17results about How to "Avoid trial and error" patented technology

The application discloses a method and system for rapidly predicting a creep stress index of a tin-based solder alloy by integrating a model, collects element compositions, test temperatures and creep stress index values of the tin-based solder alloy from literature, and adds experimental data as dataset samples; the element compositions and test temperatures of the tin-based solder alloy are sorted out and used as features for modeling; the dataset is randomly divided into a training set and a test set in a 4:1 ratio; the collected creep stress index values of the tin-based solder alloy are used as target variables, and the features are used as independent variables; based on the divided training set, the independent variables are scaled by using RobustScaler, three learners are trained and integrated to obtain an R-X-L integrated model; and the R-X-L integrated model is used to rapidly predict the creep stress index of the test set samples and four independent experimental samples. The prediction model for the creep stress index of the tin-based solder alloy is simple, fast, low-cost, pollution-free and the like based on reliable literature data and a modeling method.

This invention proposes a dynamic routing decision-making method, specifically a TSSDN dynamic routing decision-making method based on the DDPG deep reinforcement learning algorithm. The aim is to design dynamic routing decisions using deep reinforcement learning algorithms based on network dynamic awareness prediction results, thereby reducing the transmission latency of low-priority flows in time-sensitive networks. This invention uses a deep learning algorithm to predict switch queue lengths in real time, and then makes next-hop routing decisions based on the prediction results. Higher prediction accuracy leads to better dynamic routing performance and improved decision-making efficiency. The implementation steps are: 1) Constructing the TSSDN network node architecture; 2) Constructing the network topology; 3) Constructing a topology feature extraction method based on PCA; 4) Constructing a prediction model based on a deep learning algorithm; 5) Constructing a routing decision-making model based on a deep reinforcement learning algorithm; 6) Iteratively training the deep reinforcement learning-based routing decision-making model based on the prediction results. This invention can be applied to scenarios such as telemedicine.

The application discloses a retinal light damage box experimental device for observing mouse visual dynamic response, which comprises a reflecting box body, a box cover hinged to one side of the top end of the reflecting box body, the box cover being matched with the reflecting box body, a light irradiation assembly fixedly connected to one side of the box cover close to the inside of the reflecting box body, the inner wall of the reflecting box body being used for reflecting the light emitted by the light irradiation assembly, the light irradiation assembly being electrically connected with a control system, a frequency adjusting assembly fixedly connected to the middle of the bottom end of the reflecting box body, the frequency adjusting assembly being covered on a placing table, the frequency adjusting assembly being correspondingly arranged on the inner wall of the reflecting box body, and a placing assembly fixedly connected to the middle of the top end of the placing table, the experimental mouse being placed in the placing assembly, the light irradiation assembly and the frequency adjusting assembly being correspondingly arranged on the placing assembly. The application realizes dynamic observation of the light damage condition of the experimental animal, avoids repeated experiments, shortens the experimental period and improves the experimental efficiency.

This invention relates to the field of computer-aided design technology, specifically a digital design system for rib jacquard fabric textures. The system includes a jacquard pattern structure conversion module, used to acquire the coordinate parameters of coil nodes and the connection direction parameters of adjacent coil nodes within the design pattern, establish a jacquard directed graph, extract the surface identification parameters of coil nodes, assign cross-layer weight values ​​to directed edge parameters based on the difference in surface identification parameters, and fuse the cross-layer weight values ​​with the jacquard directed graph to generate a weighted graph dataset. In this invention, by comparing risk values ​​with separation threshold parameters, a node reconstruction distribution set is automatically established within abnormal grid areas, replacing the original connection direction attributes to generate a digital jacquard pattern set, thus completing a closed-loop, intelligent repair of design defects. This allows fabric structural defects to be detected and eliminated during the design phase, avoiding repeated trial and error in the physical sampling process and improving design efficiency and first-time success rate.

The invention belongs to the field of cell culture automation and intelligent regulation and control, and discloses an optogenetics-based adherent cell culture optimization method and system. The method comprises the following steps: inputting an adherent cell type and a culture target, and calling an adherent cell-optical genetic parameter joint database; performing targeted pretreatment on the target adherent cells; processing through a multi-parameter optimization algorithm hardware platform to generate an executable customized photostimulation scheme; performing accurate light stimulation on the positive adherent cells; comparing the obtained detection data with normal adherent cell parameters in a joint database, and evaluating the influence of a photostimulation scheme on the cells; updating the parameters of the multi-parameter optimization algorithm and the prediction model; and inputting the adherent cell type and the culture target to the updated prediction model, and outputting an optimal light stimulation scheme. The core problems of low photostimulation accuracy and poor targeting in the prior art are solved, and high-activity and high-consistency light-sensitive adherent cells are stably produced.

The application provides a network node state data trusted algorithm determination method and system, the method comprises the following steps: the security state agent of each network node obtains the available security algorithm information of the local XFRM framework through a Netlink interface, and generates local state data with a unique node identifier and a version number; the state data is synchronized with neighbor nodes by using a Gossip protocol, version number, integrity and multi-source consistency verification are performed on the received data, and the algorithms corresponding to the same state data from at least two non-direct neighbor nodes are marked as cluster trusted algorithms; and a trusted algorithm list is generated for the local IPsec process to query for security association negotiation. The application realizes dynamic discovery and trusted synchronization of cluster security algorithms, adapts to edge nodes and multi-region cluster scenarios, guarantees synchronization reliability and security, and does not affect the running performance of the cluster.

The invention discloses a preparation method of a tunnel lining degradation similar material based on performance inversion, the tunnel lining degradation similar material and application, and the preparation method comprises the following steps: firstly, carrying out a four-factor four-level orthogonal test based on cement, river sand, gypsum and water to obtain test block mechanical property data; establishing a tunnel lining reduced scale performance calculation model by using a multi-target-ideal point method; simulating performance degradation of the lining after N years of operation by combining a concrete incremental damage theory; and finally, inversely calculating the mix proportion of the degraded similar material through a multi-target-ideal point method. According to the preparation method, the whole-course simulation of the tunnel lining from a prototype state to a degradation state is realized, namely a reliable experimental material can be provided for tunnel maintenance. The tunnel lining degradation similar material can be accurately matched with the real degradation state of a tunnel in a specific service period; when the tunnel lining degradation similar material is used for a model test, the residual life of an existing tunnel can be more truly predicted, and the effectiveness of reinforcement measures is evaluated.

This invention belongs to the field of industrial internet security technology, specifically relating to an industrial internet vulnerability verification method that addresses the problems of low efficiency, insufficient accuracy, poor engineering feasibility, and inconvenient remediation in existing vulnerability verification technologies. This invention first constructs a protocol template library and parses the original network packets to obtain field sequences; it calculates the distribution entropy, historical mutation response rate, and type identifier as scenario feature vectors; it retrieves similar historical scenarios and dynamically selects strategies based on mutation strategy statistics and experience scores; it generates test cases from mutation seed packets, sends them to the target device for verification, and obtains responses; it updates strategy statistics and the experience replay pool; in case of anomalies, it actively intervenes in experiments to determine causal effects, generating verification records, reproduction packages, and guidelines for manual confirmation. This invention achieves accurate and efficient vulnerability verification, improves the interpretability and reproducibility of results, reduces engineering deployment costs, and facilitates vulnerability analysis and remediation.

This invention relates to the field of space optical payload integrated simulation technology, specifically providing a gravity unloading optimization method based on a sensitivity matrix. The method includes: pre-setting corrected surface shape error indices and engineering constraints on unloading forces; constructing a mechanical sensitivity matrix for the mirror surface through finite element analysis; obtaining the change in mirror surface shape caused by applying a unit force at each gravity unloading point; establishing an objective function aimed at minimizing the corrected surface shape error; solving for the optimal unloading force at each gravity unloading point; calculating the corrected surface shape error based on the optimal unloading force and the mechanical sensitivity matrix at each gravity unloading point; and verifying whether the corrected surface shape error meets the surface shape error indices. This invention avoids the traditional method of repeated trial and error and iterative simulation, greatly improving the efficiency of optimization simulation.

The application discloses a kind of sound barrier backboard pressure rib parameter optimization design method, it is related to engineering structure design and optimization technical field, and design method includes the following steps: establishing the finite element model of sound barrier, applies design wind pressure load, with predetermined initial pressure rib parameter as benchmark, deflection is solved;In the case where remaining parameters remain unchanged, respectively, change the depth, width, quantity and length of backboard pressure rib alone and carry out single-factor parameterization simulation, obtain the deflection variation corresponding to each parameter under different value;According to the size of deflection variation, determine the influence weight order of each parameter on the wind pressure resistance performance of screen body;With the parameter of maximum influence weight as priority maximization object, determine the maximum feasible value of this parameter within the range allowed by manufacturing process, and form optimal pressure rib parameter combination in combination with the maximum value of the remaining parameters.It is realized that the wind pressure resistance performance of screen body is maximized by systematic parameterization simulation and influence weight ordering.

The application discloses an intelligent method for structural model parameter identification and adjustment, comprising: grouping and calibrating target components in a structural model; using a structural domain knowledge base storing standard structural topology, component mechanical parameter benchmark values and design specification limit values to perform feature extraction and matching identification on each component group, and outputting parameter initial value suggestions; visualizing the matching results for designers to audit and confirm; receiving manual adjustment instructions, wherein spatial structure node coordinates are driven by macro-geometric control parameters to update in batches; automatically generating complete updated model files based on the adjusted parameters and re-associating various model information; constructing a three-dimensional visual display interface to realize high-light linkage display of parameters and components and comparison before and after adjustment. The application solves the problems of low structural design parameter adjustment efficiency, difficulty in batch adjustment of spatial structure node coordinates and poor generality of parameterized programs, and significantly improves design efficiency.

This invention discloses a steel-shell composite girder structure and its optimized design method for filling ultra-high performance concrete (UHPC) within a steel shell. It relates to the field of steel-concrete composite structure technology. The key technical points are: the invention welds and fixes the lower steel plate of the bridge deck's steel shell to the upper chord and upper crossbeam of the truss, creating a continuous connection between the upper chord and the lower steel plate, forming an integrally closed frame structure with the side plates of the steel shell. During UHPC pouring, the continuity between the upper chord and the lower steel plate avoids the problem of phased pouring. This frame structure also serves as a permanent formwork for the UHPC pouring and a part of the structural load-bearing capacity, thereby enhancing the integrity between the bridge deck and the truss. By arranging perforated I-beams, shear bolts, and transverse reinforcement details between the bridge deck's steel shell, a good combination of UHPC and steel shell is achieved, forming an integrated steel-shell-UHPC composite bridge deck system, improving the bridge deck's stiffness and load-bearing capacity.

This invention provides a method and system for autonomous iteration and real-time control of forging process based on machine vision for extracting time-frequency map features. The method transforms the thermal and deformation history data during forging into a time-frequency map through time-frequency transformation, and establishes a mapping relationship between the time-frequency map and the microstructure using a convolutional neural network (CNN). Then, a generative model is used to construct a bidirectional mapping model between process parameters and the time-frequency map. Based on this, combined with a model predictive control (MPC) framework, the process parameters are optimized in real time with microstructure targets as constraints. After the process is completed, the model parameters are iteratively updated autonomously, thereby achieving iterative optimization of the microstructure quality of the forging. This invention can effectively extract deep features of the thermal deformation history, establish a reliable mapping relationship between "process parameters - thermal deformation history - microstructure," and achieve online optimization of process parameters during forging, providing an intelligent production process optimization solution for the high-end equipment manufacturing field.

The application discloses a kind of metal welded pipe spraying intelligent adaptation process methods, belong to metal surface treatment technical field, by welded pipe information acquisition and preprocessing, spraying process parameter intelligent matching, virtual simulation verification optimization, closed-loop intelligent spraying execution, coating on-line detection and model feedback update five core steps, realize the self-adaptive matching of different properties metal welded pipe spraying process and whole-process closed-loop management and control.The present application can effectively solve the problem of poor adaptability of existing process parameters, coating quality stability is insufficient, the problem of whole-process management and control is missing, significantly improve the coating uniformity and finished product pass rate of welded pipe spraying, reduce the cost of production rework, through on-line full-dimensional detection and process feedback correction after coating forming, coating defects can be quickly identified and the process parameters of subsequent production are adjusted, to avoid the repeated occurrence of similar defects, greatly improve the finished product pass rate of welded pipe spraying, significantly reduce the cost of subsequent rework and raw material loss.

This invention relates to the field of fluid control valve technology, specifically to a method and system for predicting the dynamic stability of a pilot-operated pressure reducing valve. The invention establishes a force balance equation containing p-Laplace terms and derives the stability criterion S for the pressure reducing valve to determine whether the valve system is stable. This allows for the assessment of whether parameter combinations will lead to oscillations during the design phase, avoiding trial and error and enabling the prediction of the pressure reducing valve's stability. The criterion is simple in form, can be calculated using a calculator or Excel, does not rely on complex simulations, and is highly concise. Furthermore, its p-value is adjustable, making it applicable to different media and operating conditions, thus offering wide applicability. This system can be embedded in an intelligent valve controller to achieve real-time stability warnings.

This invention discloses a deformable blade design method based on solving the electromechanical coupling matrix equations, belonging to the field of engine blade design technology. Starting from a fully tessellated MFC (Mechanical-Fuel-Coupling) scheme, the method uses the finite element method to discretize and derive the key matrices of the electromechanical coupling system, establishing quasi-static electromechanical coupling control equations. Ill-conditioned problems in the equation set are addressed through voltage degree-of-freedom scaling preprocessing, and the driving voltage distribution is solved in conjunction with target deformation constraints. The birth and death element method is introduced to quantify the contribution of MFC elements at different locations to deformation, gradually eliminating inefficient elements and generating an optimized arrangement and driving scheme. For complex three-dimensional blades, static condensation and implicit iteration of inner and outer layers are used to reduce the computational scale, and the MFC polarization and driving direction setting problems are solved through the element coordinate system method. This invention eliminates the need for repeated iterative trial and error, significantly improving the efficiency of deformable design and achieving high deformation accuracy, providing a systematic design method for the engineering application of controllable deformable blades.

This invention relates to the field of production line lifecycle management technology, specifically to an intelligent operation system and method for a glass production line based on a digital twin. The system includes a digital process package generation module, a digital twin construction module, and a monitoring and verification module. This application uses the obtained glass performance indicators as constraints for multiphysics simulation and optimization to obtain a digital process package for the glass production line. This provides a standardized and directly executable process basis for subsequent production line operation, improving the consistency and reproducibility of process solutions in actual production. Furthermore, by combining the acquired BIM model and collected raw multi-source sensor data with the digital process package, a digital twin is constructed, achieving a high-precision bidirectional mapping between the physical production line and the digital twin. Finally, the status monitoring and verification of the production line operation are performed based on the digital twin, achieving more accurate and efficient glass production line management and solving the problems of low accuracy and real-time performance in existing glass production line management technologies.