8 results about "Inverse Laplace transform" patented technology

The invention provides a Laplace-DLTS stabilization inversion method and system, and the method comprises the steps: applying a pulse bias voltage to a tested semiconductor device, and collecting a transient capacitance signal of the tested semiconductor device; the transient capacitance signal is preprocessed; performing inverse Laplacian transformation processing on the preprocessed transient capacitance signal, and introducing at least one of non-negative constraint, sparsity constraint, physical prior constraint and time window segmentation constraint in an inversion process; carrying out optimization processing on the obtained inversion result, and judging the stability of the inversion result; and extracting a deep energy level trap parameter based on the inversion result, and outputting the deep energy level trap parameter and the processed transient spectrum data. At least one, preferably at least two, constraint conditions are introduced in the inverse Laplacian inversion process, so that the influence of noise and abnormal peaks on the inversion result is effectively inhibited, and the stability, physical consistency and parameter extraction reliability of the inversion are improved.

The invention provides a dendritic pipe network thermal dynamic modeling method based on a transfer function, and belongs to the technical field of electric digital data processing. The method comprises the following steps: firstly, establishing an advection diffusion-heat loss control equation of a single pipeline, and deducing a frequency domain transfer function of the single pipeline through Laplace transformation; then combining theoretical analysis and high-precision numerical simulation to accurately calibrate and correct a turbulence temperature diffusion coefficient alpha and a temperature loss coefficient gamma, so that the physical consistency of the model is remarkably improved; the method comprises the following steps: for a dendritic pipe network topological structure, decomposing the dendritic pipe network topological structure into a plurality of independent branches according to heat user load nodes, and constructing a frequency domain expression of the return water temperature of the whole pipe network based on a flow weighting principle; and finally, obtaining a time domain response through inverse Laplace transformation. The method effectively solves the contradiction between the insufficient precision of a traditional node method and the complex calculation of a high-precision numerical method, considers both the modeling precision and the calculation efficiency, and is suitable for the real-time optimization scheduling of the heat supply pipe network in the comprehensive energy system.

This invention discloses a food baking processing control system and method, belonging to the field of intelligent control technology for food processing. The system includes: acquiring the dielectric properties of materials and capturing the dynamic changes in the dielectric loss tangent; simultaneously using time-domain dielectric spectroscopy analysis to identify the phase transition stages of the materials in real time; constructing a dual-channel heat conduction model and dynamically identifying the regional temperature gradient of the baking equipment based on the phase transition stages; and calculating the microwave power adjustment and fan speed ratio adjustment of the baking equipment based on the regional temperature gradient of the baking equipment using a multi-parameter coupled control algorithm, and generating a composite control command set. This invention identifies the phase transition stages of materials in real time using time-domain dielectric spectroscopy analysis, and accurately analyzes the correlation between the relaxation time distribution and the phase transition characteristic spectrum using inverse Laplace transform and dynamic time warping algorithms, achieving dynamic capture of key phase transition nodes such as glass transition and starch gelatinization.

The invention discloses a method, system and equipment for determining the emulsification effect of a middle-phase microemulsion based on nuclear magnetic resonance, a medium and a product, and relates to the technical field of oil exploitation, and the method comprises the following steps: carrying out baseline correction, noise removal, normalization processing and Laplace inverse transformation on a spin echo intensity signal; obtaining an effective diffusion coefficient-effective transverse relaxation time combined distribution diagram, projecting the effective diffusion coefficient-effective transverse relaxation time combined distribution diagram in an effective diffusion coefficient direction, and solving by adopting a multi-peak Gaussian fitting model and a least square method according to the effective diffusion coefficients of different components to obtain an effective diffusion coefficient range; and integrating the effective diffusion coefficient-effective transverse relaxation time combined distribution diagram within the effective diffusion coefficient range so as to determine an effective transverse relaxation time distribution curve, obtaining a simulated oil peak area in a bicontinuous phase and a simulated oil peak area in an oil phase through integration, and calculating the emulsification effect of the middle-phase microemulsion. According to the method, the accuracy of calculating the emulsification effect of the to-be-detected middle-phase microemulsion can be improved.

The application provides a kind of branch pipe network thermal dynamic modeling method based on transfer function, belongs to the technical field of electric digital data processing.The application first establishes the advection diffusion-heat loss control equation of single pipeline, and deduces the single pipe frequency domain transfer function through Laplace transform;Then, combined with theoretical analysis and high-precision numerical simulation, the turbulent temperature diffusion coefficient α and temperature loss coefficient γ are accurately calibrated and corrected, which significantly improves the physical consistency of the model;For the topology structure of branch pipe network, it is decomposed into multiple independent branches according to the heat user load node, and the frequency domain expression of the overall pipe network return water temperature is constructed based on the flow weighting principle;Finally, the time domain response is obtained by inverse Laplace transform.The application effectively solves the contradiction between the insufficient accuracy of traditional node method and the complexity of high-precision numerical method, balances the modeling accuracy and calculation efficiency, and is suitable for real-time optimization scheduling of heating pipe network in integrated energy system.

This method uses magnetic resonance (MR) data to estimate a diffusion tensor distribution (DTD). The method includes inverting a Fredholm integral of the first kind, specifically performing an nD Inverse Laplace Transform subject to several constraints. First, a positive definiteness constraint is used, which zeros out a subset of diffusion tensor components that do not lie on a manifold of symmetric positive definite matrices. Second, marginal distribution constraints are used, which further partition the manifold of symmetric positive definite matrices into even smaller domains to improve DTD estimates in each MR voxel.

The invention relates to the technical field of process safety operation, in particular to a process continuous operation method and system, electronic equipment, a storage medium and a program product, and the method comprises the steps: constructing a time domain model according to a dynamic mechanism of a process system; converting the time domain model into a complex frequency domain model through Laplace transformation; solving a complex frequency domain optimal continuous operation variable based on the complex frequency domain model, and converting the complex frequency domain optimal continuous operation variable into a time domain optimal continuous operation variable through inverse Laplace transformation; and performing continuous operation based on the time domain optimal continuous operation variable. According to the process continuous operation method, an analytical method based on a complex frequency domain is provided, continuous working condition switching of a complex chemical system is achieved, compared with a subsection control strategy, the continuous control strategy can describe the real situation as much as possible, feature details of operation variables are clearly presented, higher information density is achieved, and the method is suitable for large-scale popularization and application. And therefore, the safety and the stability of the production process can be improved.

This invention provides a method and apparatus for simulating positive alpha stable distribution sea clutter amplitude data, relating to the field of sea clutter data processing technology. The method includes: determining a probability density function based on the characteristic function, inverse Laplace transform, Merlin transform properties, and G function of the positive alpha stable distribution; determining a cumulative distribution function based on the probability density function; establishing a correspondence table between multiple target characteristic index parameters, multiple target comprehensive scale parameters, multiple target sea clutter amplitude values, and the values ​​of the cumulative distribution function; and determining the target sea clutter amplitude data matrix based on preset characteristic index parameters, preset scale parameters, a random number matrix, and the correspondence table. By utilizing the characteristic function, inverse Laplace transform, Merlin transform properties, and G function of the positive alpha stable distribution, a closed-loop representation of the probability density function of the positive alpha stable distribution is achieved, enabling the direct simulation and generation of positive alpha stable distribution sea clutter amplitudes.