27 results about "Non linear behavior" patented technology

The present application relates to a kind of mountainous large-span bridge transverse damping system parameter solving method and system, method includes: obtaining bridge structure, establish spatial finite element model, obtain target design displacement, set the initial damping parameter of each position damper of bridge;Actual displacement is calculated based on the damping parameter at this time, and the adjusted vector of damper is obtained according to the difference between target design displacement and actual displacement, combined with adjusted vector and influence matrix, calculate the application vector, the adjusted damping parameter is calculated based on application vector, it is judged whether the adjusted damping parameter satisfies design requirement, if satisfy, then the adjusted damping parameter is regarded as final damping parameter, otherwise, repeat this step.Compared with prior art, the basic principle of influence matrix is used, the multi-tower / pier coupling effect in transverse damping system and the strong nonlinear behavior of damping measure are considered, and the reasonable design parameters of damping system at each tower / pier position can be determined by the iterative calculation of fast and stable convergence.

The invention discloses a digital self-interference cancellation method based on transceiver nonlinear behavior modeling, and belongs to the technical field of electronic reconnaissance and interference. The digital self-interference cancellation method comprises the following steps of performing linear combination on memory components of a broadband signal, and generating cross terms with different phase structures by using a nonlinear effect so as to construct a Wiener model; establishing a multipath self-interference channel model; nonlinear modeling is carried out on linear components of interference signals received by a radio frequency front end at a receiver, and nonlinear component modeling is a linear model; for a nonlinear model constructed by a linear component in an interference signal received by a radio frequency front end, adopting dynamic reduction measurement to reduce the complexity of the model; parameter preliminary estimation is carried out by using the characteristics commonly represented by the intermediate variables, and parameter estimation is optimized by combining a two-step iterative algorithm; and reconstructing the transmitting signal in the digital domain according to a parameter estimation result to generate a reference signal, and realizing interference cancellation in the digital domain of the receiving end.

This invention provides a converter impedance measurement method that overcomes the influence of nonlinearity. By injecting voltage disturbance signals of different frequencies and amplitudes multiple times, the impedance is determined based on the voltage and current responses of the voltage disturbance signals. The method also takes into account the voltage and current responses caused by circuit disturbances, which can effectively avoid the influence of nonlinear behavior in the process of determining the impedance group of the converter under test, ensure the final measurement accuracy, and provide accurate data reference for subsequent impedance stability analysis and the formulation of impedance stabilization strategies.

The application discloses a kind of based on the detection result prediction method of electric network reserve pool, belong to neural network technical field, the method includes: the voltage signal sequence corresponding to historical detection result is passed into the electric network reserve pool based on the input node of multiple type electric characteristic neuron, to map voltage signal sequence into high-dimensional output state matrix;Compared with the dimension increasing method of pure mathematical operation of traditional reserve pool algorithm, this method is completely based on the I-V intrinsic electric characteristic of semiconductor device, for the spontaneous nonlinear behavior of electric network formed by the connection of multiple electric characteristic neurons, it is highly explainable, and it is convenient to physically realize.Further, the output state matrix of electric network reserve pool is dimensioned again, the future detection result is predicted by the fitting of historical detection result, thereby solve the technical problems that extrapolation prediction based on historical data in existing detection technology is difficult to realize.

The invention provides an equivalent thin layer unit simulation method and system for an eVTOL aircraft threaded connection structure. And respectively calculating the axial rigidity of the internal thread under the unit length, the radial rigidity of the internal thread under the unit length, the axial rigidity of the external thread under the unit length and the radial rigidity of the external thread under the unit length. And calculating the axial total rigidity and the radial total rigidity of threaded connection, and determining the axial modulus and the radial modulus of the equivalent thin-layer material. In the finite element model, establishing a thin layer unit at a threaded connection interface, and endowing the thin layer unit with an axial modulus and a radial modulus; and connecting the thin layer unit and the two parts in threaded connection through binding constraint, and applying a pre-tightening force and a dynamic load to complete construction of a simulation model. Therefore, the simulation precision is improved, the dynamic response error is reduced, and the nonlinear behavior of the thread under multiple working conditions can be accurately simulated.

The application provides a SiC MOSFET behavior modeling method based on physical mechanism optimization, comprising: for a SiC MOSFET output characteristic curve, constructing a static electrical model structure of the SiC MOSFET on the basis of considering a drain-induced barrier lowering effect of the SiC MOSFET; based on the static electrical model structure, adopting a voltage function to describe nonlinear behavior of an interelectrode capacitance varying with a bias voltage, and constructing a dynamic characteristic model structure of the SiC MOSFET; adopting a method combining experimental data and structure function analysis to perform physical mechanism optimization on the static electrical model structure and the dynamic characteristic model structure, and obtaining a final required SiC MOSFET behavior model. The application can accurately reflect static and dynamic characteristics of the SiC MOSFET device, improve precision, applicability and convenience of parameter extraction of the model, and meet design requirements of a new generation of high-performance power electronic systems.

The invention discloses a permanent magnet synchronous linear motor optimal current control method based on a magnetic equivalent circuit model, and the method comprises the steps: considering the nonlinear behavior of a motor, building an accurate MEC model suitable for a PMLSM for a stator part, an air gap part and a rotor part through the electromagnetic quantity of the motor, and building an electromagnetic parameter and thrust balance equation; therefore, an accurate motor thrust expression is obtained, and an optimal current control strategy considering thrust accuracy and coil copper loss minimization is further designed based on the motor thrust expression. According to the MEC model and the corresponding optimal current control strategy, the calculation burden can be reduced on the basis that the model precision is ensured, meanwhile, accurate control over the position and thrust is achieved, the optimal current strategy can further reduce copper loss and improve the efficiency of the system, and high research value and application value are achieved.

The application relates to the field of ethylene industry diagnosis, in particular to an ethylene furnace tube coking thickness prediction method and system.The method comprises the following steps: collecting ethylene furnace tube parameter time sequence data, extracting time sequence convolution features, obtaining bidirectional time sequence features through bidirectional time sequence dependence processing, and obtaining time sequence pooling features through attention pooling; linearly mapping the features to obtain a furnace tube coking thickness linear prediction value, combining a learnable nonlinear transformation with the linear prediction value to obtain a furnace tube coking thickness nonlinear prediction value; finally, fusing historical furnace tube coking thickness prediction error features, the furnace tube coking thickness linear prediction value and the furnace tube coking thickness nonlinear prediction value to calculate the furnace tube coking thickness prediction value of the ethylene furnace tube.Compared with the prior art, the linear behavior and the nonlinear behavior are combined, and the fusion strategy is adaptively adjusted based on the historical prediction error, so that the ethylene furnace tube coking thickness can be effectively predicted.

This application discloses a method and system for adjusting neurological drug delivery parameters. By collecting real-time ambient temperature information and actual instantaneous motor speed data around the infusion pump and comparing them with the expected response of the motor under ideal linear operating conditions, it can accurately identify and quantify the nonlinear behavior characteristics of the motor caused by temperature. A two-dimensional mapping relationship is established based on the ambient temperature information and nonlinear behavior characteristics. Before issuing the target control command, the current ambient temperature is acquired in real time, and the corresponding compensation parameters are calculated according to the mapping relationship. Finally, the target control command is adjusted and compensated based on these compensation parameters. This effectively solves the problems of decreased drug delivery accuracy and flow fluctuation caused by differences in the physical properties of novel drug solutions, long-term performance degradation of motors, and nonlinear response characteristics in the prior art.

The application provides a magnetic liquid rheology measurement method under a magnetic field. The magnetic liquid rheology measurement method comprises the following steps: S1, performing strain scanning on the magnetic liquid, drawing a corresponding change curve, and determining the linear viscoelastic region and the non-linear viscoelastic region of the magnetic liquid; S2, selecting a strain value according to the linear viscoelastic region of the magnetic liquid, performing frequency scanning on the magnetic liquid under the magnetic field, drawing a corresponding change curve, and obtaining the linear viscoelastic property curve of the magnetic liquid under the magnetic field; S3, performing time scanning on the magnetic liquid under the non-constant magnetic field, and drawing a corresponding change curve; and S4, performing a steady shear experiment on the magnetic liquid under the magnetic field, drawing a corresponding shear flow curve, and obtaining the non-linear rheological property of the magnetic liquid under the magnetic field. The application can reflect the rheological property of the magnetic liquid under different magnetic fields, provide help for the non-linear behavior analysis of the magnetic liquid under the magnetic field, and provide a theoretical basis for the application of the magnetic liquid under the magnetic field.

The invention discloses an apparatus and method for non-linearity cancellation in an electronic system. In some embodiments, an electronic system includes two or more circuit channels that process a common input signal in parallel, each circuit channel including at least one instance of a non-linear behavior circuit. Thus, a non-linear circuit is replicated and included in each circuit channel at least once. Each circuit channel has an input scaling factor and an output scaling factor that can be changed from one circuit channel to another. The scaled output signals of the circuit channels are combined to generate a combined output signal. The input and output scaling factors are selected to eliminate or reduce nonlinearity.

In order to deeply explore the dynamic response mechanism and the elasticity resistance of the composite target plate under the impact of the projectile, the missile-target action finite element model of the composite target plate is based on all components of the composite target plate, combines the dynamic characteristics of the impact of the projectile, reasonably divides grid units and selects an adaptive material constitutive model, so that the missile-target action finite element model of the composite target plate is obtained. And deformation, damage and failure behaviors of different materials under the high-speed impact load are accurately described. In a model building process, a nonlinear behavior of a missile target contact interface is emphatically considered, a penalty function method and a Lagrangian multiplier method are combined to process contact state change in a projectile penetration process, and meanwhile, an adaptive mesh refinement technology is introduced, so that the operation efficiency is improved on the premise of ensuring the calculation precision; through comparison with related experimental data (such as projectile residual velocity, armor damage mode and the like), the calculation result of the model is highly matched with an experimental value, which indicates that the dynamic mechanical response rule of the composite target plate under the impact of the projectile can be effectively reflected.

The invention relates to a refined axle coupling power simulation analysis method and device based on OpenSees and a medium, and belongs to the technical field of bridge structure simulation. According to the method, the additional spring-mass-damping effect of any moving vehicle and the random traffic flow can be considered, and the axle coupling power simulation analysis capability under linear and nonlinear behavior modeling scenes is integrated based on an OpenSees open source finite element calculation platform. According to the method, a vehicle is regarded as a multi-degree-of-freedom spring-mass-damping vibration system composed of a vehicle body, a suspension system and tires, and the vehicle mass effect and the suspension system of the vehicle are simulated through vehicle body container nodes and zero-length units. And determining the position of the vehicle on the current bridge floor based on the pseudo time and the vehicle speed time history in OpenSees. The wheel load is applied through a series of pulse load modes in OpenSees. By combining a WIM vehicle statistical model with a microscopic traffic flow model with vehicle following and lane changing capabilities, accurate simulation of random traffic flow is realized.

The application discloses an AGV digital twin monitoring method based on a three-dimensional simulation model, relates to the technical field of digital twin monitoring, and comprises the following steps: performing multi-dimensional feature extraction on a target AGV to form an AGV behavior mode vector set; generating a nonlinear coupling matrix representing the correlation strength between AGV motion state parameters and environmental constraint parameters based on the vector set and environmental geometric information; dividing a three-dimensional digital twin model into a plurality of simulation units, and independently simulating local AGV disturbance responses of the units according to the matrix; mapping high-frequency motion events and low-frequency task events into the simulation units based on the local AGV disturbance responses to form a nonlinear disturbance coupling field; and dynamically adjusting a virtual AGV state based on the disturbance propagation trend of the disturbance coupling field. The application realizes nonlinear behavior synchronization of a virtual AGV and a physical AGV, thereby solving the problem that virtual and real behaviors of an AGV are difficult to be consistent in the prior art.

The invention relates to a hyperbolic sand large-diameter single pile design method based on static sounding, which comprises the following steps: firstly, acquiring geometric parameters of a single pile, such as pile diameter, wall thickness, penetration depth and the like, and soil body information including effective weight and conical tip resistance; then calculating initial rigidity and ultimate bearing capacity of pile-soil interaction, and determining a rigidity attenuation coefficient and a bearing capacity adjustment coefficient according to a penetration-depth ratio; integrating the parameters to establish a hyperbolic p-y spring relationship at different depths so as to accurately simulate the nonlinear behavior of the soil body; then dispersing a single pile into beam units by applying a Timoshensincaro beam-spring model, and obtaining the lateral displacement distribution of a pile body and the bearing capacity of a soil body under an external load through numerical solution; and finally, a load-displacement curve at the mud line is generated by combining the load eccentric distance, and complete prediction of the displacement response of the pile body is achieved. Compared with the prior art, by combining the static sounding data with the hyperbolic model, the design precision and reliability of the large-diameter single pile in the sandy soil are improved.

The application relates to the field of numerical simulation and provides a method and system for evaluating the shearing performance of a shearing connector of a concrete structure, the method comprising the following steps: constructing a finite element model of a target shearing connector; calculating a shearing performance prediction value of the target shearing connector based on the finite element model; constructing a mechanics model based on the stress analysis result after stress analysis of the target shearing connector; calculating a shearing performance theoretical value of the target shearing connector based on the mechanics model; and evaluating the performance of the target shearing connector based on the shearing performance prediction value and the shearing performance theoretical value. The method is used to solve the defects that the complex interaction between the connector and the concrete, the material nonlinear behavior and the failure mechanism are difficult to accurately simulate in the related art, the prediction accuracy is insufficient, the design is conservative or potential risks exist, and the scheme can more accurately predict and evaluate the performance of the shearing connector.

The invention relates to the technical field of seismology, in particular to an incremental dynamic correction method for related spectrum duration evolution of a gravity dam, which comprises the following steps: establishing a finite element model of the gravity dam, determining mechanical parameters, nonlinear behaviors and boundary conditions of the model, and setting analysis working conditions; based on the seismic characteristics of a specific site, determining the coupling evolution law of the seismic oscillation duration and the seismic oscillation spectrum shape along with the seismic intensity; non-linear responses of the gravity dam under different analysis working conditions are obtained, and the non-linear response difference between the standard IDA working condition and the actual coupling working condition and only one of the working conditions changing along with the peak ground acceleration is determined; and constructing a unified correction model, and correcting an analysis result of a standard IDA method by quantifying a spectrum form difference and a duration difference and introducing a spectrum shape effect function, a duration correction coefficient and a coupling correction coefficient so as to eliminate systematic deviation.

The invention discloses a hyper-chaos heterogeneous neural network circuit for electrical synapse regulation. The circuit comprises a two-dimensional Hopfield neural network integrating circuit and a three-dimensional Hopfield neural network integrating circuit which are connected through an electrical synaptic coupling channel. The electrical synapse coupling channel is simple in structure, and state interaction between two heterogeneous neurons is realized through an addition subtractor and a variable coupling resistor. The method has the beneficial effects that the dynamic state of the whole heterogeneous neural network can be effectively controlled only by adjusting the single variable coupling resistor, so that the heterogeneous neural network shows multiple exact dynamic behaviors such as hyper-chaos, chaos, quasi-periodic and periodic behaviors. Compared with the prior art, the circuit provided by the invention does not contain a multiplier, is simple in structure and low in cost, and can realize abundant and reproducible nonlinear behaviors through a simple and convenient adjustment mode.

The application relates to a control system and an optimization control method based on a composite controller and relates to the field of advanced control technology. The existing nonlinear time-delay system is generally present in complex industrial control and automation systems, and traditional control strategies are difficult to effectively cope with the problems caused by time delay and nonlinearity. The application eliminates the influence of time delay in the system by designing a Smith predictor, and introduces a fractional order controller to enhance the adaptability of the system to nonlinear behavior. The composite controller formed by combining the Smith predictor and the fractional order controller can significantly improve the dynamic response performance and control accuracy of the system. In order to further optimize the controller parameters, an improved artificial rabbit optimization algorithm is adopted. The algorithm improves the global search ability and convergence speed by introducing a dynamic adjustment factor, a Levy flight strategy and a boundary control strategy.

The application provides a GIS internal fastener loosening active diagnosis method and system, a control exciting device is used to apply exciting force to a target gas chamber according to a linear frequency modulation signal, and input signals and output signals are obtained, an acoustic vibration transfer function and a coherence function are constructed according to the input signals and the output signals, a selected resonance peak is selected based on the acoustic vibration transfer function, and a frequency shift average value of the selected resonance peak relative to a standard curve is calculated to obtain a first index, a coherence value average of the selected resonance peak in an effective evaluation frequency band is calculated according to the coherence function to obtain a second index, and a diagnosis result of an internal fastener of the target gas chamber is determined based on a comparison result of the first index, the second index and a safety threshold, and the test error is eliminated through the acoustic vibration transfer function, and the fastener state is evaluated from two dimensions of stiffness change and nonlinear behavior.

The application discloses an intelligent power distribution room AI decision analysis system based on edge computing, which comprises a data acquisition preprocessing module, a friction state modeling module, a comprehensive state construction module, a fast and slow state evolution module, an operation decision determination module and a control instruction generation module.The data acquisition preprocessing module forms standardized multi-dimensional operation state data.The friction state modeling module constructs an improved GMS friction model and forms a friction state variable set.The comprehensive state construction module constructs a comprehensive operation state vector.The fast and slow state evolution module forms fast variable state evolution sequences and slow variable state evolution sequences.The operation decision determination module executes transient operation state determination and operation degradation trend determination, and generates edge side operation decision analysis information.The control instruction generation module generates operation control instructions.The application realizes stable operation decision analysis of the intelligent power distribution room on the nonlinear behavior of the actuator and the fast and slow evolution state by introducing the improved GMS friction model and the singular perturbation theory.

The present application relates to the technical field of bolt connection, in particular to a method for predicting the working condition of bolt connection structure based on the representation of pre-tightening force relaxation. The present application proposes a double exponential decay function, and the parameters of different functions are identified. The double exponential function is simple in structure and good in representation, and the fitting accuracy reaches 99.3%, which can accurately represent the bolt pre-tightening force relaxation law. The pre-tightening force relaxation law function is introduced into the Iwan model to represent the Iwan model under the relaxation condition conforming to the actual situation, the relationship between various parameters and pre-tightening is analyzed, the least square method is used to construct the mathematical expression, the pre-tightening relaxation law in the cycle is equivalent to the pre-tightening relaxation law of the tangential displacement and the loading time, and the Iwan model density function under the relaxation condition is constructed based on various changing parameters. The method of the present application can predict the nonlinear behaviors such as energy dissipation and stiffness degradation, and especially provides a more accurate method for predicting various indicators under the pre-tightening relaxation condition of the bolt.

The invention discloses a high-speed data processing method and device based on optical co-packaging and a medium, and relates to the technical field of photoelectric integrated packaging, and the method comprises the steps: receiving a to-be-transmitted high-speed data stream, carrying out the real-time monitoring of a sensor array integrated at a photon chip and a key position of a packaging substrate, and obtaining multi-dimensional physical quantity sensing data; carrying out fusion and standardization processing on the multi-dimensional physical quantity sensing data, and constructing a feature vector used for representing a multi-physical field coupling state in a current package; inputting the feature vector into a digital twinborn model, and describing parameters of the nonlinear behavior of the optical modulator in the current environment; and performing probabilistic shaping coding on the to-be-transmitted high-speed data stream, and obtaining a pre-distortion lookup table for compensating nonlinear distortion based on the nonlinear response parameter set and probabilistic shaping parameters used by the probabilistic shaping coding. According to the invention, mechanism-driven and high-precision prediction from the environment state to the nonlinear response of the device is realized.

The invention relates to the technical field of chemical production, in particular to a construction method and device of a viscoelastic material model, electronic equipment and a storage medium. The construction method comprises the steps that through dynamic mechanical testing of a linear viscoelastic area, the change relation of the energy storage modulus and the loss modulus along with the angular frequency is obtained; determining the shear viscosity and the characteristic relaxation time of the material; acquiring a stress response signal under a large-amplitude oscillation shear condition, extracting a high-order harmonic coefficient representing a nonlinear behavior through harmonic analysis, preliminarily determining a nonlinear parameter of the constitutive model according to the high-order harmonic coefficient, and calculating a theoretical stress response; and finally, by taking the nonlinear parameter, the shear viscosity and the relaxation time as initial values and minimizing the deviation between a theory and actually measured stress response, iterative optimization is carried out until convergence, so that the viscoelastic material model is obtained. According to the method, the non-linear parameter identification precision and the calculation efficiency can be remarkably improved, and the constructed model has excellent prediction capability and reliability in a wide frequency and wide strain range.

The invention provides a SiC MOSFET (Metal-Oxide-Semiconductor Field Effect Transistor) modeling method and system considering various parasitic parameters, and belongs to the technical field of SiCMOSFET device modeling. The method comprises the following steps: constructing a parasitic junction capacitance relational expression of the SiC MOSFET device; carrying out sectional modeling on the input capacitance of the SiC MOSFET device; modeling is carried out on an output capacitor and a reverse transmission capacitor of the SiC MOSFET device; obtaining drain inductance, source inductance, gate inductance and gate driving resistance of the SiC MOSFET device; constructing a diode model; and building a double-pulse test circuit of the SiC MOSFET device. According to the method, the defects of an existing SiC MOSFET device modeling method in the aspects of precision and efficiency are overcome, and particularly the problem of simulation deviation caused by neglecting key parasitic parameters and nonlinear behaviors in the high-frequency switching process of the SiC MOSFET device is solved.

The application discloses a spiral anchor foundation bearing effect evaluation method and system, relates to the technical field of finite element analysis, and comprises the following steps: establishing a soil body and a spiral anchor finite element model, setting a boundary condition, and obtaining finite element data; according to the finite element data, introducing a local damage variable based on a stress-strain degradation function, simulating local shear band development, and generating first damage data, wherein the first damage data comprises a first stress-strain curve and a first local damage variable; stratifying the soil body, optimizing the first damage data based on layer internal constraints, and obtaining second damage data; and calculating full-field stress, displacement and bearing capacity based on a finite element solver according to the second damage data for effect evaluation; and the problems of inaccurate spiral anchor effect evaluation caused by soil body nonlinear behavior and stratified heterogeneous effects are solved.

This disclosure describes systems, methods, and apparatus for an adaptive engine with a bifurcated nonlinear model partially represented by a mapping function. The adaptive engine uses a nonlinear model able to produce a possible control signal via a mapping function. The model also has estimation portion using a time-varying linear system to approximate nonlinear behavior of a power system. A boot up phase can be used wherein the mapping function provides possible control signals based on measured system outputs rather than an estimated model parameter tensor.