869 results about "Test analysis" patented technology

The invention relates to the technical field of automatic report generation, and provides a test analysis and report generation method and system based on large model retrieval enhancement, and the method comprises the steps: firstly carrying out the semantic task decomposition of user query, and meanwhile, achieving the multi-dimensional information extraction through the butt joint of a knowledge vector library and a structured image-text knowledge system established by a private knowledge base module. And three strategies of RAG, Self-RAG and Graph-RAG are combined to enhance the generation capability of the large model so as to accurately obtain background knowledge. And constructing a standard SQL statement according to a structured query requirement, and performing data filling according to template prompt by an output result fusion module in combination with a query background and an SQL execution result to form a test report. By optimizing a retrieval enhancement generation method, professional knowledge supplement related to query is realized, and the reasoning ability of a large model in a professional scene is effectively enhanced, so that the accuracy and the intelligent level of data analysis are improved.

The invention relates to the technical field of chip testing, in particular to a chip testing method and a chip testing system. The method comprises the following steps: acquiring a thermal imaging image of a working state of a chip; global color temperature offset optimization is carried out on the thermal imaging image of the working state of the chip, and spatial heat distribution mining is carried out, so that a chip heat distribution diagram is constructed; performing multi-moment heat distribution tracking processing on the chip heat distribution diagram, performing dynamic heat distribution evolution fitting, and constructing a dynamic heat distribution trend evolution diagram; acquiring a high-definition image of a to-be-tested chip; performing chip assembly visual monitoring on the high-definition image of the to-be-tested chip, performing heat distribution trend rendering based on the dynamic heat distribution trend evolution graph, and constructing a chip assembly heat distribution trend rendering model. According to the invention, through limit working condition test analysis, the evaluation efficiency and accuracy of the chip performance are improved.

The invention provides an intelligent product service system concept design method based on cue word engineering. The method comprises the following steps: constructing a knowledge base, including data collection, integration and knowledge graph construction; then, a cue word project is constructed, a reasoning mode is determined, and an optimization cue template is created; and then, gradually designing from a demand layer to a physical layer, enabling LLMs in each layer to play different roles for cooperation, realizing demand collection, arrangement and conversion, function determination and decomposition, behavior and logic architecture construction, physical architecture determination and related detection analysis and the like, integrating various technologies to improve the design quality and efficiency, and meeting the market demand.

The invention relates to the technical field of network service testing, in particular to a testing method and system based on optical fiber characteristics. The method comprises the following steps: acquiring multi-dimensional optical fiber characteristic data of an optical fiber link through optical fiber characteristic acquisition equipment; performing characteristic data hierarchical integration on the multi-dimensional optical fiber characteristic data to obtain an optical link characteristic vector group; performing temperature-error code wavelet transform association according to the optical link feature vector group to obtain a temperature-error code wavelet feature set; constructing an association prediction matrix according to the temperature-error code wavelet feature set; performing a service delay exception test according to the association prediction matrix to obtain a delay tail exception event set; and performing micro-bend three-dimensional feature recognition according to the delayed tail abnormal event set to obtain micro-bend mode features. According to the invention, the operation and maintenance efficiency, reliability and toughness of the optical fiber network of the data center are improved through full-link test analysis from optical fiber physical characteristics to storage service delay.

The invention relates to the technical field of data analysis, in particular to a wind tunnel test analysis method and system for a large-span warehouse structure. The method comprises the following steps: executing a wind tunnel simulation test operation, and collecting wind tunnel test data of the wind tunnel simulation test operation; performing wind pressure quantitative distribution simulation analysis of multi-scale wind direction angles based on wind tunnel test data to generate multi-scale wind pressure quantitative distribution data; designing a wind tunnel test large-span warehouse model according to the wind tunnel simulation test operation; based on the multi-scale wind pressure quantitative distribution data, carrying out wind load analysis on each node of the warehouse on the wind tunnel test large-span warehouse model to generate warehouse wind load data; based on the warehouse wind load data, large-span warehouse structure design parameter analysis is carried out, and large-span warehouse structure design parameters are generated; and transmitting the large-span warehouse structure design parameters to a terminal to execute large-span warehouse structure design parameter feedback operation. According to the method, optimization design of large-span warehouse structure parameters is realized through wind tunnel simulation test analysis.

The invention discloses a ship mobile energy storage system CAN communication protocol automatic test system and method, and the system comprises a protocol modeling and test configuration module, a simulation node behavior simulation module, a CAN bus interaction and power closed loop module, and a test analysis and result evaluation module. A CAN communication protocol specification of the ship mobile energy storage system and parameters of tested equipment can be obtained, a protocol analysis model and a test configuration file are constructed for format verification and logic consistency verification, meanwhile, a corresponding test case sequence is automatically generated, and the message sending time is controlled to generate a time sequence simulation message flow; and sending the time sequence simulation message flow to the tested equipment, simulating energy interaction behavior acquisition to generate a power feedback data set, testing to obtain a signal consistency deviation and a power execution error to construct a protocol conformity evaluation matrix, and generating a visual test report. According to the invention, the high coverage rate and automatic closed-loop test of the CAN communication protocol can be realized.

The invention relates to the field of pipeline welding, in particular to a prediction model construction method, system and equipment of a heat affected zone and a prediction method. The method comprises the steps that phase change parameters of a metal microstructure phase change model are corrected based on a thermal simulation test; building a heat affected zone microstructure finite element prediction model according to the circumferential weld simulation calculation finite element model; and correction is carried out based on a heat affected zone hardness test and a small punch test correlation parameter correction method, and the heat affected zone strength prediction model is trained by using the expansion database to obtain the pipeline welding joint heat affected zone strength prediction model. Based on a material performance determination test, a finite element model construction method and a finite element model expansion database mode, the accuracy of the heat affected zone strength prediction model is greatly improved, the research cost is reduced, the prediction from a microstructure to macroscopic performance is realized, and the method is suitable for popularization and application. And the defect that the softening mechanism of the hot area material cannot be clarified by traditional macroscopic mechanical property test analysis is overcome.

The invention relates to the technical field of data testing, in particular to an intelligent test analysis system and method for an integrated circuit. The method comprises the following steps: acquiring circuit monitoring data; performing data preprocessing on the circuit monitoring data to generate circuit monitoring preprocessing data; performing multi-dimensional feature extraction on the circuit monitoring preprocessing data to generate a circuit monitoring multi-dimensional feature data set; performing feature set fusion on the circuit monitoring multi-dimensional feature data set to generate a circuit monitoring feature fusion data set; therefore, the problems of insufficient precision, response delay and high maintenance cost in traditional circuit monitoring are solved through an accurate data processing and intelligent analysis method, and the real-time performance, the accuracy and the predictability of intelligent testing of the integrated circuit are improved.

The invention relates to the technical field of waterproof coating detection, in particular to a waterproof coating aging life prediction method and system, which not only improve the prediction precision, but also enhance the scientificity and rationality of waterproof coating use. The method comprises the following steps: collecting a use environment parameter set and a use structure vector of a to-be-predicted waterproof coating; the use environment parameter set comprises humidity, temperature, ultraviolet intensity and pH value; the used structure vector comprises a coating area and a coating thickness; taking the use structure vector as a mapping condition, and extracting a corresponding structure aging influence factor from a pre-constructed structure influence factor matrix; obtaining component characteristic information and a standard environment parameter set of the waterproof coating to be predicted; performing deviation analysis on the use environment parameter set and the standard environment parameter set to obtain environment aging influence factors; and performing test analysis on the component characteristic information, and determining the standard service life of the waterproof coating under the standard environment parameter set.

The invention discloses a vortex-induced vibration response prediction method for a double-layer steel truss bridge based on a machine learning algorithm, and the method comprises the steps: carrying out the wind tunnel test of a section model of the double-layer steel truss bridge, and carrying out the test analysis of the influence rule of various subsidiary facilities and additional pneumatic measures on the vortex-induced vibration of the section of the double-layer steel truss bridge; the vortex vibration generation mechanism of the bridge forming state segment model is analyzed through numerical simulation, and the influence rule of additional pneumatic measure parameter change on the vortex vibration of the section of the double-layer steel truss bridge is explored; based on a machine learning algorithm, a section amplitude prediction model under different wind speeds and a vortex vibration characteristic parameter prediction model under different additional pneumatic measures are established to predict the vortex vibration response of the double-layer steel truss bridge. According to the method, wind tunnel test, numerical simulation and machine learning methods are combined, the vortex-induced vibration response of the double-layer steel truss bridge is predicted, the stability is good, the prediction accuracy is high, and therefore reference is provided for bridge design, operation and maintenance.

The invention provides a device for testing an analyte in a liquid sample, and the device includes: a sample chamber for accommodating a sample collector; a detection chamber with a bottom, where a testing element is provided in the detection chamber and used for testing an analyte in a liquid chamber; and a connecting chamber, where the sample chamber is connected with the detection chamber through the connecting chamber, a liquid is accommodated in the sample chamber, and a level of the liquid in the sample chamber is higher than a bottom of the detection chamber.

The invention relates to the field of chip testing, in particular to a chip signal integrity test analysis method, device and equipment and a storage medium. The method comprises the following steps: extracting a chip performance index based on a chip design requirement document; performing saturation frequency excitation setting based on the chip performance index to generate an excitation test signal; performing a multi-port signal excitation test and parallel signal sampling based on the excitation test signal to generate a high signal-to-noise ratio response data set; obtaining a chip layout design file; performing chip communication link analysis on the chip layout design file, and constructing communication line layout data; performing signal mapping and waveform quality evaluation on the communication line layout data based on the high signal-to-noise ratio response data set to obtain a node signal distortion rate; and performing signal integrity quantization and theoretical signal integrity score comparison based on the node signal distortion rate, and marking a fault node. According to the invention, the chip testing efficiency is improved, and the signal abnormal part of the chip is accurately and efficiently detected.

The invention discloses a code generation and restoration method and device based on multi-round feedback of a large language model, and the method comprises the following steps: 1, converting problem description into a structured tetrad (target, input, output and constraint) through a two-stage task demand deconstruction mechanism, and generating a pseudo-code frame according to the structured tetrad; 2, generating a plurality of candidate code schemes in parallel based on different implementation strategies; 3, selecting an optimal code implementation scheme through multi-dimensional evaluation; 4, generating an extended test case through boundary condition analysis and public test reasoning, and expanding a verification range; 5, classifying error types in combination with static analysis and dynamic execution information, and applying a special repair strategy; 6, providing detailed repair reasons and ideas by an interpretable repair mechanism; and 7, establishing a multi-round feedback repair verification iteration mechanism composed of testing, analysis, repair and verification. According to the method, the performance of an existing large language model in processing a complex programming task is effectively improved.

The invention discloses an intelligent flow sensor test analysis method and system, and relates to the technical field of sensor testing, and the method comprises the steps: applying a stepped flow excitation signal to a tested sensor through a standard flow generation device, and synchronously collecting the dynamic response data of the sensor; extracting a feature parameter set from the response data; performing similarity matching calculation to obtain a matching degree evaluation value of each error type; quantifying the induction relation strength among different error types; generating a composite weight coefficient in combination with the matching degree evaluation value and the evoked relationship strength; and making a multi-stage compensation strategy based on the composite weight coefficient. The method has the advantages that by combining error correlation network modeling driven by historical data, induction mechanisms and interaction relations of different error types can be analyzed, the pertinence of a compensation strategy is greatly improved, a multi-stage error suppression mechanism is formed, stable control over comprehensive errors is achieved under complex working conditions, and meanwhile the system maintenance requirement is lowered.

The invention provides an integrated circuit performance testing method based on multi-dimensional parameter fusion, and belongs to the technical field of integrated circuit performance testing. S2, collecting multi-dimensional parameters; s3, data preprocessing; s4, carrying out multi-dimensional parameter fusion; and S5, performance test analysis. Through multi-parameter coverage, multi-algorithm collaboration and full-process closed loop, the problems of isolation, fragmentation and simplification of traditional testing are solved, and systematic and refined technical support is provided for performance testing of the integrated circuit.

The invention discloses a new energy broadband test analysis management and control method and system, and relates to the technical field of new energy detection and intelligent management and control, and the method comprises the following steps: obtaining a multi-window splicing frequency spectrum of a load switching edge, superposing phase lock consistency verification in a splicing frequency spectrum result, generating a frequency spectrum leakage suspicion chart, and carrying out the boundary constraint for energy track extraction; under the constraint of a spectrum leakage suspicion chart, an energy center track, a group delay curve and a phase derivative sequence are extracted, and a cross-frequency migration fingerprint is constructed and is used as a basic evidence for misjudgment traceability. By means of spectrum suspicion identification, feature fusion modeling, misjudgment traceability, label correction, energy reverse intervention and the like, accurate identification and closed-loop regulation and control of false operation caused by spectrum leakage are achieved, high identification accuracy, low misjudgment rate, high anti-interference performance and quick response capacity are achieved, and the operation stability and safety of a new energy field station are remarkably improved.

The invention discloses a rope technical equipment testing system and method under multi-environment conditions, and relates to the technical field of rope testing, and the system comprises the steps: building target testing equipment, and activating an environment simulation cabin module to set a plurality of environment simulation conditions; connecting the to-be-tested rope equipment to target test equipment and activating a mechanical loading module; performing various mechanical tests on the to-be-tested rope equipment, and generating a test data sensing record log; evaluating the to-be-tested rope equipment according to the test data sensing record log to generate a rope performance evaluation index; and performing test analysis on the to-be-tested rope equipment, generating a test report, and generating optimization suggestions of the to-be-tested rope equipment. The technical problem that the rope is lack of safety and reliability due to inaccurate performance test of the rope in the prior art is solved, and the technical effects of accurately simulating a complex environment, comprehensively evaluating the performance of the rope and improving the use safety and reliability of the rope are achieved.

The invention is applicable to the technical field of PCB testing, and particularly relates to a PCB electrical performance testing method, which comprises the following steps of: acquiring test object information; wherein the object information comprises a PCB image and at least one test area, the PCB image corresponds to the PCB and reflects the circuit structure of the PCB, the test area is marked on the PCB image, and the test area comprises a main test position and an auxiliary test position; when an electrical performance test instruction is received, contact judgment information is obtained based on the test object information; when it is detected that the auxiliary test probe is in stable contact with the auxiliary test position, the control device controls the main test probe to continuously send test signals and collect test results in real time, and test analysis information is obtained based on the test results. According to the PCB electrical performance test method provided by the embodiment of the invention, the problem of high test error caused by asynchronous actions of the main test probe and the auxiliary test probe can be improved.

The invention relates to the technical field of chip test analysis, in particular to an analysis optimization method and system based on chip test data, and the method comprises the following steps: carrying out the voltage collection and current collection based on the chip test data and probe contact information, carrying out the node relation operation through combining with a graph neural network, and extracting the adjacency relation; and abnormal waveforms and noise waveforms are screened, wafer atlas positions are associated, and channel waveform mapping is generated. According to the method, voltage and current data and probe contact information are integrated, the graph neural network is adopted to deeply explore the relationship between nodes, the adjacency relationship is effectively extracted, the abnormal waveform is screened and associated to the wafer graph position, and the analysis capability of waveform data is improved. According to the strategy, by dynamically comparing the waveform difference values and counting the waveform amplitude and optimizing the test steps through the deep reinforcement learning technology, the efficiency of the test process is effectively improved, and redundant operation is reduced.

The invention provides a tire test analysis and reliability evaluation method based on a damage evolution model, and the method comprises the steps: obtaining data: obtaining 12 mechanical channel data of forces and displacements of a tire in three directions and moments and rotation angles of three axes; identifying a periodic tread jitter value and a sidewall movement value of the tire as deformation channel data; acquiring a tire temperature field as temperature channel data; data analysis: analyzing the reliability of the tire based on the mechanical signal, the visual deformation signal and the temperature field signal; and reliability prediction: judging the tire damage probability based on reliability analysis results of the mechanical signal, the visual deformation signal and the temperature field signal.

The invention provides a karst foundation model test block preparation device and a test method, belongs to the technical field of physical property test analysis, and is used for solving the problem that a karst model with a cavity structure is difficult to cast inside by a traditional model test block preparation technology in the prior art. Specifically, the device comprises a model frame with an opening in the top and a reinforcing structure arranged on the periphery of the model frame; the device further comprises a cavity reserving device, the cavity reserving device is located in the model frame and does not make contact with the wall face of the model frame, rock mass similar materials are poured into the model frame to form a karst foundation model test block, and after pouring is completed, the reserving device forms a cavity with an arc-shaped top face in the karst foundation model test block. A cavity space for simulating a karst hole is constructed in the model test block, the problem that a hole structure is difficult to form in the model test block through a traditional preparation technology is effectively solved, and powerful support is provided for deeply researching a karst foundation instability mode and a karst foundation instability process.

The invention discloses a leakage current test analysis method and platform for a low-power-consumption chip, and belongs to the field of semiconductor testing, and the method comprises the steps: collecting the chip feature data of a target low-power-consumption chip, and determining a plurality of environment parameter test ranges and working voltage test ranges of the target low-power-consumption chip; generating an environment test sequence and a voltage test sequence, combining the environment test sequence and the voltage test sequence, and generating an adaptive test scheme; constructing a leakage current data matrix based on the adaptive test scheme; obtaining a first analysis result; obtaining a second analysis result; and obtaining a leakage current characteristic evaluation result of the target low-power-consumption chip based on the first analysis result and the second analysis result. The technical problems that in the prior art, the leakage current testing condition is single, the characteristics of the low-power-consumption chip under the multi-environment parameter and voltage condition are difficult to comprehensively evaluate, and consequently the accuracy and applicability of the testing result are insufficient are solved.

The invention relates to the technical field of hydrogen energy safety, and provides a hydrogen fuel cell automobile hydrogen leakage diffusion concentration monitoring test device and method.The device comprises a hydrogen storage system, a flow control system, a data acquisition and storage control system and a leakage opening simulation device, the hydrogen storage system comprises a hydrogen cylinder, and the flow control system comprises a plurality of airflow channels arranged in parallel; one end of each gas flow passage is connected with the hydrogen storage system, the other end of each gas flow passage is connected with a leakage port of one leakage port simulation device, each gas flow passage is provided with a plurality of gas flow branches in parallel, and different gas flow branches regulate and control the leakage gas flow by controlling the gas flow or the pressure and the size of the leakage port in a combined manner; according to the automobile hydrogen leakage diffusion test system, the hydrogen leakage diffusion platform of the hydrogen fuel cell automobile and the data acquisition and storage control system are built, so that the diffusion characteristics of the automobile after hydrogen leakage can be tested and analyzed, and the result can assist in making a hydrogen leakage emergency scheme and preventing the occurrence of hydrogen leakage fire explosion.

The invention relates to the technical field of network security, and discloses a multi-agent cooperative RESTful API vulnerability test method. Constructing a parameter structured representation by analyzing an API interface specification, generating a test value conforming to service semantics by using a large language model, and establishing a semantic request baseline representing normal service logic; constructing a multi-agent collaborative architecture including vulnerability reasoning, case generation, test execution, test analysis and test management; all the agents are coordinated to carry out iterative vulnerability testing through a signal mechanism and a state transition table, and API service analysis, test strategy customization, use case directional variation and execution, result study and judgment and strategy optimization are achieved; and finally generating a structured vulnerability report. According to the method, the problems of semantic blind areas, shallow analysis layers, insufficient adaptive capacity and the like are solved, security risks such as business logic vulnerabilities and sensitive data leakage in the RESTful API can be deeply detected, and the accuracy and coverage rate of vulnerability detection are remarkably improved.

The invention relates to the technical field of data analysis, in particular to a method for constructing an acute pancreatitis severity prediction model based on a liquid neural network, which comprises the following steps: firstly, extracting and preprocessing patient data, and then dividing AP patients into a severe AP group and a mild AP group; screening two groups of characteristic indexes with differences through nonparametric test analysis to carry out machine learning modeling in the next step; in order to prevent overfitting, five-fold cross check is adopted to train the model, and optimal feature combinations under respective machine learning models (a liquid neural network, a decision tree, a random forest, Logistic regression and an XGBoost algorithm) are obtained by drawing AUC values under an ROC curve for comparison. The method comprises the following steps: firstly, training a liquid neural network model, then verifying verification data by using respective optimal prediction models obtained by training, and finally, analyzing influence weights of different features in the liquid neural network model through SHAP visualization and carrying out visualization so as to provide visual prediction reference for users such as doctors and the like.

The invention discloses a fuel cell test system and method. The fuel cell test system comprises a test stack and a test analysis device, the test analysis device is connected with the test stack to detect the performance of the test stack, and the test stack comprises two end plates and more than two test single cells arranged between the two end plates. The pseudo single pools are arranged between two adjacent test single pools; and the test analysis device is respectively connected with the more than two test single cells so as to obtain performance parameters of different test single cells in the same test pile. The fuel cell test system provided by the invention can perform rapid detection and effective comparison on the performance of various test single cells, is beneficial to rapid model selection of single cell membrane electrodes, and improves the development efficiency of fuel cells.

The invention discloses a full-automatic intelligent multifunctional high-order nonlinear fluorescence dynamics testing method and device, and relates to the field of nonlinear optics and nano photonics. An optical testing device composed of an exciting light generation module, an automatic power regulation module, an exciting light modulation module, a sample scanning module, a data acquisition and analysis module and an intelligent control module is established, and under the excitation of incident laser, based on the overall coordination of the intelligent control module, the optical testing device is established. Other modules are driven to complete the dynamic response test of a nonlinear fluorescence sample, and full-automatic intelligent, multifunctional, high-precision, simple, efficient, low-cost and universal fluorescence dynamic test analysis is realized. The problems that traditional manual operation wastes time and labor and the testing precision is low are solved. In addition, the multifunctional integration of the fluorescence response curve, the fluorescence rise time, the fluorescence lifetime and the fluorescence imaging effectively improves the test efficiency and the application scene, and greatly reduces the system cost.

The invention relates to the technical field of battery performance test and analysis, and discloses a lithium battery test analysis method based on deep learning and feature analysis, which comprises the following steps: S1, establishing a dynamic environment model, and obtaining dynamic distribution of temperature and humidity in a battery use environment, the dynamic distribution of the temperature and the humidity is based on the combined influence of diffusion, convection and external disturbance; s2, dynamic environment features are extracted, and main amplitudes and frequencies of temperature and humidity serve as environment feature vectors; and S3, based on the lithium ion diffusion model, a coupling relationship between lithium ion concentration distribution and environmental characteristics is established, and the lithium ion concentration distribution is influenced by temperature and humidity changes in a dynamic environment. By adopting the technical scheme based on dynamic environment modeling and feature extraction, dynamic distribution of temperature and humidity is described through a partial differential equation, and environment feature vectors are extracted, so that the technical effect of accurately simulating and quantifying the influence of complex environment change on battery performance is achieved.

The invention provides a karst stratum rock groutability test analysis method, device, equipment and medium, and relates to the technical field of mine water disaster prevention and control, and the method comprises the steps: obtaining a rock core sample, and obtaining a to-be-grouted rock sample and first pore information of the to-be-grouted rock sample before grouting; the method comprises the following steps: acquiring a first weight and a rock sample length of a to-be-grouted rock sample before grouting, performing a grouting test and slurry initial setting on the to-be-grouted rock sample to obtain a grouted rock sample, and acquiring a second weight of the grouted rock sample; based on the first weight, the rock sample length and the second weight, the linear meter grouting amount of the rock sample to be grouted is determined; acquiring second pore information of the grouted rock sample; and evaluating the groutability of the karst stratum based on the first pore information, the second pore information and the linear meter grouting amount. According to the method, advanced research on the groutability of the target governance layer is realized, and a scientific basis is provided for subsequent ground area governance scheme design, project amount, grouting amount prediction and governance effect verification and evaluation.

The invention relates to the technical field of memory bank testing, and discloses a server mainboard memory bank plugging and unplugging test system which comprises a mechanical plugging and unplugging module, a sensor module, a pre-detection module, a test analysis module and a result display module.According to the server mainboard memory bank plugging and unplugging test system, automatic operation is achieved through the mechanical plugging and unplugging module, and accuracy and efficiency are improved; the sensor module adopts a four-wire system resistance measurement sensor, the contact resistance is accurately measured, and the contact detection precision is guaranteed; the pre-detection module can screen out memory banks with appearance scratches in advance from multi-angle image acquisition and equal-interval grid division to accurate pixel value analysis by utilizing a scientific appearance detection process; the test analysis module comprehensively evaluates the performance, the contact state judgment is clear, and the memory read-write and stability test is rigorous and scientific; a test report generated by the result display module visually shows results of scratch, contact, read-write, stability and the like, comprehensive information is provided for operators, and efficient judgment of the performance of the memory bank is assisted.