173 results about "Response analysis" patented technology

The invention relates to the field of bridge structure dynamic response analysis, and discloses a windmill bridge coupling response analysis method. According to the method, wind speed, wind direction and vehicle speed data are collected, and a data set is constructed by combining finite element and CFD coupling numerical simulation; a parallel encoder is adopted to fuse Transform feature extraction and LSTM time sequence processing to generate a hybrid prediction response; constructing a physical constraint and composite loss function based on a train-bridge motion equation, and optimizing neural network parameters through a subtraction average strategy; and finally, predicting dynamic response through forward propagation and verifying physical consistency to form a model optimization closed loop. According to the method, a deep learning method and physical equation constraints are fused, the analysis precision and calculation efficiency of windmill bridge coupling response are remarkably improved, and a more reliable dynamic evaluation means is provided for bridge wind resistance design.

The invention relates to the field of water quality monitoring analysis, in particular to a multi-modal water quality monitoring data intelligent processing method and system. The method comprises the following steps: obtaining a water quality monitoring parameter stream and a water quality monitoring image, and carrying out adaptive processing to obtain a filtering optimization parameter stream and an optimization monitoring image; performing water quality state evolution perception according to the adaptive filtering optimization parameter flow, and constructing a water quality state evolution graph; and performing biological index response analysis and water quality ecological influence evaluation based on the water quality state trend evolution graph to obtain a water quality evaluation report. And carrying out pollutant spatial distribution change analysis based on the optimized monitoring image, and executing final water quality monitoring evaluation according to a water quality evaluation report. The invention provides efficient and accurate water quality status analysis.

The invention discloses a multi-dimensional natural resource intelligent monitoring method and system based on big data analysis, and relates to the technical field of resource monitoring, and the method comprises the steps: calculating the information sharing degree between different data streams, constructing an abnormal feature credibility distribution map, and carrying out the calculation of the abnormal feature credibility distribution map; and inputting the abnormal feature credibility distribution graph and the multi-source auxiliary information into an integrated classifier, carrying out joint analysis and comprehensive research and judgment on multi-dimensional information to output a target list, constructing an event response relation graph reflecting a monitoring task priority and an execution logic relation according to the attribute features of each element in the target list, and carrying out event response analysis on the monitoring task priority and the execution logic relation. Wherein each node represents a to-be-monitored target, an edge represents a dependency relationship between tasks, and an optimal monitoring execution path is planned for various intelligent monitoring carriers by using an improved A algorithm integrated with a multi-factor cost function. Through natural resource monitoring of multi-modal data interference correction, intelligent classification and path optimization and dynamic response, the monitoring quality and the execution efficiency are effectively improved.

The invention discloses a rapid calculation method based on a non-coordination and reanalysis theory and a computer device. The invention relates to the technical field of structural design optimization, and solves the problem that it is difficult to realize efficient structural response analysis while ensuring the calculation precision in the prior art. The method comprises the following steps: selecting a structural member of a to-be-calculated structural response and discretizing the structural member; preprocessing the data, and determining a coarse and fine grid index set corresponding to interface fine grid nodes; solving a unit shape function, and embedding the shape function into a body stiffness matrix according to a degree-of-freedom position to serve as an interface constraint condition; calculating a variable element stiffness matrix, and completing the construction of a modified model stiffness matrix; carrying out iterative calculation to obtain a basis vector; and calculating and solving the structural response of the modified model. According to the method, the efficient response analysis of the non-coordinated variable structure is realized on the premise of ensuring the calculation precision.

The invention discloses a dynamic response regulation and control and vibration reduction system and method for a floating type photovoltaic platform in the technical field of offshore new energy equipment, and aims to improve the anti-wave stability and structural safety of the platform under complex sea conditions. The system comprises a platform main body, a monitoring unit, a response analysis and early warning unit and a regulation and control execution unit, the monitoring unit is arranged on the platform main body and is used for collecting real-time sea condition data; the response analysis and early warning unit is in communication connection with the monitoring unit and is used for performing response analysis on the real-time sea condition data and sending an early warning signal to the regulation and control execution unit when the abnormal working condition of the platform main body is identified; and the regulation and control execution unit is used for carrying out regulation and control and vibration reduction on the platform main body according to the received early warning signal. According to the method, the assembly fatigue can be obviously relieved, the cable damage probability is reduced, the service life of the platform is prolonged, and good engineering adaptability and intelligent expansion potential are achieved.

The invention provides a deep sea temporary platform large-diameter steel casing dynamic response analysis method, and relates to the technical field of deep sea engineering, and the method comprises the steps: building a three-dimensional explicit dynamic coupling model according to the typhoon frequent generation characteristics of a target sea area and steel casing structure parameters; according to the three-dimensional explicit dynamic coupling model, the wave load is decomposed, the vibration hammer load effect, the ocean current load effect and the internal wave current load effect are integrated, and a comprehensive dynamic load set of the steel casing is determined. By establishing a precise model, integrating multi-source loads, identifying a risk area, monitoring stress in real time and optimizing design parameters based on data, self-adaptive matching of steel casing design and a complex marine environment is achieved, the structural safety of the deep sea temporary platform steel casing is effectively improved, and the cost is reduced.

The invention relates to the technical field of data processing, in particular to an engineering geological survey data processing method and system, and the method comprises the following steps: obtaining hole site space positioning and lithologic boundary information, collecting a structure segment sequence, extracting resistance change direction classification disturbance behaviors, recognizing node sequence conflicts, and judging hydrological turning positions. Identifying the corresponding relation between the structural section and the water level track, and generating a structural section water level merging mapping table. According to the method, the spatial information, the lithology identification, the sampling level and the penetration resistance of the drilling structure sections are collected and serialized, disturbance identification and non-sampling section classification are performed based on the resistance change trend between the sections, and node conflicts are identified in combination with the numbering relation and the lithology combination; continuous modeling and classified merging of geological information on the spatial level are achieved, the linkage adaptability of data in a multi-dimensional analysis scene is enhanced, misjudgment interference caused by information isolation is avoided, and dynamic recognition and hydrological response analysis of a geological structure are supported.

The invention discloses a method for constructing an evaluation model for the influence of climate change on biodiversity, and particularly relates to the technical field of ecological modeling and climate response analysis. The method comprises the following steps: generating a high-resolution characteristic grid based on microclimate disturbance data and a remote sensing image, extracting ecological plaques and establishing a heterogeneity spatial index model, constructing a connectivity map and a coupling response path library, extracting a typical species response mode by using nonlinear dimension reduction and spectral clustering, and performing dynamic fitting in combination with biological survey data. And finally, generating a diversity attenuation trend prediction curve and a risk thermodynamic diagram, identifying a biodiversity collapse critical point and outputting an intervention priority, and the method can be widely applied to regional ecological early warning and protection planning.

The invention discloses a rock mass structural surface identification method and system based on adaptive neighborhood and multi-seed-point growth, and relates to the technical field of geotechnical engineering, geological exploration and mining engineering, and the method comprises the steps: carrying out the adaptive non-uniform downsampling of three-dimensional point cloud data based on local feature entropy; retaining key geometric features of the structural surface while compressing the data volume; fusing the normal vector and the local point cloud density to carry out multi-feature classification; an improved region growing algorithm supporting parallel growth of multiple seed points is adopted, and a structural surface is accurately recognized; automatically extracting occurrence, spacing, trace length and roughness parameters of each structural surface; performing full-automatic advantage grouping on the occurrence through a DP-DBSCAN hybrid clustering algorithm; and constructing a three-dimensional discrete fracture network model based on the statistical parameters, and integrating the three-dimensional discrete fracture network model to discrete element software for mechanical response analysis. According to the method, full-process automation of rock mass structural surface recognition is realized, and the processing efficiency, the recognition precision and the engineering practicability are remarkably improved.

The invention relates to the technical field of engineering safety management, and particularly discloses an engineer safety management method and system based on big data, and the method comprises the steps: collecting all data of a construction site in real time; performing space-time alignment and fusion processing on the collected data to generate multi-modal fusion data; training a multi-modal risk assessment model based on the obtained construction big data; performing construction risk feature extraction on the collected data based on the multi-modal risk assessment model, and outputting construction risk features; and performing safety response analysis on the multi-modal fusion data based on the construction risk features, and generating a safety response result. All data of a construction site are fused, and a multi-modal data set is constructed, so that full-dimensional monitoring of the construction site is realized; a big data training model is matched based on construction types, and space-time correlation analysis of risk features is achieved; a differentiated early warning mechanism for personnel, equipment and environment is generated, multi-agent co-processing is supported, and accident loss is reduced.

An emergency response data system (ERDS) integrates an AI agent into an emergency management application to generate emergency response analytics to facilitate operational efficiency of one or more ECCs. The ERDS provides an emergency management application operable by an emergency communications center (ECC) computing system to display an emergency management user interface (UI) at one or more ECC. The ERDS stores, in one or more data structures, historical emergency response analytics. The ERDS receives, with the emergency management UI, user instructions related to the historical emergency response analytics. The ERDS provides the user instructions to the emergency response AI agent. The ERDS generates, with the AI agent, textual or visual representations of the historical emergency response analytics in response to the user instructions. The ERDS displays, with the emergency management UI, the textual or visual representations of the historical emergency response analytics to facilitate operational efficiency of ECCs.

The invention provides a tree wind-induced response evaluation and analysis method, and relates to the technical field of disaster prevention and reduction engineering, and the method comprises the steps: carrying out the construction of a geometric model for a target tree; on the basis of the geometric model, CFD analog simulation is carried out, and wind pressure time history data and crown load data of CFD grid points of the branches under different wind field conditions are obtained; finite element mesh generation is carried out on the geometric model, a finite element model is constructed, and mesh unit types in the model comprise hexahedron units, tetrahedron units and wedge-shaped units; the branch wind pressure time history data and the crown load data are mapped to the surface of a finite element model, structural finite element analysis is carried out, and cloud chart data of stress and displacement of the target tree changing along with time under different wind field conditions are obtained; and carrying out wind-induced response analysis and wind resistance evaluation on the target tree based on the cloud picture data and the wind-induced damage criterion of the tree. According to the technical scheme, a scientific basis can be provided for understanding the response behavior of the target tree under the strong wind condition.

The invention relates to the technical field of component quality control, and discloses a remote component quality control system based on digital twin and wireless communication. A component data acquisition module of the system obtains multi-dimensional data of a to-be-monitored component through a wireless sensor network, and a component identification code is associated to generate a quality basic data set; the regional association analysis module establishes association mapping of adjacent components according to a spatial topological relation to form a quality association partition map; the environmental response evaluation module analyzes the influence degree of environmental factors on the performance of the component and generates an environmental response analysis report; the defect positioning module identifies problem points and constructs a defect distribution map; and the quality early warning module integrates the problem points and the associated parameters, marks the position of the potential safety hazard, and outputs a quality evaluation and risk early warning report. The system realizes remote and comprehensive control of component quality, and assists in timely finding and dealing with quality problems.

The invention provides an intelligent response method and device for dam safety abnormity based on a large text model, and the method comprises the steps: collecting dam monitoring data in real time through an edge calculation node, and carrying out the abnormity detection based on an LSTM-Attention time sequence prediction model and a multi-physics coupling analysis model; generating a standardized text report containing exception description, time, position and associated parameters; the text report serves as input, intelligent response analysis is conducted through a text large model based on LoRA fine tuning, and emergency disposal suggestions conforming to industry specifications are generated; and performing knowledge base matching verification on the emergency disposal suggestions, screening out a high-confidence-coefficient response scheme based on a cosine similarity threshold, and automatically triggering an emergency response process when a dam break risk coefficient is detected to exceed a preset threshold. According to the method, full-process automation of dam safety monitoring from abnormal detection to emergency response can be realized, the response time is remarkably shortened to the minute level, and the early warning accuracy and decision scientificity are improved.

The application discloses an intelligent identification method for dominant seepage channels based on big data, which comprises the following steps: collecting static geological data, dynamic development data and dynamic monitoring data of an oil reservoir and performing data processing; performing data quality analysis on the processed data and establishing a sample database; performing inter-well connectivity analysis and inter-well pressure response analysis in a plane according to the sample database, and identifying dominant channels in the plane; performing interlayer production and absorption law research in a vertical direction according to the sample database, predicting interlayer liquid production and absorption ratios and water cut, and identifying dominant interlayer positions in the vertical direction; and comprehensively identifying dominant seepage channels between each layer of a production well and an injection well based on the identified dominant channels in the plane and the dominant interlayer positions in the vertical direction.

The invention belongs to the field of dam flood discharge safety, and provides a dam flood discharge safety protection method and system based on earthquake response analysis, and the method comprises the steps: S1, obtaining multi-source environment and structure data in real time; s2, preprocessing the multi-source environment and structure data to form a unified time sequence multi-dimensional data set; s3, simulating and analyzing the structural dynamic response of the dam and the flood discharge gate based on the unified time sequence multi-dimensional data set, and evaluating potential damage; s4, comprehensive risk assessment is carried out by combining the earthquake response analysis and damage assessment result, the hydro meteorological data and the flood discharge gate operation state data, and early warning information is generated; s5, generating a dynamically adaptive flood discharge gate opening and closing strategy according to the comprehensive risk assessment result and the early warning information; s6, executing the opening and closing strategy of the flood discharge gate, and monitoring the actual operation state of the flood discharge gate in real time; and carrying out comparative analysis on the actual running state of the flood discharge gate and the prediction strategy, and carrying out updating and optimization according to an analysis result.

The invention discloses a real-time monitoring control system based on a thermal flow sensor and a controller, and relates to the technical field of sensor monitoring. According to the real-time monitoring control system based on the thermal flow sensor and the controller, the method comprises the steps that S1, sensor monitoring data and historical statistical data are preprocessed; s2, lagging and response time dynamic characteristics are extracted; performing modal decomposition, phase estimation, peak calculation and steady-state noise analysis; s3, executing phase compensation, peak value recovery and enhancement compensation judgment; recording a residual sequence and a compensation parameter, and outputting optimized flow data; s4, constructing a credibility interval and dynamic consistency score synthesis control credibility mark; and executing security constraint and prediction filtering and archiving. The problems that an existing thermal flow sensor generates obvious phase lag and peak smoothing distortion due to the influence of thermal diffusion thermal inertia under the rapid fluctuation and pulsation working conditions, and the real-time monitoring precision and the closed-loop control stability are difficult to guarantee due to the lack of an online dynamic response analysis and compensation mechanism are solved.

The invention discloses a building construction quality optimization method and system based on a large-span transfer beam, and relates to the technical field of building structure intelligent construction quality control, and the method comprises the steps: collecting multi-source engineering data, constructing a unified data standard, and carrying out the multi-working-condition disturbance modeling through combining a simulation platform; importing a finite element system for dynamic structure response analysis and outputting a response risk map; mapping the response variable to a multi-factor coupled bearing capacity function, and outputting a load limit which can be actually and stably borne by the template system; and constructing an on-site real-time monitoring network, performing linkage comparison on monitoring data and a multi-working-condition disturbance modeling result, and driving response verification, maintenance strategy adjustment and demolding node management and control. According to the method, a construction quality optimization mechanism with disturbance modeling, bearing capacity evaluation and real-time monitoring as the core is constructed, and risk prediction, response regulation and control and quality closed-loop control of the whole construction process of the large-span transfer beam are achieved.

The invention relates to the field of vulnerability evaluation of extreme rainfall induced mass landslide, in particular to an extreme rainfall mass landslide vulnerability evaluation method fusing diffusion generation and interpretable learning, which comprises the following steps: firstly, constructing a multi-dimensional factor data set, and realizing rasterization preprocessing; secondly, establishing a feature response analysis module, identifying main control factors of landslide occurrence and eliminating redundant variables; then, a denoising diffusion probability model is introduced, and an enhanced balance sample library is constructed; then, carrying out landslide probability prediction based on a multi-algorithm fusion integrated discrimination model, and outputting a grid-level landslide occurrence probability; and finally, minimizing intra-class variance and maximizing inter-class variance by using a natural breakpoint method, determining an optimal grading threshold set, and realizing landslide susceptibility grade division and spatial mapping output. Under the extreme rainfall condition, the method can effectively characterize the susceptibility zoning influence of the mass-occurring landslide flow slip catastrophe process, and achieves high-precision landslide susceptibility evaluation.

A method for selecting near-source strong motion records considering fling-step effects includes the following steps: introducing a permanent displacement as a conditional parameter into ground motion selection based on generalized conditional intensity measures, and giving a target permanent displacement by extended probabilistic fault displacement hazard analysis; characterizing a frequency content component of a ground motion with a spectral displacement instead of spectral acceleration in a target ground motion intensity measure set; further calculating an empirical correlation coefficient suitable for near-source strong motion records with permanent displacement, constructing a corresponding target conditional distribution, and finally obtaining a data set of near-source strong motion records with permanent displacement most consistent with a target conditional distribution by optimizing selection from a near-source strong motion database. A reasonable ground motion selection method is provided for seismic response analysis of near-source engineering structures under a strong motion-fault dislocation coupled effect.

The invention discloses a meteorological risk analysis early warning system based on meteorological data, and relates to the technical field of meteorological perception early warning, the meteorological data and structure operation data of an area where a power transmission tower is located are collected, wind direction abrupt change feature recognition is carried out to obtain a wind direction abrupt change rate V theta, a sand and dust invasion change index Esant is constructed, and the wind direction abrupt change rate V theta is obtained; the method comprises the following steps: performing sand-dust invasion state evaluation on a sand-dust invasion judgment threshold Ethresh, performing sand-dust impact response analysis when the sand-dust invasion judgment threshold Ethresh is evaluated as a sand-dust impact period, constructing an instantaneous shear wind pressure stress sigma sh, further obtaining a foundation erosion response coefficient Rfd in combination with a sand-dust invasion change index Esant, and performing coupling modeling on the instantaneous shear wind pressure stress sigma sh and the foundation erosion response coefficient Rfd to obtain a foundation erosion response coefficient Rfd. And the structural fatigue rate PLfat is obtained to evaluate the structural safety state of the power transmission tower, so that the response sensitivity of the early warning system to high-frequency sand and dust disturbance is improved, and safe and stable operation of power transmission facilities under extreme weather conditions is ensured.

The invention discloses an electric meter box temperature control system based on environmental perception, and relates to the technical field of electric meter box temperature control, and the system comprises a position parameter collection module which is used for obtaining static structural parameter information representing an actual fixed installation scene after an electric meter box is installed, constructing a position parameter set representing the long-term operation environment of the target electric meter box; and the environment response module is used for establishing an environment adaptation model corresponding to the temperature change rule of the electric meter box based on the position parameter set and real-time operation data acquired in a data acquisition stage required for completing initialization of the environment adaptation model. According to the invention, through fusion of position parameter modeling, environmental response analysis, temperature rise trend monitoring, dynamic temperature control strategy setting and resource allocation management, intelligent thermal management of the electric meter box in a complex operation environment is realized.

The invention discloses a traffic risk analysis method and system based on multi-source perception data, and relates to the technical field of traffic risk management. The traffic risk analysis method based on the multi-source perception data comprises the following steps of performing noise interference optimization judgment; quantifying the timeliness of traffic risk capture; traffic conflict probability prediction; and carrying out traffic risk decision response analysis. According to the method, whether noise interference optimization is carried out or not is judged through the obtained high-frequency signal amplitude, whether timeliness optimization is carried out or not is judged based on the obtained capture timeliness quantification result, and when the timeliness is qualified, whether interaction parameter step length optimization is carried out or not is judged based on the predicted traffic conflict probability; meanwhile, whether decision response optimization is carried out or not is judged based on the decision response analysis result, and the effect of improving the accuracy of dynamic traffic jam risk assessment in the road transformation area in the urban road transformation process is achieved; the problem that the accuracy of dynamic traffic jam risk assessment is not high in the urban road transformation process in the prior art is solved.

The invention relates to a data processing technology, and provides a mass distribution network industrial resource collaboration method based on load interaction and response analysis, which comprises the following steps: firstly, constructing a real-time synchronous data acquisition and processing system, and fusing multi-source data to form a unified data base; secondly, realizing flexible dynamic identification through mechanism modeling and data driving, and introducing a flexible label to quantify adjustable power, duration and response rate; constructing an interactive network based on the flexibility label, depicting a space-time coupling effect and group response characteristics, and generating an equipment, station and region level scheduling scheme through a multi-target hierarchical optimization model in combination with market electricity price and renewable output prediction; and finally, comparing the plan with the actual response in the actual scene, and performing correction. According to the invention, the cooperative scheduling and fine management capability of the power distribution network on massive industrial loads can be improved, the flexible utilization level is improved, and the economical efficiency and robustness of the system are enhanced.

The invention provides a chemical accident emergency response method and system under real-time monitoring, and relates to the technical field of emergency response, and the method comprises the steps: carrying out the time alignment through collecting multi-source heterogeneous data in real time, and generating multi-source synchronous data; extracting multi-modal features of the multi-source synchronous data to carry out chemical accident identification; accident scene parameters are called, accident response analysis is carried out based on an accident identification result, an emergency response scheme is formulated, resource scheduling analysis is carried out, and a resource scheduling network diagram is constructed; and performing accident monitoring and early warning according to the resource scheduling network diagram in combination with the multi-source synchronous data, generating a real-time decision instruction, and pushing the real-time decision instruction and an emergency response scheme to an emergency command center. According to the method and the device, the technical problems of low chemical accident identification accuracy and response flow lag caused by lack of a multi-source heterogeneous data fusion and real-time linkage mechanism in the prior art are solved, and the technical effects of improving the chemical accident identification precision and the emergency response speed are achieved.

The embodiment of the invention relates to the technical field of offshore wind power, and provides a three-dimensional dynamic response analysis system and method for an offshore wind turbine single pile foundation, and the system comprises an input data collection module which is used for collecting multi-physical field input data of a target site; the three-dimensional dynamic model modeling module is used for modeling to obtain a finite element model; the multi-source load calculation and application module is used for mapping a multi-source load to a specified node of the finite element model according to a node concentrated force or acceleration form; the dynamic response analysis module is used for performing time-history dynamic response analysis and outputting response data of the single pile foundation structure and the soil body; wherein the finite element model is obtained through modeling based on a substructure method, a preset hardened soil constitutive model is embedded in the finite element model, and the finite element model is in butt joint with the three-dimensional erosion pit geometric model. The embodiment of the invention is suitable for dynamic response analysis of a large-diameter single pile foundation under the action of complex load and scouring, and is beneficial to dynamic response analysis in a complex marine environment.

The invention discloses a description language tool for a protocol fuzz test, and the tool comprises a PDL module which is used for defining a protocol message structure, a session state, and association between fields; the analysis module is used for analyzing the PDL definition into an intermediate representation; the fuzzy test engine is used for generating a use case by adopting a three-stage coding assembly line according to the intermediate representation and the session context; and the execution module is used for sending the use case and receiving the response. The PDL of the tool supports bit-level precision, a composite structure and an inheritance mechanism, a semantic perception variator is arranged in the fuzzy test engine, and consistency of use case generation and response analysis is achieved through single-definition bidirectional semantics. Accurate modeling and dynamic simulation of a complex protocol are realized through a unified description language, and the efficiency, the coverage rate and the maintainability of fuzzy testing are remarkably improved.

The application relates to the field of extreme rainfall-induced group landslide susceptibility evaluation, in particular to an extreme rainfall group landslide susceptibility evaluation method fusing diffusion generation and explainable learning, which comprises the following steps: firstly, a multidimensional factor dataset is constructed to realize grid pretreatment; secondly, a feature response analysis module is established to identify main control factors of landslide occurrence and remove redundant variables; then, a denoising diffusion probability model is introduced to construct an enhanced balanced sample library; next, a landslide probability prediction is carried out based on an integrated discriminant model of multi-algorithm fusion, and a grid-level landslide occurrence probability is output; finally, the natural breakpoint method is used to minimize intra-class variance and maximize inter-class variance, so that an optimal grading threshold set is determined, and landslide susceptibility grading and spatial mapping output are realized. Under the condition of extreme rainfall, the application can effectively represent the susceptibility partition influence of group landslide flow slide catastrophe process and realize high-precision landslide susceptibility evaluation.

The application provides a communication feature model driven relay protection device automatic test method and system, comprising the following steps: 1. Through active detection and response analysis, the communication protocol type, message format and function code mapping relationship of the relay protection device are identified, and a device communication feature model is constructed; 2. Based on the device communication feature model, test cases covering function verification, abnormal processing and boundary conditions are dynamically generated, and automatic mapping of the test cases and the device and execution sequence optimization are completed. The technical scheme can solve the problems of relay protection device test dependence on manual configuration, low efficiency and poor adaptability.

This invention provides a peak-scale response analysis method based on nested sub-basin division. By constructing a nested sub-basin structure controlled by area thresholds, and based on a unified design storm conditions and hydrological model parameter system, the method calculates peak discharge under different scale conditions by only changing the sub-basin division scale. It also establishes a logarithmic decay function model between peak discharge and the number of sub-basin units, achieving a quantitative expression of peak-scale response. Furthermore, by comparing and analyzing the scale decay coefficients under different design frequencies, the method quantifies the sensitivity of peak discharge to changes in the division scale. This method forms a complete technical process from data acquisition, structure construction, control variable setting, model running to function modeling and sensitivity analysis. It features a clear logical closed loop, strong repeatability, and good generalization, and does not depend on specific hydrological model software or specific watershed conditions. Under the premise of meeting the unified storm input and nested division principles, it can be widely applied.