148 results about "Coefficient matrix" patented technology

The invention discloses a deep and far sea wind power time-varying impedance model grid connection analysis method based on a time domain residual error method, relates to the technical field of power system modeling simulation, and can efficiently and accurately analyze deep and far sea wind power grid connection. The method comprises the following steps: establishing a differential algebraic equation set containing high-capacity submarine cable impedance and a plurality of nonlinear links, and constructing a recursive coefficient matrix; dividing a preset global time domain into a plurality of time domain subintervals, and solving the recursion coefficient matrix in each time domain subinterval by referring to a universal analytic solution represented by a power series explicit operator to generate a global time domain explicit solution corresponding to the preset global time domain; performing discrete Fourier transform on the global time domain explicit solution to obtain a time-frequency domain spectrum result; and constructing a time-varying impedance model according to the differential algebraic equation, setting the time-varying impedance model by adopting a time-frequency domain spectrum result, and analyzing the deep and far sea wind power grid-connected control system by utilizing the set time-varying impedance model.

The invention relates to the technical field of ion beam physical calculation, in particular to an ion beam optical property evaluation method based on a CPU-GPU hybrid parallel stable double-gradient conjugate algorithm. According to the technical scheme, the method comprises the following steps that a CPU-GPU hybrid parallel architecture is initialized, and CPU end and GPU end memory allocation, CUDA related object creation and GPU equipment initialization and parameter setting are completed; constructing a linear equation set, a sparse coefficient matrix A and a right-end vector b, and setting an initial solution vector, convergence precision epsilon and related parameters of the number of iterations; and analyzing the sparseness of the coefficient matrix A. Through combination of three core mechanisms of CPU-GPU cooperative calculation, dynamic load balancing and intelligent preprocessor selection, efficient, stable and universal evaluation of the ion beam optical characteristics is successfully realized, and an excellent solution is provided for solving the solving problem of a large-scale sparse linear equation set in the field of high-performance calculation.

The invention relates to the technical field of geometric error evaluation of hole and shaft parts in the field of machinery, and discloses a hole and shaft part action boundary discrimination method, which comprises the following steps of: deriving a motion coefficient vector for describing radius change of each measuring point based on a tiny rigid body motion model of a surface measuring point set of a measured part; and the motion coefficients are combined into a motion coefficient matrix. Furthermore, the method establishes a discriminant inequality group based on a mutual exclusion proposition. The judgment process is realized by analyzing the rank of the motion coefficient matrix and iteratively solving an equation set formed by the maximum linear independent matrix of the motion coefficient matrix, and finally, whether the fitting cylinder is the action boundary or not is determined by judging whether the inequality set has a feasible solution or not. According to the method, the problems of complicated geometric discrimination conditions, lack of universality and the like in the existing evaluation method can be solved, and a reliable basis which is easy to realize in a stylization manner is provided for determining the action boundary of the hole-shaft part.

A method of non-destructive testing (NDT) using prompt gamma neutron activation analysis (PGAA) and a suite of algorithms based on various mathematical algorithms, includes: analyzing stored spectra for net peak areas; determining aggregate type from the analyzed stored spectra; calculating dominant element ratios; solving for dominant element mass fractions; calculating elemental mass fractions; solving a linear equations system including a coefficient matrix; and determining material components.

The invention provides a balance calibration modeling method and system based on sample errors and space optimization. The method comprises the steps of obtaining a calibration data set and dividing the calibration data set into a sample set and a verification set; calculating a load space weight and a load complexity weight of the sample set, and obtaining a comprehensive weight based on the load space weight and the load complexity weight; and constructing a polynomial model of the sample set, and solving a coefficient matrix in the polynomial model based on the comprehensive weight to obtain a final balance calibration model. The method further comprises the following steps: verifying and evaluating the balance calibration model by using the sample set and the verification set, and optimizing the balance calibration model according to an evaluation result. According to the balance calibration modeling method cooperating with the sample space distance and the load complexity weight provided by the invention, nonlinear system errors introduced by calibration load complexity are fully considered, so that the influence of error distribution of calibration samples under various load combinations on modeling is more uniform and reasonable; and meanwhile, the problem of sample space occupation ratio is also solved.

The invention relates to a POD secondary manifold lower chamber flow field nonlinear model order reduction method based on anchor point optimization, and the method comprises the steps: obtaining a two-dimensional lower chamber computational fluid mechanics model as a full-order model, and building a snapshot matrix according to the full-order model; carrying out POD order reduction on the snapshot matrix, and calculating a POD reconstruction error matrix and a secondary manifold coefficient matrix of the snapshot matrix; determining an anchor point, and calculating a quadratic manifold modal matrix at the anchor point according to the POD reconstruction error matrix and the quadratic manifold coefficient matrix; according to the secondary manifold modal matrix at each anchor point, obtaining a secondary manifold modal matrix at the test point; and according to the quadratic manifold modal matrix at the test point, calculating an approximate snapshot of the POD quadratic manifold nonlinear reduced-order model at the test point. According to the method, the representative anchor points are introduced into the parameter sampling space, so that self-adaptive calculation of the secondary manifold modal matrix is realized, and the approximation precision of the reduced-order model is improved.

In order to overcome the problem that the current technology is difficult to estimate and continuously correct the bridge twin model by obtaining a series of test and test data, the application provides a bridge twin dynamic model Fourier modeling method based on test data, which is only related to the parameters of the bridge according to the system matrix related to all nodes of the bridge and the observation coefficient matrix related to all nodes, and the first continuous test process of the bridge does not change greatly, and the first comprehensive detection of the bridge twin dynamic mathematical model and the subsequent each time of the bridge twin dynamic mathematical model comprehensive correction process is relatively short, according to the characteristics of the fast and slow change matrix, the slow change matrix is set as a constant matrix in the first continuous test, and the system matrix related to all nodes of the bridge and the observation coefficient matrix related to all nodes in the bridge twin model are established through a series of effective tests and optimal indexes, and the bridge twin model is continuously corrected in the whole life cycle of the bridge, so that the technical problem of estimating and improving the bridge vibration model by obtaining a series of test and test data is solved.

The present invention discloses a method for quickly calculating the frequency response characteristics of a hollow winding coil of arbitrary shape, belonging to the technical field of electrical and electronic equipment components and sensors. The method comprises: establishing a three-dimensional rectangular reference coordinate system with a certain point in space as the origin; calculating the geometric center spatial coordinates of each turn based on the geometric centerline parameter equation of the skeleton, thereby obtaining the spatial parameter equation of each turn; combining the Newman formula to calculate the mutual inductance of any two turns and the self-inductance coefficient of the turns, the capacitance, resistance and skin depth between the turns, and the electrical relationship equation between any turn and other turns; writing the electrical relationship equation in matrix form, converting the coefficient matrix of the equation into an upper triangular matrix, and then converting the matrix into a coil port voltage and current relationship equation to obtain the coil port frequency response characteristics. The present invention has strong versatility, convenient calculation, and is easy to program for calculation, saving design time. No empirical formula is required during the calculation process, and the calculation accuracy is high.

Embodiments of the present disclosure disclose an implicit geological modeling method based on adaptive grid and an electronic device. A specific implementation of the method comprises: performing initial grid division on a calculation region according to geological modeling parameters and geological source data to obtain a first grid set; determining a grid to be refined in the first grid set according to a preset judgment rule; dividing the grid to be refined into a set of sub-elements according to a preset refinement rule to obtain a second grid set of the calculation region; storing grid data of the second grid set; performing difference on a second grid in the second grid set and determining a coefficient matrix A according to a difference coefficient; constructing a linear equation set Ax=b based on the Lagrange multiplier method, wherein the vector b is used to represent point constraints and directional constraints; solving the linear equation set to obtain a second grid value, and outputting a modeling result according to the second grid value. Thus, a new implicit geological modeling method based on adaptive grid is provided.

The application discloses a neutron transport constitutive relation and low-dimensional control equation modeling method based on sparse regression, which comprises the following steps: a neutron flow matrix under multiple state parameters is formed by state parameters of each state and physical quantity parameters calculated through a neutron transport program; fitting physical quantity parameters are filled into a sparse regression physical quantity matrix; a coefficient matrix is obtained by using a least square method to calculate an inverse matrix; and a neutron transport constitutive relation under multiple state parameters is obtained by assembling. The application utilizes the accurate characteristics of the calculation result of the neutron transport equation, grasps the cause of the larger deviation of the calculation result of the neutron diffusion equation in a small scale range, combines sparse regression fitting to obtain the neutron transport constitutive relation, and further obtains a low-dimensional macroscopic neutron transport control equation. The theoretical derivation is less difficult, the research progress is easier, the effect of improving the calculation precision is more obvious, the applicability is better, the gap with the situation under the actual reactor core working condition is not large, and the application has certain practicality.

The application discloses a multi-unmanned aerial vehicle control method based on reinforcement learning and belongs to the technical field of unmanned aerial vehicle cooperative control. The application designs a control algorithm for a double-time-scale multi-agent, effectively avoids possible calculation errors in the process of solving a matrix equation by introducing a novel coefficient matrix, and proposes a hybrid iteration algorithm which is independent of initial stable controller gain and has a fast convergence speed and is used for solving an approximate solution of a game algebraic Riccati equation based on a communication topology between agents. The application can realize consistency between unmanned aerial vehicles, enables the unmanned aerial vehicles to work cooperatively, and completes a task.

Embodiments of the invention disclose a constraint equation determination method and apparatus, a medium, a device and a product. The method comprises the steps of obtaining a constraint equation of an augmented matrix group; the constraint equation is represented as follows: the sum of the first product and the second product is zero, a subordinate degree-of-freedom vector in the constraint equation is determined by an independent degree-of-freedom vector, a weight coefficient matrix, a displacement matrix and a distribution matrix, and the distribution matrix is determined by the weight coefficient matrix and the displacement matrix; and determining a target weight coefficient matrix and a target displacement matrix, and substituting the target weight coefficient matrix and the target displacement matrix into the constraint equation to obtain a target constraint equation of the augmented matrix group. According to the method, the weight coefficient matrix capable of accurately reflecting the physical coupling strength between the nodes and the displacement matrix capable of representing the real deformation state can be automatically calculated, the constraint equation is generated, the defect of insufficient calculation precision caused by simple hypothesis of the constraint relation is effectively overcome, and therefore the construction effectiveness of the constraint equation can be improved.

The invention discloses a parallel solving method and system for a system of linear equations of an electric power system based on a Woodbury theory, and belongs to the technical field of large-scale electric power system computation.The method comprises the steps that a coefficient matrix of a network equation of the electric power system is obtained and subjected to block representation; performing truncated singular value decomposition on the non-diagonal block coupling matrix, and realizing low-rank decomposition through an Arnoldi iterative algorithm; carrying out inversion on the coefficient matrix based on a Woodbury matrix identical equation, and carrying out parallel calculation on each block sub-matrix and an intermediate variable; and solving the system of linear equations by using the inversed matrix. According to the method, the low-rank characteristic and parallel computing advantages of the inter-region coupling matrix of the power system are fully utilized, the solving efficiency of the large-scale linear equation set is remarkably improved, and the method is suitable for transient analysis, real-time simulation and other high-performance computing scenes of the power system.

The invention belongs to the technical field of line resistance network analysis, and discloses a fast line resistance network analysis method for a nonvolatile memory array, which comprises the following steps of: establishing electrode KCL equations of all rows and columns in a line resistance network of the nonvolatile memory array; a voltage line and a coefficient matrix in the KCL equation are transformed and decomposed, a fixed point iterative algorithm is introduced, and voltage distribution of nodes at the top and the bottom of the array is iteratively calculated. An original complex large-scale linear equation set problem is converted into two small-scale sub-problems. And solving is carried out through mutual iteration of the two sub-problems, so that the calculation complexity and the calculation memory are reduced. According to the method, the influence of IR-drop on neural network calculation acceleration can be predicted and evaluated in the design stage. The method has the advantages that the accuracy is high, and the influence of IR-drop can be simulated with the accuracy exceeding 95%; the calculation complexity is low, and the calculation complexity is reduced from O ((2mn) 2) to O (mn); the memory load is small, and the use of the memory is minimized while high accuracy is kept.

The present invention provides a trajectory polynomial generation device, comprising a trajectory floating-point calculation circuit and a trajectory sequence controller. The trajectory sequence controller is coupled to the trajectory floating-point calculation circuit. The trajectory sequence controller performs a cubic spline interpolation algorithm to convert the coordinates of a plurality of path points into coefficients of a curve. The trajectory sequence controller schedules the trajectory floating-point calculation circuit to calculate the x-axis step length between any two adjacent path points among the plurality of path points, uses the x-axis step length to obtain multiple elements of a coefficient matrix in a linear equation system of the cubic spline interpolation algorithm, uses the x-axis step length and the coordinates of the plurality of path points to obtain multiple elements of a constant vector in the linear equation system, uses the coefficient matrix and the constant vector to obtain a quadratic difference value vector in the linear equation system, and uses the quadratic difference value vector to calculate the coefficients of the curve.

The present invention discloses a method for fast mode decomposition of anti-noise fiber laser, including: obtaining a spot to be decomposed with noise, rearranging the eigenmodes into vectors in sequence, and then multiplying the N eigenmode vectors pairwise to obtain a coefficient matrix A; obtaining a mode information vector X based on the coefficient matrix A; determining the errors of the elements in the mode information vector X based on the L2 norm of the pseudo-inverse matrix A<supgt;‑1< / supgt>, and deleting the elements with larger errors until at least 2N‑1 elements remain in the mode information vector X; establishing a nonlinear equation system based on the remaining elements in the mode information vector X, obtaining the mode coefficients and mode phases of each eigenmode restored, and generating a first reconstructed spot therefrom to obtain the mode decomposition result. The present invention is applied to the field of fiber laser mode decomposition. Based on the matrix analysis method, redundant feature information is screened and removed, so as to improve the measurement accuracy of mode coefficients and mode phases in a noise environment.

The invention discloses an efficient numerical solution method for a steady-state water head field of a dam containing a complex foundation, and relates to the technical field of geotechnical engineering. The method comprises the following steps: establishing a seepage mathematical model in a Cartesian coordinate system by acquiring foundation parameters and boundary conditions, introducing similar lines parallel to a far-field boundary to construct an improved proportional boundary finite element coordinate system mapping relation, and discretizing and deducing a variable coefficient control equation by adopting a one-dimensional high-order spectrum unit; an equation is simplified into a Riccati equation by analyzing the characteristics of a coefficient matrix, an infinite seepage matrix is solved in combination with Schur decomposition, a seepage matrix at a boundary is obtained through iteration of a fourth-order Runge-Kutta method with the infinite seepage matrix as an initial value, and finally steady-state water head field distribution is obtained. According to the method, the continuity of the interface water head and the flowing boundary condition is guaranteed, the precision and efficiency of complex foundation seepage solving are greatly improved, and reliable technical support is provided for engineering seepage-proofing design and stability evaluation.

The invention belongs to the technical field of underwater acoustic detection. The invention provides a distributed sound barrier layout optimization method based on a minimum estimation error. According to the embodiment of the invention, constraint conditions such as the number of sound sources and receivers, the laying range and the like are input, and a linear equation set of an observation model is established in combination with a target motion model; taking the equation set coefficient matrix condition number as an optimization index, taking a sonar node position vector as an optimization independent variable, and taking matrix condition number minimization as a principle to establish a system layout objective function; a detection area is gridded to reduce the calculation amount, and a global optimal solution of the position of the sonar node is given in a traversal search mode. According to the method, specific transmitting and receiving configuration is not needed, the target detection precision is practically improved through layout optimization, and higher practicability and flexibility and universality are achieved in application.

The present invention relates to a wide-range concentration detection system and method for a gas analyzer. The system includes a light source, a collimator, a measuring cell, a spectrometer, a temperature controller, a signal converter, a data acquisition module, and a data analysis module. The method collects a reference zero-point spectrum and concentration sequence spectra of n gases as reference original spectrum sequences, performs differential, normalization, and polynomial fitting on the reference zero-point spectrum and obtains n fitting coefficient matrices for the n gases. The matrix is ​​then combined with the real-time differential spectrum of the gas to be measured to form a nonlinear equation system. The least squares method is used to solve the nonlinear equation system to obtain the initial normalized concentration solution of each gas. The initial normalized concentration solution is further optimized and denormalized to obtain the final concentration value of each gas. The present invention solves the problem of gas concentration detection when the absorption cross section and concentration of the gas to be measured have a nonlinear relationship, and has high detection efficiency and detection accuracy, and a wide concentration detection range.

The application belongs to the technical field of robot dynamics parameter identification, and discloses a double sparse efficient identification method and system for robot dynamics parameters. The method comprises the following steps: S1, collecting joint positions, joint speeds, joint torques and joint accelerations of a robot to be processed at each time; S2, constructing an implicit dynamics equation of the joint torque by taking the joint torque as a target; S3, constructing a base function database, evaluating the importance of each base function in the base function database, thereby completing the first sparse of the base function; and performing sparsification on the coefficient matrix to make some elements in the coefficient matrix 0, thereby completing the second sparse of the base function, determining the base function and the coefficient matrix, and realizing the acquisition of an explicit dynamics equation of the joint torque. Through the application, the technical problems of complex theoretical modeling or low interpretability of a black box model in the prior art are solved.

The present application relates to the technical field of data processing, and especially relates to a sparse direct solution method based on data kernel external storage, which comprises the following steps: obtaining a coefficient matrix of a high-dimension sparse linear equation group, analyzing a non-zero element distribution mode and a matrix topological structure to establish a task dependency relationship; detecting a system memory capacity and a disk performance parameter to set a slice size parameter, dividing a wavefront matrix into data slices with balanced floating-point operation amounts to execute a left-looking numerical decomposition; creating a message queue and a monitoring mechanism to realize asynchronous disk storage; reading data from the disk to execute a numerical update cycle; and establishing a back substitution solution memory work area to generate a numerical solution by using a previous generation back substitution algorithm. The present application utilizes disk storage to relieve memory pressure and supports large-scale finite element simulation application.

The application discloses a kind of based on parameter self-adapting time-invariant track information acquisition method, comprising: for the orbit equation of spacecraft motion, construct linear random time-invariant system, determine initial state quantity and external disturbance term;Based on initial state quantity and external disturbance term, obtain constant coefficient matrix and constant disturbance input matrix;Input the parameter self-adaptive Runge-Kutta solver established, obtain the list of to-be-solved orbit parameters;According to the adaptive parameter constraint formula, the dependent relationship of each parameter in parameter list is solved, free parameters therein are optimized according to genetic algorithm, iteratively updated until the optimal parameters of determination standard are obtained, these parameters are used as the parameters of Runge-Kutta solver, and the orbit information is iteratively solved by Runge-Kutta solver to realize the acquisition of orbit information.The application can be widely applied to space science and technology satellite orbit solving aspect, and is not only suitable for single scientific satellite orbit determination, but also suitable for scientific satellite constellation orbit formulation.

The invention provides a quantum classical hybrid calculation method and device. The method comprises the following steps: performing linearization operation on an objective function and constraint conditions in a QCBO model; setting a variable matrix and a linear mapping operator according to the objective function after linearization operation, the constraint condition and the corresponding co-orthogonality optimization problem; according to the current variable matrix and the linear mapping operator, calculating to obtain a residual vector, and calculating to obtain a secondary unconstrained binary optimization coefficient matrix; solving the current secondary unconstrained binary optimization problem to obtain a current solution vector; determining an iteration direction according to the current solution vector, updating the variable matrix by using the first step length, and taking the updated variable matrix as a current variable matrix; and when the number of iterations is greater than a preset iteration threshold value, performing rounding operation on the current variable matrix, and extracting a vector from the variable matrix after the rounding operation as a final solution. By applying the method, the problem of 0-1 binary optimization with nonlinear constraints can be effectively solved.

The invention discloses a load flow calculation method, system and device based on quantum singular value transformation and a medium, and belongs to the technical field of load flow calculation, and the method comprises the steps: obtaining the initial power parameter of each node of a power system and the given power of each node, and determining the power unbalance amount; constructing a node admittance matrix according to the initial power parameters, constructing a correction equation of Newton method load flow calculation, and converting the correction equation into a linear equation set for expression; coding the coefficient matrix into a unitary matrix by using block coding, and executing polynomial transformation based on quantum singular value transformation to construct a quantum circuit representing an inverse matrix of the unitary matrix; encoding the power unbalance amount into a quantum initial state, and enabling a quantum circuit to act on the quantum initial state and performing measurement; and determining the correction of the node voltage based on the measurement result, judging whether to iterate based on the convergence condition, and outputting a load flow calculation result. By utilizing the characteristics of quantum parallelism and quantum singular value transformation, the time consumption of large-scale power system load flow calculation is remarkably reduced.

This invention discloses an advanced positioning algorithm that, by constructing a statically indeterminate linear equation system, can efficiently integrate data from various stations in a large-scale distributed positioning system and accurately determine the target location in a single calculation. Its innovation lies in utilizing the transformation relationship between polar and rectangular coordinate systems to directly construct a boundary value equation containing mixed variables based on the path difference equation. Through appropriate equation transformation and variable substitution, the algorithm achieves linearization of the boundary value equation, significantly simplifying the calculation process. Furthermore, addressing the decisive influence of the path difference construction method or matrix construction strategy on positioning accuracy, this invention proposes unique path difference construction rules or coefficient matrix construction methods. These rules and methods ensure highly accurate positioning results in practical applications. The new algorithm is not only simple but also significantly improves positioning efficiency, bringing a revolutionary change to large-scale distributed positioning.

The present invention relates to a method for estimating the radiated sound pressure of a shallow water complex target based on a near-field vertical array, comprising the following steps: S1, using a vertical array equal to the water depth to measure the near-field sound pressure of a sound wave emission point, and measuring a virtual cylindrical measurement surface that can completely enclose the sound wave emission point at different orientations of the sound wave emission point; S2, substituting the measurement data of each array element point of the vertical array into the general solution form of the radiated sound pressure in the virtual cylindrical coordinate system and constructing a matrix equation; S3, then solving the coefficient matrix of the radiated sound pressure, substituting the obtained coefficient matrix into the modal expansion form solution of the radiated sound pressure in the virtual cylindrical coordinate system, and calculating the radiated sound pressure of any point outside the virtual cylindrical measurement surface in the shallow water ocean waveguide. The beneficial effect is that in the ocean waveguide, the far-field sound pressure is estimated using the near-field vertical measurement data array.

The present invention belongs to the technical field of line resistance network analysis, and discloses a fast line resistance network analysis method for a non-volatile memory array, comprising: establishing KCL equations for electrodes in all rows and columns of the line resistance network of the non-volatile memory array; transforming and decomposing the voltage lines and coefficient matrices in the KCL equations, introducing a fixed-point iteration algorithm, and iteratively calculating the voltage distribution of the top and bottom nodes of the array. The originally complex large-scale linear equations problem is converted into two smaller-scale sub-problems. The two sub-problems are solved by mutual iteration, thereby reducing the computational complexity and computational memory. The method of the present invention can predict and evaluate the impact of IR-drop on the acceleration of neural network calculations during the design phase. Advantages include: high accuracy, capable of simulating the impact of IR-drop with an accuracy of more than 95%; low computational complexity, reducing the computational complexity from O((2mn) 2 ) is reduced to O(mn); the memory load is small, minimizing memory usage while maintaining high accuracy.

The invention relates to the technical field of automatic driving, and discloses an automatic driving decision planning cooperation method and system based on fault prediction, and the method comprises the steps: collecting gateway operation data, carrying out the abnormal trend detection and analysis of time sequence features, and generating a fault probability prediction curve; acquiring a load trigger signal and dynamic response data, and estimating a quality parameter on line by a recursive least square algorithm; the mass center position is calculated by combining suspension displacement data with a statics equation, and a kinetic parameter updating package is generated through fusion; comparing the gateway fault probability with a threshold judgment risk, sending an update packet and generating a check code at a low risk, and pre-synchronizing a storage snapshot at a high risk; updating the kinetic equation coefficient matrix and outputting to a decision domain and a chassis domain; when the gateway fails, each domain operates independently based on a snapshot, and versions are compared to verify consistency and output a collaborative identifier; according to the invention, each function domain can still cooperatively operate based on the same kinetic parameter reference during the gateway fault period.

The present invention discloses a method for analyzing the dynamic characteristics of a composite beam taking into account shear slip and vertical uplift, belonging to the field of bridge dynamics and civil engineering structure analysis. The method comprises establishing a composite beam motion control equation and natural boundary conditions based on the material properties of the composite beam; deforming the composite beam motion control equation to obtain a deformed motion control equation; substituting the input frequency into the deformed motion control equation to solve the eigenvalues ​​of the coefficient matrix of the motion control equation; obtaining a general solution to the motion control equation; constructing a matrix-vector product expression of the force and displacement boundary to obtain a dynamic stiffness matrix; substituting the input frequency into the dynamic stiffness matrix to obtain a dynamic stiffness matrix corresponding to the input frequency in the current round; and judging whether the input frequency is a frequency corresponding to the composite beam based on the determinant of the dynamic stiffness matrix corresponding to the input frequency in the current round. The present invention solves the problems that current methods do not consider shear slip and vertical uplift and cannot strike a balance between efficiency and accuracy.

The application provides a volume coefficient matrix fast solving method for residual stress field deduction and application, and relates to the technical field of material stress measurement and characterization. The method comprises the following steps: step S1: calculating the unconstrained node sub-stiffness matrix inverse matrix of the initial state of a part; step S2: calculating the unconstrained node sub-stiffness matrix change caused by material removal of the part at each step; step S3: calculating the unconstrained node sub-stiffness matrix inverse matrix of the part at each step; step S4: calculating the volume coefficient matrix of the part at each step; and step S5: assembling the volume coefficient matrix of the part at each step into a volume coefficient matrix. The method solves residual stress by using the volume coefficient matrix in residual stress field deduction. The application significantly improves the calculation efficiency of the volume coefficient matrix, and effectively solves the problem of low calculation efficiency of the volume coefficient matrix in the prior art.