pipeline with defects and belongs to the technical field of pipeline strength analysis. The finite element-based intelligent analysis method for the strength of the pipeline with defects comprises the following steps of: 1) building a practical model according to the geometrical shape of the defects; 2) dividing a finite element mesh, namely selecting a three-dimensional 10-noide tetrahedron element to carry out free mesh division; 3) loading boundary conditions for the designed model, namely loading boundary constraint and pressure load; 4) calculating for solving a stressed pipeline model, namely calculating for solving the stressed pipeline model according to different corrosion defect shape groups; 5) extracting the calculation result, namely extracting the strain value of the stress on the external wall of the pipeline around the defect; 6) building a stress mathematical model of the external wall of the pipeline; 7) building a software estimation system, namely programming the pipeline critical strain value in the software according to the standard so as to estimate the pipeline. The method provided by the invention can be used for not only making up the conservative property of the conventional evaluation, but also preventing plenty of time from being spent in building a complex model, and the precision meets the engineering needs.

The invention provides a remote sensing target detection method based on boundary constraint CenterNet, which is used for solving the technical problems of relatively low detection precision and recall rate of dense small targets in the prior art. The method comprises the following implementation steps: obtaining a training sample set; the method comprises the following steps: constructing a boundary constraint CenterNet network; obtaining a prediction label and an embedded vector of the training sample set; calculating the loss of the boundary constraint CenterNet network; carrying out the training of a boundary constraint CenterNet network; and obtaining a target detection result based on the trained boundary constraint CenterNet network. Through performing maximum pooling in the constrained pooling area through the corner constraint pooling layer, the fine features around the target are extracted, the detection precision and recall rate of dense small targets are effectively improved, meanwhile, the boundary constraint label generated by the boundary constraint convolutional network is utilized to constrain the prediction box, a more accurate target prediction box is obtained, and the detection precision of the target is further improved.

The invention discloses an underground structure quasi-static test device and method. The device includes a counterforce device, a model box, a boundary constraint device, an actuator and an underground structure model. The counterforce device is composed of a counterforce wall and a steel frame. The model box is located between the counterforce wall and the steel frame and is spliced by four vertical reinforced steel plates and a bottom steel plate. The model box adopts flexible connection for the gaps among the reinforced steel plates on the periphery. The tops of the left and right reinforced steel plates are pulled towards each other by roller connecting members, and the bottoms are hinged with the bottom steel plate with rollers. The left side of the model box is provided with the actuator at the top and is provided with a hydraulic pressure stabilizer at the bottom. The model box is provided internally with an underground structure member and is filled with a similar material to surrounding rocks. The mode box is provided with rubber spacers on the two sides. The rubber spacers are connected with the steel plates through clamping grooves. The rubber spacers can be varied in the type and detached partially to simulate different constraint conditions. The underground structure quasi-static test device and method of the invention can achieve quasi-static loading of an underground structure and simulate seismic response features of the underground structure, and have the advantages of being economical in test, simple to operate, high in reliability and so forth.

The invention provides a method and system for acquiring a ground water storage variation value by combing a gravity recovery and climate experiment (GRACE) satellite. The method comprises: acquiring satellite data of the GRACE satellite, land water storage data, water intake and use hydrological model data and longitude and latitude information of a preset region, and computing a satellite appearance ground water storage variation value of the preset region; and acquiring analogue ground water storage variation iterative value of the preset region, and determining an analogue ground water storage variation iterative value of the preset region, which meets the preset condition, to be the ground water storage variation value according to the analogue ground water storage variation iterative value of the preset region by using the water intake and use hydrological model data as a boundary constraint condition. According to the method for acquiring the ground water storage variation value by combing the GRACE satellite, the acquired ground water storage variation value is more accurate, the spatial resolution of the ground water variation value can be improved about 50 times, and the inversion error of the ground water storage variation value is controlled within 10%.

The invention discloses a concrete dam formwork safety construction analysis method based on finite element simulation. The invention simulates the stress and deformation development law of the high formwork under different loading conditions before and during the concrete pouring and rolling construction through finite element simulation, according to the design drawings and technical parametersof large formwork, the original two-dimensional drawing is transformed into three-dimensional finite element model in ADINA finite element software AUI geometry modeling, and by combining with the lateral pressure measured in the existing site filling construction, the deformation parameter and template boundary constraint parameter setting, the simulation simulates the deformation and stress prediction analysis of large formwork under different working conditions, especially the most unfavorable construction loads, such as rapid filling, thereby providing decision-making parameters for the design optimization, installation and transformation of large formwork and construction process adjustment, and ensuring the safety and economy of formwork design and construction application.

The invention discloses a modeling method for airplane composite material wall plate weight analysis and relates to the airplane weight research direction in the airplane overall design technical field. The modeling method is used for weight control in the airplane composite material structural component production process and includes the steps that S1, structural parameters are defined and comprise parameters of panels and ribs; S2, a composite material wall plate structure finite element model is constructed; S3, loads and boundary constraint of the composite material wall plate structure finite element model are defined; S4, the structural strength and the rigidity of the composite material wall plate structure finite element model are analyzed; S5, structural stability is analyzed; S6, a laying layer of a composite material structure is optimized; S7, the composite material wall plate structure weight is calculated. According to the modeling method for airplane composite material wall plate weight analysis, finite element modeling is fast and accurately performed on an anti-axial-compression composite material wall plate structure at the early stage of airplane design, and therefore the weight, the gravity center and the rotating inertia of the anti-axial-compression composite material wall plate structure can be accurately and fast calculated through numerical simulation.

The invention discloses an operating index optimization method in the beneficiation process, and belongs to the technical field of the beneficiation process. The method comprises the steps of collecting operating indexes of various processes in the beneficiation process; optimizing the operating indexes in the beneficiation process according to the collected operating indexes and operating index boundary constraint so as to optimize the quality index and the yield index in the beneficiation process, wherein the optimization process comprises the steps of setting the boundary constraint, the target value of the quality index and the target value of the yield index of the beneficiation process, optimizing the set target value of the quality index and the set target value of the yield index, predicting the quality index and the yield index, obtaining the predicted value of the quality index and the predicted value of the yield index, correcting the preset values of the target values of the operating indexes and obtaining the optimization values of the operating indexes; and sending control instructions to the various processes in the beneficiation process according to the optimization values of the operating indexes. According to the method, by setting corresponding work condition parameters, the target values of the operating indexes corresponding to the different processes are controlled through complete flow scheme daily comprehensive production index optimization of enterprises, and coordinative optimization of the various processes in the beneficiation process is achieved.

The invention relates to a method for calculating deformation of a throttle valve disc of hydraulic damper combination valve under the action force of a spiral spring, which belongs to the field of dampers; the invention aims at solving the problem of calculating the deformation that restricts the analytical design of practical dampers and the characteristic stimulation modelling valve discs. The method provided by the invention comprises the steps of establishing an equivalent simplified mechanical model of the throttle valve disc according to the physical model of the damper throttle valve disc under the action of spring force; establishing the bending deformation curved surface differential equation of the throttle valve disc under the spring action force by utilizing the theory of the elasticity mechanics; obtaining the general solution of the differential equation by utilising the boundary constraint condition of the throttle valve disc and the continuous condition at the loading position; and establishing the bending deformation coefficient and the bending deformation analytical calculation formula of the throttle valve disc at any radius through the identical transformation. The method provided by the invention avoids the repeated test and modification when designing the damper, reduces the design cost of the damper and improves the development period of the damper; the method provided by the invention can be used for analytic design and characteristic stimulation of the cylinder hydraulic damper.

Four-dimensional (4D) computed tomography (CT) is simulated by first generating a surface mesh from a single thoracic CT scan. Tetrahedralization is applied to the surface mesh to obtain a first volume mesh. Finite element analysis, using boundary constraints and load definitions, is applied to the first volume mesh to obtain a lung deformation according to an Ogden model. Constrained tetrahedralization, using control points, is applied to the lung deformation to obtain a second volume mesh, which is then deformed using mass-spring-damper simulation to produces the 4DCT.

The invention provides a high-speed train body local structure instability finite element simulation device and method. By simulating train body structure completeness and defect conditions of local profile concave or protrusions through a linear buckling analysis and finite element simulation method, analyzing local instability critical load force of the train structure, and instructing tooling applying, working days off processes and welding parameter setting during existing train machining, waste and safety potential hazards are prevented. The method comprises using a man-machine interaction unit, building models according to train body drawings, and establishing simulation concave portions on the local train body portions; establishing train body boundary constraints, performing linear synthesis to obtain train body maximum vertical loads and compression loads, and defining train body mode frequencies, establishing static loads and linear buckling analysis work conditions; performing train body instability simulation analysis, and calculating critical buckling coefficients to obtain the maximum load that can be applied; determining that the portions are reliable if the critical buckling coefficients are larger than or equal to 1; determining that the portions need be reinforced if the critical buckling coefficients are smaller than 1.