20 results about "Critical parameter" patented technology

The invention belongs to the technical field of metal plate processing and testing, and particularly discloses a device and method for testing the bending forming capacity of a metal composite plate. The device comprises a test base, a movable heating mechanism which slides and can be locked on the test base, a bending test mechanism rotationally connected to the test base, a fixed hydraulic mechanism, a first driving motor and a second driving motor, a heating element is arranged in the movable heating mechanism, so that the plates can be uniformly heated on line; the bending test mechanism controls the clamping force and the bending angle of the bearing through a servo motor in a closed-loop manner, and collects pressure and angular displacement data in real time; and the hydraulic telescopic head of the fixed hydraulic mechanism executes reverse pushing after single bending, so that a fatigue cycle test is realized. According to the invention, normal-temperature / thermal-state multi-angle bending and fatigue testing can be carried out on metal composite plates with different specifications, the forming limit and layering failure critical parameters are rapidly obtained, and the process optimization efficiency and the product reliability are improved.

The invention belongs to the technical field of servo drive control, and provides a multi-source heterogeneous data fusion servo driver adaptive optimization method, which comprises the following steps: dividing working condition groups by clustering multi-dimensional working condition features, determining a reference interval of each working condition group, positioning a current working condition, identifying unqualified parameters, and determining a reference interval of each working condition group; key parameters are screened through the fault influence indexes, mismatch indexes are calculated according to the adaptive optimization parameter library and the proportion of unqualified parameters in the key parameters, whether the mismatch phenomenon exists between the parameter library and the current working condition or not is judged, and if yes, the mismatch index is calculated; the optimization priority of the unqualified parameters is determined according to the fault influence index and the deviation between the adaptive interval and the reference interval, the unqualified parameters are adjusted in stages according to the priority, dynamic optimization of the parameter library is finally achieved, the problems that in traditional adaptive optimization, the parameter interval is too wide and the like are solved, and the optimization efficiency is improved. And the self-adaptive capability and the operation reliability of the servo driver under complex working conditions are improved.

The invention discloses a device and method for determining the opening degree of a critical fracture capable of being injected with slurry, the device integrates high-precision mechanical driving, fracture model customization and real-time dynamic observation functions, and precise and continuous adjustment of the fracture opening degree is achieved through continuous propulsion of a stepping motor. The device is based on a transparent fracture model structure which is narrow inside and expanded outside during deformation, the seepage resistance of slurry is reduced, and visual observation of seepage and diffusion processes of the slurry in fractures is supported; in the test, the grouting pressure and the fracture opening degree change are synchronously monitored, and when the grouting pressure is sharply increased, the corresponding opening degree is the critical fracture opening degree, so that the integrated test from fracture opening degree regulation and control, visible slurry migration to quantitative analysis of critical parameters is realized. The device is simple in structure and convenient to operate, and an effective means is provided for groutability evaluation and process optimization of geotechnical engineering grouting materials.

The invention discloses an adversarial training method and device based on criticality perception fine tuning, and the method comprises the steps: for each to-be-trained parameter, comparing the robust performance difference between the current value of the parameter and the optimal value of an adversarial sample, initializing the robust criticality of each parameter according to the criticality degree, and obtaining the criticality of each parameter; obtaining an initial criticality score; for each parameter, calculating a gradient of the adversarial loss with respect to the parameter; iteratively updating the robust criticality of the parameter in combination with the initial criticality score and gradient of the parameter to obtain an updated criticality score; for a high-key module, bottleneck Adapter parameters are added in parallel, and for a low-key module, the parameters are kept frozen; and only updating Adapter parameters of a high-key module by using a robust fine tuning loss function, and freezing parameters of a low-key module. According to the scheme, only a small number of key parameters are finely adjusted, and the total calculation amount and video memory occupation are greatly reduced in the training process.

This application relates to the field of vehicle testing technology, specifically a method and device for determining critical parameters in vehicle slope rollover tests. The method includes: collecting a set of test data from actual vehicle rollovers and dividing it into subsets according to vehicle type; inputting vehicle parameters and test parameters into a forward discriminant model to train the model; calculating a basic inverse model from the forward discriminant model, adding constraints to the output of the basic inverse model, and correcting the basic inverse model using the vehicle parameters and test parameters of the vehicle to be solved; inputting the rollover result into the basic inverse model to obtain an angle range, and filtering test data within the angle range; returning to the operation of training the forward discriminant model until a cutoff condition is met to obtain the target angle range; and finally verifying the rollover critical angle value from the target angle range through actual vehicle angle gradient tests. This application achieves accurate inverse solving from rollover results to test parameters.

The present invention is a system and method for controlling an aviation or road vehicle to optimize performance, where the system can modify flight and drive parameters in real-time to ensure the vehicle can travel from a starting location to a destination location effectively. The system and method monitors and controls parameters of an aircraft or road vehicle and makes calculations that include a baseline-parameter set, a payload-parameter set, and route-parameter set. The system includes sensors coupled with a computer application. The application quantifies each set of data to reach a defined parameter set, further calculating more specific, “critical” parameter sets which recommend an optimized plan to achieve a mission goal. A mission goal might be derived from a critical parameter set.

The invention discloses a critical parameter prediction method, a readable storage medium and a device, and belongs to the technical field of nuclear systems, and the prediction method comprises the steps: determining a to-be-predicted new nuclear system and a calculated value of an existing critical experiment; calculating sensitivity vectors of the new nuclear system and the critical experiments to the nuclear data; on the basis of the calculated value and the sensitivity vector, in combination with the relationship between the experimental value of the existing experiment, the experimental uncertainty and the critical experimental coefficient, constructing a calculation formula of the critical parameter predicted value and the predicted uncertainty of the new nuclear system; solving a coefficient of a critical experiment enabling the uncertainty of the prediction parameters to be minimum; and substituting the coefficient into the two calculation formulas to obtain a predicted value and the uncertainty thereof. The method is stored in the readable storage medium. The device comprises a terminal program for executing the steps of the method. According to the method, the information of a plurality of critical experiments can be effectively integrated, the critical parameters can be more reliably and accurately predicted under the condition of lack of very similar critical experiments, and the uncertainty of the prediction parameters can be more effectively compressed.

Method and system for managing critical parameters of assembly of pressure boundary bolted flanged joints (1 ) having a gasket (9) between sealing surfaces (11,12) of flanges (2,3). Bolt load, applied load, turn of nut or bolt head, joint misalignment and flange gap closure can be monitored and controlled concurrently during assembly to indicate if joint assembly is unacceptable and / or whether assembly / component requires rectification. A field control unit (23) has a portable electronic processor (21 ) and a data acquisition and control unit (22), including a load cell test sensor (24) enabling pre-assembly of the joint or bolts (4,5) for on-site testing of applied bolt load by using the load cell test sensor (24) to verify bolt load achieved. Automatically guiding joint assembly can improve safety and efficiency of joint assembly and also joint reliability..

The invention relates to the technical field of information security, in particular to an intensive platform construction method for information security management, which comprises the following steps of: calculating a ratio of a flow peak value to a defense upper limit, comparing with a preset critical parameter to quantify a defense effect level and generate a state identifier; calling a corresponding cleaning strategy according to the defense effect level, calculating a change rate of a flow peak value after cleaning so as to adjust parameters in the cleaning strategy, obtaining a leakage risk value based on a total weighted exposure risk value, an encryption coverage rate and access control intensity analysis, delimiting a risk level to which the leakage risk value belongs, obtaining a data leakage risk index, and obtaining a data leakage risk index. A full-link automatic defense system of'monitoring-evaluation-response-optimization 'is formed from flow cleaning, risk analysis and strategy adjustment, and defense efficiency and real-time performance are improved.

The invention belongs to the technical field of power system stability control, and particularly discloses an optimization method for ultralow frequency oscillation damping characteristics of a one-pipe double-machine type pumped storage power station. The method comprises the following steps: firstly, constructing a kinetic model of the one-pipe double-machine pumped storage power station; analyzing the stability of the model by using Hopf bifurcation, and determining critical parameters and dividing a stability domain through a Jacobian matrix eigenvalue; introducing a stability margin to quantify the stability, and analyzing a first influence of different working condition points on the oscillation frequency and the damping ratio under the same stability margin; obtaining a second influence of the parameter on the oscillation frequency and the damping ratio through sensitivity analysis; and constructing a three-dimensional curved surface of the oscillation frequency, the damping ratio and the control parameters based on the two influences, dividing an equal-frequency area and an equal-damping-ratio area on the three-dimensional curved surface under the stable allowance working condition, and identifying the optimal control parameters from the equal-frequency area and the equal-damping-ratio area. Optimized identification of the key parameters is realized, and support and guidance are provided for suppressing ultra-low frequency oscillation of the pumped storage power station and improving safe and stable operation of the system.

The present application relates to the technical field of information security, in particular to a method for constructing an intensive platform for information security management, the present application calculates the ratio of traffic peak value and defense upper limit, compares the ratio with the preset critical parameter to quantify the defense effect level, generates a state identifier, calls the corresponding cleaning strategy according to the defense effect level, calculates the change rate of the traffic peak value after cleaning, adjusts the parameters in the cleaning strategy, analyzes the leakage risk value based on the total weighted exposure risk value, encryption coverage and access control strength, divides the risk level to which the leakage risk value belongs, and obtains the data leakage risk index. From traffic cleaning to risk analysis to strategy adjustment, a full-link automatic defense system of "monitoring-evaluation-response-optimization" is formed, and the defense efficiency and real-time performance are improved.

The present invention relates to the technical field of hollow silica microsphere preparation, and discloses a method for optimizing hollow silica microsphere preparation parameters based on flow field simulation. The method first plans the optimization process based on target physical property parameters and preparation conditions, specifies the reactor flow field distribution simulation, obtains microsphere morphology data for different parameter combinations, and determines parameter combination types such as high temperature, specific physical properties, and general physical properties. The method then generates a parameter optimization process set and execution sequence, and generates a list of simulation inputs and experimental configurations for each parameter combination, which are linked to form a complete solution. The method also includes determining parameter optimization boundaries, extracting optimized data subsets, and implementing targeted adjustments, corrections, and stabilization strategies for high-efficiency, low-efficiency, and critical parameter combinations. The method also includes a real-time data update process, experimental rules (dynamic adjustment of the number of experiments, triggering supplementary experiments, and equipment calibration compensation), and database management and analysis. The method improves optimization efficiency and preparation stability and is suitable for industrial production.

The invention relates to the technical field of spring production automation control, in particular to a control method for a spring production line, which comprises a production data acquisition step, a working parameter self-adaptive adjustment step, a finished product detection step and a postpartum model updating step. Various technological parameters are collected in real time through the distributed sensor set, all key parameters in the spring production process can be comprehensively and completely collected, the production precision is guaranteed, and the control precision and the production stability of a spring production line are remarkably improved based on dynamic adjustment of a preset quality model and a self-adaptive PID algorithm; the defective rate caused by process fluctuation is reduced, and meanwhile, the rapid switching requirements of springs of different specifications are met; after a product is manufactured, a detection link is introduced and is automatically compared with a standard model, so that the optimization of the detection link is facilitated, a correction instruction is generated according to a detection result after each detection is completed, manual correction is not needed, the labor cost is reduced, seamless conversion of different spring type production lines is realized, and the production efficiency is remarkably improved.

The invention relates to the technical field of detection. The invention discloses a valve sealing performance detection method, which comprises the following steps: determining the type of a valve, and synchronously collecting key parameters influencing sealing; adopting an actual working condition medium, and obtaining static data through a leakage point and leakage amount detected by equipment; performing laser scanning on the sealing surface to obtain a three-dimensional point cloud and constructing a mathematical model; dynamic data such as leakage trend and critical state are obtained based on model dynamic simulation; performing quantitative scoring according to industry standards in combination with static and dynamic data, and calculating a comprehensive performance index; and finally, original data, results and the like are integrated to form a complete detection report. Static detection and dynamic simulation are fused, sealing surface defects and material aging are captured, leakage trends under different working conditions are predicted, and current performance and long-term attenuation risks are covered. Through detection and optimization of a closed loop, defect positioning is associated with a production process, technological parameters such as tool precision and a material formula are adjusted in a targeted manner, batch defects are solved, and the product percent of pass and consistency are improved.

The invention relates to the technical field of oil-gas field development and gas storage safety management, and discloses a gas storage integrated erosion prevention and control prediction method, which comprises the following steps: S1, establishing a production system analysis model taking a well bottom as a solution node, including an inflow part from a stratum to the well bottom and an outflow part from a separator to the well bottom; s2, obtaining a dynamic curve of an inflow part based on the flow provided by the stratum under different bottomhole flow pressures; s3, on the basis of the pressure distribution of the outflow part from the separator to the well bottom, the well bottom flowing pressure corresponding to each flow is obtained, and therefore a dynamic curve of the outflow part is obtained; s4, calculating at least one critical parameter of the production system; s5, coupling the inflow dynamic curve and the outflow dynamic curve; and S6, based on the inflow and outflow dynamic curve, the system working point and the critical parameters, a gas production capacity chart for guiding safe peak regulation and productivity optimization of the gas storage is drawn.

The invention discloses an electric vehicle stability determination method based on tire side deviation characteristics and a phase plane, and belongs to the technical field of vehicle stability determination, and the method comprises the steps: S1, building a basic simulation model, including simulation model building and configuration of an information acquisition module; s2, phase plane construction and preliminary partitioning are carried out; according to the electric vehicle stability judgment method based on the tire side deviation characteristics and the phase plane, vehicle state parameters and a road adhesion coefficient are obtained through multi-model fusion estimation, then a side slip angle-side slip angle speed phase plane is constructed, preliminary partitioning is conducted in combination with a five-characteristic rhombus method, and the stability of the electric vehicle is judged. Critical parameters are solved based on tire lateral deviation characteristics to complete secondary partitioning, and finally, the stability margin is quantified through the distance between a state point and the instability boundary, so that accurate judgment is realized, the limitation of single-phase plane analysis is made up, the instability boundary is accurately quantified, stable region division is refined, and a clear basis is provided for intervention of a control system. And the stability judgment accuracy and robustness under the limiting working condition are improved.

The invention discloses a multi-module cooperative control method and system for an unmanned aerial vehicle electric power inspection system, relates to the technical field of unmanned aerial vehicle electric power inspection, and aims to analyze initial feature vectors of equipment images and sensor data through a machine learning model, intelligently identify equipment types and inspection requirements and dynamically determine a functional module sequence needing to be activated. Afterwards, for the complexity of data transmission between the modules, an inter-module data handover chain based on key parameters such as temperature distribution characteristics is established, and a module switching-in time sequence is generated through a grouping algorithm to realize on-demand activation. When the computing resource load exceeds a threshold, a resource allocation scheme is generated to ensure prioritized execution of key functions. And finally, processing the inspection data through a resource allocation scheme, and generating an inspection analysis result, thereby ensuring that data information among the functional modules can be seamlessly transmitted in a switching process, and improving the overall cooperation efficiency of the unmanned aerial vehicle electric power inspection system.

The invention provides an online monitoring data acquisition and analysis system for key parameters of a planetary rolling mill, which can display key technical parameter information in the operation process of rolling equipment in real time and can be analyzed for decision-making analysis, which includes a rolling mill lubrication system, a rolling mill cooling system, an inert gas Protection system, mandrel temperature measurement and cooling water detection system in rolling area, smart meter, data storage module, data transmission module and data analysis and summary module; The key parameters on the equipment are collected in real time, and the collected data is analyzed and processed to form a database, which is convenient for the enterprise to connect to the production situation and grasp the production cost in real time, and provides strong scientific data support for the enterprise's production decision-making.

The application relates to the technical field of power systems, and discloses a power line model parameter adaptability analysis method and system, which comprises the following steps: S100, acquiring electrical parameters reflecting actual operation characteristics of a power line as a characteristic parameter set and acquiring electrical parameters calculated by a power line model as a model parameter set; S200, performing statistical analysis on the model parameter set and the characteristic parameter set; and S300, calculating an adaptability index I of the model parameter set, I=I1*I2, wherein I1 represents expected adaptability of the model parameter set, and I2 represents interval adaptability of the model parameter set. Through the above technical scheme, adaptability analysis and defect analysis of the overall line parameters can be realized, overall review and evaluation of the effectiveness of various key parameters of the power line can be performed, common defects of the line parameters can be identified, reference bases for re-measuring the line parameters can be provided, the risk control level of a relay protection system can be improved, and the stable and economic operation of a power system can be ensured.

The invention discloses a parallel platform non-singular trajectory planning method and system and a storage medium, and relates to the technical field of robot trajectory planning and obstacle avoidance control. The method comprises the following steps: firstly, establishing a platform kinematics model and a singular point judgment standard; generating a smooth initial trajectory based on quintic polynomial interpolation; calculating a normalized weighted Euclidean distance between the trajectory point and the singular point to identify a risk segment; constructing an artificial potential field model containing an attraction potential field and a repulsion potential field for the risk segment, and correcting the track points according to resultant force; further constructing a comprehensive evaluation function fusing security, smoothness and fidelity; and finally, carrying out automatic global optimization on the key parameters of the artificial potential field by adopting a particle swarm optimization algorithm to obtain an optimal non-singular trajectory. According to the method, the problems that multiple performance indexes are difficult to collaboratively optimize and parameters are adjusted and optimized depending on experience in trajectory planning are solved, and comprehensive optimization of motion stability and path precision is guaranteed while singular points are effectively avoided.