256 results about "Iterative method" patented technology

An iterative method for monitoring a computing device characterized by metric data to be monitored, including, for each iteration, of collecting metric data over a predetermined interval of time, detecting a seasonality pattern of said metric data over said predetermined interval of time, determining an interval-specific model representing the detected seasonality pattern, calculating modelled data using said determined model and the collected metric data, comparing the calculated modelled data with the collected metric data to calculate a score characterizing the difference between the calculated modelled data and the collected metric data, calculating an anomaly likelihood for each data of the collected metric data using the calculated score, detecting an anomaly on a data when probability that the value of said data is an anomaly is greater than a predetermined threshold.

The invention discloses a three-level ANPC converter model prediction control method and device based on Newton iteration method vector optimization, and belongs to the technical field of converter control, and the method comprises the steps: building a mathematical model of a three-level ANPC converter under a three-phase static coordinate system based on the Kirchhoff theorem; performing forward Euler discretization on the mathematical model of the three-level ANPC converter to obtain a current prediction equation model; establishing a cost function according to the control target; performing online search on the optimal voltage vector according to a cost function; voltage vector synthesis is carried out, voltage vectors selected when the optimal voltage vector falls in 36 different small sectors, a voltage vector action sequence and action time distribution are obtained through calculation, and then the action time of a pair of redundant positive and negative small vectors in the voltage vectors is adjusted to carry out neutral point potential balance control. According to the invention, rapid optimal voltage vector search and three-level ANPC converter output current and neutral point potential control are realized.

The invention discloses a circular foundation pit diaphragm wall deformation calculation method and system based on a vertical elastic foundation beam. The method comprises the steps that S100, a design scheme and design parameters of a circular foundation pit are collected; s200, establishing a vertical elastic foundation beam calculation model of the circular foundation pit supporting structure, and inputting the design scheme of the circular foundation pit into the model; s300, dispersing the beam into a plurality of calculation points, dividing the excavation step into a plurality of load increment steps, and calculating each load increment step of the beam; and S400, based on the load increment step of the beam, calculating an accumulated deformation amount, and outputting the accumulated deformation amount. A bending equation of a vertical elastic foundation beam is adopted to establish a calculation model of a circular foundation pit supporting structure, an inner supporting structure is introduced into the bending equation of the beam, the excavation process is decomposed into a plurality of excavation steps and increment steps, an iteration method is adopted for calculation, and the soil pressure distribution and deformation process of each stage in the excavation process is accurately simulated. Therefore, the accuracy of deformation calculation of the circular foundation pit diaphragm wall is improved.

The invention discloses a water level prediction method based on an improved intelligent algorithm, a readable storage medium and a device, and belongs to the technical field of water level prediction.The method comprises the steps that normalization preprocessing is conducted on original hydrological data of multi-source information, and an original water level sequence is obtained; performing VMD decomposition on the original water level sequence to decompose the original water level sequence into modal components; inputting the modal component into an LSTM model to construct a prediction model; and inputting an original water level sequence of recent multiple days into the prediction model, generating a predicted value of a future date based on an iteration mode, and restoring to obtain real water level data through reverse normalization processing. A computer program is stored in the readable storage medium, and the method is carried out when the computer program is executed. The apparatus includes a memory, a processor, and a terminal program stored in the memory and operable in the processor. Water level influence factors can be comprehensively considered, multiple variables are fused, the water level condition closer to the reality is obtained through analysis, and the water level prediction precision is improved.

The invention belongs to the related technical field of power system optimization operation, and particularly relates to a non-iterative interconnected multi-microgrid system optimal power flow determination method based on a dimensionality reduction projection method, and the method comprises the steps: reconstructing a multi-microgrid centralized operation model, and obtaining a sub-problem of each sub-microgrid; taking a multi-dimensional variable space formed by all public variable sets in each sub-problem and a preset sub-microgrid operation cost variable as a projection space of the sub-problem; determining an initial vertex set of the projection of the convex hull corresponding to the original operation space constraint of each sub-problem in the projection space, and translating the coordinate origin to the interior of the convex hull enclosed by the vertex set; based on the convex hull and the outer normal vector of each boundary surface, circularly searching vertexes satisfying original operation space constraints outside each boundary surface in the projection space, and taking a space enclosed by a final vertex set as a projection space of the operation space constraints of the sub-problem; and reconstructing the sub-problem in the space and solving the sub-problem. According to the method, the optimal power flow can be solved under the condition that only public variables are disclosed.

The invention provides a financial research report generation method based on a large model. Comprising a data collection module, a data analysis module and a report writing module. The data collection module is used for receiving a predefined data collection task and an autonomously generated data collection task, then inputting the tasks into a deep search agent, and constructing a structured multi-modal memory for a search result for storage; the data analysis module constructs a data analysis agent, and realizes the generation of a structured multi-modal small report through cooperation of a financial calculation tool, a chart generation tool and a reference addition tool in an actor-reviewer iteration mode in which a large language model is matched with a visual language model; and the report writing module constructs a report writing agent to obtain a chapter first draft and then inputs the chapter first draft into the post-processing agent to obtain a final report. The problems that an existing deep research system and a large language model agent in the financial field are lack of financial field knowledge, limited in multi-modal ability, limited in research and report generation depth and comprehensiveness and the like are solved.

The application discloses a kind of gas-liquid two-phase flow numerical simulation method considering coalbed gas desorption lag, comprising the following steps: using well logging, indoor experiment means to obtain productivity calculation parameter;Desorption equation of matrix system is defined in combination with desorption lag effect, diffusion equation;Gas-water two-phase percolation equation of fracture system is defined, and desorption equation of matrix system, diffusion equation is combined, and double medium gas-water two-phase coupling flow equation set is formed;The porosity and permeability change of matrix system and fracture system in production process is calculated respectively, and the physical property change equation set of double medium is deduced;Using the numerical solver of COMSOL, the coupling equation set is solved using iterative method, and the gas production and water production are calculated.The application is simple to operate, can more scientific and reasonable assess the influence of coalbed gas desorption lag effect on gas well productivity, while greatly reducing the cost and time of gas well numerical simulation calculation, and also has important inspiration for other unconventional gas reservoir development affected by desorption lag.

The embodiment of the invention discloses a nonlinear system dynamic characteristic calculation method based on a structural dynamic modification method, and the method achieves the high-precision reduced-order modeling of a nonlinear structure through enabling a complex nonlinear effect to be equivalent to an additional stiffness field and combining with a structural dynamic modification algorithm. And based on the decoupled linear substructure modal space, a nonlinear correction operator is introduced, and the global dynamic response of the nonlinear structure is solved through a resolving method after modification. Structural vibration frequency, vibration shape and energy dissipation characteristics under a nonlinear effect can be efficiently obtained, and dynamic characteristics under different nonlinear amplitudes can be obtained. Compared with a traditional iteration method, the method has the advantage that the calculation complexity is remarkably reduced by equivalently linearizing a nonlinear part.

The embodiment of the invention provides a calculation method and device for boundary parameters of a supercritical fluid heat exchanger, computer equipment and a medium, and relates to the technical field of fluid mechanics and heat transfer science calculation.The method comprises the following steps that design parameters and target working conditions of the heat exchanger are obtained; calculating to obtain the single section length of each infinitesimal section; based on the initial inlet pressure guess value, according to the length of the single section and the pressure and the temperature of the infinitesimal section i, the pressure and the temperature of the infinitesimal section i + 1 are obtained through calculation, the difference value between the outlet calculation pressure and the target outlet pressure is calculated, and the difference value serves as a pressure error; if the pressure error is greater than the convergence tolerance, updating the inlet pressure guess value by adopting a numerical iteration method, and performing iteration again based on the inlet pressure guess value after iteration; otherwise, iteration is terminated, and the final inlet pressure value and the final outlet temperature value are output. According to the scheme, the calculation efficiency and accuracy of solving the inlet pressure and the outlet temperature of the supercritical fluid heat exchanger under the given target outlet pressure are improved.

The invention relates to the technical field of power systems, and discloses a wind and light output scene-oriented power system power flow data reconstruction method, system and device and a medium, and the method comprises the steps of constructing structured boundary input data; generating a voltage amplitude and a phase angle estimation vector of each node through a deep neural network model, and taking the voltage amplitude and the phase angle estimation vector as a power flow initial solution; performing physical constraint check on the initial solution, identifying out-of-limit nodes and determining an adjustable point set with reactive power regulation capability; and in the range of the adjustable point set, constructing an optimization function, solving to obtain a local adjustment quantity, correcting the initial solution, and generating a final power flow solution meeting the operation constraint of the power system. According to the method, data-driven modeling and physical constraint checking are fused, overall mapping is performed on a high-dimensional scene formed by wind and light output and load by using the deep neural network, the problem that the convergence performance is sharply reduced when the dimension is increased and the number of scenes is increased in a traditional iteration method is avoided, and rapid, stable and engineering-available power flow data generation is realized.

The invention discloses a low-altitude flight path planning method based on grid coding, which relates to the technical field of path planning, and is characterized in that on the basis of space and time grid coding, an A * path planning algorithm is improved, a neighbor node range in a classical algorithm is expanded, pruning optimization for removing invalid neighbors is applied to the A * path planning algorithm, and the path planning efficiency is improved. Relatively fast searching and establishment of a smooth grid path meeting the motion constraint become possible; an algorithm for interpolating a track on a grid path at equal time intervals is introduced; comprising the following steps of: thinning and smoothing a grid path; carrying out mathematical modeling on a flight state of the unmanned aerial vehicle; calculating flight segment initial and final speeds and flight segment middle cruising speeds which meet the motion performance constraint of the unmanned aerial vehicle and the consistency between flight segments by a backtracking iteration method; and calculating specific flight path points by speed integration. And a relatively accurate unmanned aerial vehicle flight plan track prediction generation method is provided.

Lowest cost usage scheduling of an energy system during a time interval of interest is achieved by utilizing two components of learning and optimization. First, several learning methods are used to forecast energy production and if needed energy consumption of a given group of energy components as a function of historical production data, weather, and solar irradiance data collected from weather and geo reports. A classification approach is used to select the learning model. A classification approach is used to select the learning model and approach. Then, an optimization problem is formulated and solved to create the optimal schedule of energy usage during time intervals of interests for the given group of energy components subject to scheduling and equipment constraints. Accordingly, integrated iterative methods, programs, and systems are described aiming at minimizing the cost of energy consumption for the given group of energy components within time intervals of interest.

The disclosed systems, methods, and computer-readable media for attributing value to a plurality of members of a company can be configured to retrieve, from each user device associated with at least a respective member, first user input data indicating a respective set of initial scores; assign a respective preliminary first member valuation to at least one member of a group; update a respective preliminary first member valuation assigned to each member of the group by performing an iterative method; generate at least one feature vector based at least on the each first user input data and the respective preliminary first member valuation assigned to each member of the group; provide the at least one feature vector to a machine learning model that is configured to generate final member valuations for the first group for generation of a recommendation that at least one member of the first group be replaced.

The invention relates to the technical field of computer aided design, in particular to a neighborhood gradient-oriented large-curvature curved surface projection point calculation method, which comprises the following steps of: S1, calculating a space bounding box of a curved surface to be projected, and performing triangulation to generate a triangular mesh; s2, traversing curved surface control vertexes of the triangular mesh, recording an adjacent vertex set, and judging whether the vertex set is a boundary point or not according to the UV parameter coordinates; s3, storing the vertex information and constructing a BVH tree, traversing the BVH tree for a to-be-projected point, querying and obtaining the nearest vertex with the minimum distance from the to-be-projected point, judging whether the nearest vertex is a boundary point or not, and processing according to a judgment result to obtain an iteration initial value; and S4, constructing a target function by taking the iteration initial value as an initial value, and calculating by using a Newton iteration method to obtain an accurate projection point of the to-be-projected point on the curved surface. The curved surface projection point approximation result calculation method is high in calculation efficiency and robustness, and the influence of curvature, grid division and other factors on Newton iteration input is reduced.

The invention discloses a power distribution network load flow calculation method based on a full-pure embedding theory. The power distribution network load flow calculation method comprises the following steps: (1) establishing a full-pure embedding load flow calculation model of a two-node system consisting of a balance node and a PQ node by applying a full-pure embedding method; (2) deriving and expanding based on the full-pure embedded load flow model of the two-node system established in the step (1) to obtain a full-pure embedded load flow calculation model of a multi-node system comprising a balance node and N PQ nodes; and (3) completing power flow calculation of the power distribution network by using the full-pure embedded power flow calculation model of the multi-node system. Compared with the Newton-Raphson method, the method has the advantages that the difference is small, the calculation time is greatly shortened, and the accuracy and the high efficiency of the method are remarkably improved compared with those of the Newton-Raphson method which is an iterative method.

The invention discloses a multi-park integrated energy system collaborative optimization method based on an equivalent projection theory. The method comprises the following steps: establishing a park integrated energy system scheduling model considering fuel gas hydrogen doping; establishing a park integrated energy system robust collaborative scheduling model participating in the multi-park integrated energy system alliance by considering the uncertainty of hydrogen energy interaction and energy load; the established double-layer region integrated energy system robust collaborative scheduling model is equivalent to a single-layer mixed integer programming collaborative scheduling model based on an equivalent projection theory; deriving a decentralized solution of the established mixed integer programming collaborative scheduling model by using a dual decomposition algorithm; and establishing a multi-park integrated energy system collaborative optimization model based on the feasible region equivalent projection and solving the multi-park integrated energy system collaborative optimization model. According to the method, a two-stage robust problem is converted into an MILP type robust optimization problem through feasible region projection, the converted model does not need to be iteratively solved, and the solving time is greatly shortened compared with that of a traditional iterative method; and a decentralized solution is derived by using a dual decomposition algorithm, so that the convergence and optimality of the result are ensured.

The invention relates to the technical field of bearing assembly, in particular to a rolling bearing assembly optimization method and system based on a particle swarm algorithm. The method comprises the following steps: discretizing a contact area and correcting a local curvature by acquiring the material modulus and the microcosmic waviness of a bearing assembly, and generating an infinitesimal stiffness mapping matrix; then, an assembly parameter vector is constructed, the Newton-Raphson iteration method is used for solving the real displacement, meeting force balance, of the inner ring, a stiffness time-varying curve is synthesized, and a closed-loop pre-tightening response spectrum is generated; and finally, defining a stiffness ripple robust index containing a stiffness variance and a gradient penalty term, and optimizing and outputting an assembly instruction through a hybrid coding particle swarm optimization algorithm. According to the method, the geometric error complementary effect of parts can be effectively utilized, the rigidity fluctuation in the rotation period is eliminated, and the dynamic precision and the process robustness after the bearing is assembled are remarkably improved.

The invention discloses a disturbance-induced lag type rockburst prediction method, device and system, and a storage medium. The method comprises the following steps: collecting disturbance data; according to the disturbance data, damage values under different disturbance amplitude conditions are calculated, meanwhile, the disturbance number is normalized, and the relation between a damage coefficient and the normalized disturbance number is obtained; fitting the relationship between the damage coefficient and the relative disturbance frequency of the sample subjected to the rockburst, trying by adopting a least square method, and searching a uniform fitting curve which meets all the rockburst samples; adopting an iteration method to adjust the values of N and epsilon u for the sample which does not generate the hysteresis type rockburst; wherein N is the disturbance frequency of rock burst, and epsilon n is the vertical strain corresponding to the disturbance frequency n; and calculating the rockburst time according to the disturbance times of the rockburst. By adopting the technical scheme, the hysteresis type rockburst risk under the low-amplitude disturbance condition can be effectively predicted, and the method has the advantages of being simple in structure, high in adaptability and high in practicability.

The invention relates to the technical field of hydrographic survey, in particular to a riverway water flow calculation method, which comprises the following steps: acquiring topographic data, hydrological data and roughness data, and constructing a one-dimensional riverway hydrodynamic numerical model; the one-dimensional river channel hydrodynamic numerical model is based on a discontinuous finite element method and a Runge-Kutta time discrete shallow water equation set, and a numerical flux is solved by combining an essential oscillation-free ENO slope limiter and an HLL Riemann solver; aiming at the confluence situation of tributaries in different intervals, the interval flow is calculated by utilizing an iterative method, including initially assuming that the tributary flow is zero, simulating non-tributary outflow by using a one-dimensional river hydrodynamic numerical model, determining the difference between the simulated non-tributary outflow and actual site flow measurement, and adjusting the tributary flow; and iteration is repeated until the error between the simulated outlet flow and the actual outlet flow reaches the preset precision. By constructing a one-dimensional river water power numerical model based on a Runge-Kutta time discrete shallow water equation set, high-precision simulation of river water flow calculation under the condition of branch flow convergence in different intervals is realized.

The invention belongs to the technical field of sensor calibration, and particularly discloses a data center sensor fault calibration iteration method based on Bayesian space reconstruction, and the method comprises the steps: carrying out the fitting of the data of a target system, obtaining a first regression function, carrying out the fitting of the data of the target system which does not comprise a to-be-calibrated sensor, and obtaining a second regression function; obtaining a second regression function; constructing a calibration model based on the first regression function and the second regression function; calculating posterior distribution based on the calibration model to obtain a compensation value of the sensor to be calibrated; calibrating the sensor to be calibrated based on the compensation value; and acquiring real-time data of the target system, and adjusting the compensation value based on the real-time data. The method can improve the calibration precision and efficiency.

The present application relates to the technical field of chemical process digital twinning, and discloses a physical property mixing solving method, device, equipment and medium applied to digital twinning, comprising: obtaining physical property data of a digital twinning system; establishing a state equation and a state equation coefficient corresponding to the digital twinning system according to a mixing rule and the physical property data; calculating a discriminant by using the state equation coefficient, and determining that the state equation has three real number solutions or a single real number solution by using the discriminant; when the state equation has three real number solutions, calculating a compression factor of a target phase state by using an analytical method; when the state equation has a single real number solution, calculating the compression factor of the target phase state by using an iterative method; and simulating and optimizing the digital twinning system by using the compression factor to obtain an optimized target digital twinning system. The present application improves the solving speed of the state equation on the basis of meeting the robustness requirement of state equation solving, and significantly improves the overall performance of the calculation speed of the chemical process digital twinning system.

The present invention discloses a method for effectively disassembling a nuclear magnetic resonance relaxation time spectrum, comprising the following steps: S1, constructing a probability density function of pores and caves according to the distribution characteristics of pores and caves in a core nuclear magnetic resonance T2 spectrum; S2, setting the sum of the nuclear magnetic spectrum areas to 1, randomly generating n data points within the interval of pore distribution, and dividing all the data points into multiple data sets by screening peak values; S3, calculating a likelihood function; S4, calculating a priori probability that each data point belongs to a pore or a cave; S5, updating various parameters in an iterative method using the priori probability; and S6, calculating a new logarithmic likelihood based on the updated parameters, and updating the expected E in the iterative method. p and E v , expected E p and E v Repeat steps S2 to S5 until the convergence condition is met and the iteration is terminated. The present invention combines nuclear magnetic resonance testing with an iterative method to decompose the nuclear magnetic resonance spectrum, thereby improving the accuracy of the spectral shape distribution.

This invention discloses a calculation process and speed-up method for remote coordinated adjustment of various power electronic devices, including the following steps: 1) acquiring input power system data and establishing physical models of various power electronic devices; 2) calculating a modular local sensitivity matrix based on the physical models of the power electronic devices; 3) calculating the target physical quantity y; 4) obtaining the minimum change Δu of the control parameters of the power electronic devices during the k-th alternating iteration through pseudo-inverse calculation based on the modular local sensitivity matrix and the target physical quantity y. (k) and update the control parameter u (k+1) =u (k) +Δu (k) 4) Determine whether the active power of the tie line and the alternating iterative power flow both satisfy the convergence criterion at the k-th iteration. If so, output the control parameters of the power electronic equipment; otherwise, return to step 2). This invention can reuse the calculation results of the alternating iterative method and directly obtain the local sensitivity calculation, thus improving the solution efficiency of the remote coordinated adjustment strategy.

The present invention discloses a method for determining the equivalent pretension of cables. The method is based on nonlinear implicit equation construction and the Steffensen iteration method. Under the condition that the structural load and support state are known, the cable force value under the load state is targeted. Considering geometric nonlinear effects, the problem of determining the equivalent pretension of cables is transformed into the problem of solving multiple relatively independent nonlinear implicit equations. An iterative formula for the equivalent pretension is constructed based on the principle of the Steffensen iteration method. A set of equivalent pretensions of cables with a cable force error within an allowable error range is obtained through cyclic iterative solutions. This method has a small number of iterations, a short solution time, and has a convergence efficiency of second order or higher, high applicability, outstanding computational efficiency, and stability. It is widely applicable to the problem of determining the equivalent pretension of cables in various prestressed structures.

The application belongs to the field of gear transmission system squeeze film damper damping, especially relates to a kind of gear squeeze film damper damping quick calculation method and system, obtains the structural parameter of squeeze film damper, carries out velocity calculation and constructs the Reynolds equation of squeeze film damper oil film pressure;Based on half-step center finite difference method, the Reynolds equation is solved, and the oil film distribution pressure of oil film damper is obtained;Based on oil film distribution pressure, the oil film counterforce of oil film damper is calculated using double integral algorithm.Compared with the classical short bearing approximate solution and long bearing approximate solution, its use range is wide, and compared with super relaxation iteration method, its calculation efficiency is high.Make it can be used in gear dynamics model to carry out damping analysis.When solving fluid Reynolds equation by finite difference method, only the working condition with regular boundary condition can be processed.Based on variational principle and Galerkin method, a new more general finite element method is proposed to calculate the oil film counterforce of SFD.

This invention discloses a method and apparatus for calculating the three-phase asymmetrical short-circuit current in a distribution network considering photovoltaic (PV) power. The method includes: before a fault, using power flow calculations to obtain the node voltage and injected current of each node, including the PV node, during normal operation; equating the power source to a current source and the load to an impedance based on Norton's equivalent; calculating the admittance matrix based on an equivalent circuit model after a three-phase asymmetrical short-circuit fault; and constructing a network equation for the PV short-circuit calculation node impedance suitable for Gaussian iteration; simultaneously establishing nonlinear piecewise expressions for the voltage and current of the renewable energy node; and solving for the current and voltage during a renewable energy fault using an iterative method to obtain the fault short-circuit current. By constructing the admittance matrix and corresponding voltage and current expressions for single-phase-to-ground short circuits and two-phase-to-phase short circuits, and using iterative calculations to derive the final result, the accuracy of the calculation is improved.

This invention discloses a method for calculating the flow rate of a single compressor in a continuous wind tunnel parallel compressor system, relating to the field of supersonic wind tunnel operation and commissioning. The invention uses the mass flow rate of the wind tunnel nozzle as a benchmark for the total flow rate; pre-determines the constant-speed total pressure ratio performance curves of each individual compressor and parameterizes them into a continuous constant-speed total pressure ratio performance mathematical model; during wind tunnel operation, the rotational speed and total pressure ratio of each compressor are measured in real time, and the reduced flow rate is obtained by solving inverse functions or using iterative methods. The initial mass flow rate of each compressor is calculated by combining the inlet total pressure and inlet total temperature; finally, corrections are made based on the deviation between the nozzle mass flow rate and the sum of the initial mass flow rates of each compressor to obtain the actual mass flow rate of each compressor. This achieves accurate determination of the flow rate of each individual compressor in parallel operation, providing a guarantee for the establishment of the target flow field and operational safety in the wind tunnel test section.

The application discloses a kind of generation binary space constraint X-ray coherent diffraction image recovery method.This application is used to realize from the coherent X-ray diffraction image of acquisition recovery out sample image to be measured, using the method of deep learning with good predictive ability to generate corresponding space constraint support to X-ray coherent diffraction image, then it is carried out HIO phase iteration, the application can make up the condition that space constraint is not accurate in traditional HIO iterative method, and then can be more quickly converged, higher quality is recovered;Compared with directly using deep learning image recovery method, the result of the application is more accurate, there is no pixel error situation, can realize through small amount of iteration recovery better result, improve the robustness of X-ray diffraction image recovery.

The invention discloses a power distribution network and user oriented energy storage cooperation configuration optimization method and a storage medium. The method comprises the following steps: establishing a cooperation energy storage system model comprising power distribution network side energy storage and user side energy storage serving multiple users; constructing a target function with the minimum sum of the cost of the collaborative energy storage system, the network loss cost of the power distribution network and the energy consumption cost of the user as a target, and setting an operation constraint of the collaborative energy storage system, a power flow safety constraint of the power distribution network and a power balance constraint of the user; and solving the target function and the constraint condition by adopting an iterative method embedded mixed integer linear programming method to obtain the optimal configuration capacity of the energy storage of the power distribution network side and the user side and the optimal access point scheme of the energy storage of the power distribution network side. The operation performance of the power distribution network can be improved, and the energy storage configuration of the power distribution network and the user side is optimized.

The invention discloses a multi-source data adaptive fitting method for a liquid hydrogen storage tank bench test, which comprises the following steps: synchronously acquiring multi-source sensor data in the liquid hydrogen storage tank bench test in real time, and preprocessing the data to obtain preprocessed real-time data; establishing a physical priori constraint equation based on a low-temperature thermodynamic law and a heat transfer mechanism, embedding the physical priori constraint equation into a data fitting objective function, performing physical constraint, and determining energy conservation, phase equilibrium and heat transfer boundary conditions required to be met by a fitting result; extracting data features of the preprocessed real-time data, matching the data features with a preset working condition feature library, and performing working condition identification to obtain a current test working condition identifier; adjusting regularization parameters by adopting an iteration method according to the current test working condition identifier, the data fitting residual error and the noise level; and carrying out data fitting by combining physical constraints, current test working condition identifiers and the adjusted regularization parameters, and inverting the state parameters in the storage tank. The algorithm can provide a reliable basis for design optimization and safety evaluation of the liquid hydrogen storage tank.