39 results about "Test matrix" patented technology

A system for accidentology-based measuring of accident risk-indexing score values for a motor vehicle to be tested providing a measured accident probability value for an occurrence of an accident event having a physical impact to the tested motor vehicle. The system includes a driving scenario module, a test setting module, and a scoring module. The driving scenario module is configured for determining various driving scenarios for the motor vehicle by defining a set of measurable scenario characteristics, which include at least one ADAS variable. The test setting module is configured for determining a test setting in form of a multi-dimensional test matrix, which includes testing protocols for each of the measurable scenario characteristics for providing measured values of measurable scenario characteristics of the various driving scenarios. The scoring module is configured for generating the risk-indexing score by receiving the multi-dimensional test result signal and a historical data information signal.

The invention relates to a low-code visualization optimization method and system for power credential development, and the method comprises the following steps: S1, obtaining data in a credential environment, recognizing the interface difference and performance bottleneck points between components through a compatibility test matrix, and building a standardized adaptive interface specification; s2, obtaining a standardized business object model based on the standardized adaptive interface specification; based on the business object model, defining attributes, relationships and constraint rules of each business entity, and forming a data dictionary and an interface specification special for the electric power field; s3, on the basis of the data dictionary and the interface specification special for the power field, constructing a DSL (field specific language) of power visualization; s4, a dragging type interactive design is adopted, and the visual operation is converted into a DSL configuration file; and S5, automatically converting the DSL configuration into a React or Vue component code through a code generation engine, and carrying out compatibility optimization on the kernel of the creative browser. According to the invention, the power credential development efficiency is effectively improved.

The invention discloses a multi-dimensional power consumption test method and device for a solid state disk and a storage medium, and the method comprises the steps: controlling a test environment parameter and the solid state disk to enter a preset initial state in response to a test start instruction; based on a test matrix which predefines a plurality of temperature and capacity occupation combinations, controlling a test device to apply a multi-dimensional dynamic working load to the solid state disk, and synchronously acquiring power consumption data, internal state data and performance data; performing time synchronization and data fusion on the collected multi-source data to form an associated data set; and performing intelligent analysis on the data set, extracting power consumption characteristics of the solid state disk, and generating a power consumption evaluation report based on the power consumption characteristics. According to the method, the problems of single test dimension, incomplete test condition coverage, failure in effective fusion of multi-source data and lack of intelligent analysis in the prior art are solved, and comprehensive, accurate and automatic evaluation of the power consumption of the solid state disk is realized.

The embodiment of the invention relates to an automated vehicle test script generation method and device and electronic equipment, and the method comprises the steps: determining function items with different configurations in different vehicle types as to-be-tested items from a preset vehicle type configuration list; generating a test matrix based on the configuration word of the to-be-tested item; according to configuration words included in the test matrix, generating a corresponding test case; and generating a corresponding test script based on the test case. According to the embodiment of the invention, different function items are extracted for testing according to configuration lists of different vehicle types, the test matrix is generated according to the different function items, the pertinence and the efficiency of generating the test cases and the test scripts are effectively improved, the test cases and the test scripts are automatically generated, excessive manual intervention is not needed, and the test efficiency is improved. Therefore, the labor cost is reduced, and the efficiency and reliability of the vehicle function test are improved.

The application discloses a kind of multi-dimension power consumption test method, equipment and storage medium of solid state disk, the method includes: in response to test start instruction, control test environment parameter and solid state disk enters preset initial state;Based on the test matrix of multiple temperature and capacity occupation combinations being predefined, control test equipment to apply multi-dimension dynamic work load to solid state disk, and synchronously collect power consumption data, internal state data and performance data;The multi-source data collected are time-synchronized and data fusion, form associated data set;Intelligently analyze the data set, extract the power consumption characteristics of solid state disk, and generate power consumption evaluation report based on it.The application solves the problems of single test dimension, incomplete test condition coverage, ineffective fusion of multi-source data and lack of intelligent analysis in the prior art, and realizes comprehensive, accurate and automated evaluation of solid state disk power consumption.

This invention relates to the field of engine performance calibration technology, and provides a method for optimizing and calibrating engine transient performance based on response surface design. The method includes the following steps: setting decision variables and target variables to construct an experimental matrix; conducting experimental tests based on the test matrix; fitting and evaluating a quadratic model; simplifying and selecting the fitted model; performing predictive optimization calculations and experimental verification; and performing full-condition Map calibration over a speed range. This method can be practically applied to transient performance optimization during engine R&D testing, optimizing engine performance during real-vehicle operation, and intuitively demonstrating the validity of test data through mathematical models, without requiring excessive testing resources.

The invention discloses a function detection method, device and equipment and a readable storage medium, and the method comprises the steps: training a neural network model through a training sample set, so as to enable the neural network model to have a processing function of a to-be-detected object in a multi-time-sequence scene; obtaining a test case of the multi-time-sequence scene; the test case comprises a plurality of verification incentives with time sequence constraints; respectively inputting the plurality of verification excitations into the to-be-tested object according to time sequence constraints to obtain a first test result output after the to-be-tested object is processed; converting the plurality of verification excitations into a test matrix according to time sequence constraints, and inputting the test matrix into the neural network model for processing to obtain a second test result; and comparing the first test result with the second test result to detect the processing function of the to-be-tested object in the multi-time-sequence scene. According to the invention, the development and verification period of the chip can be effectively shortened.

The application relates to a low-code visual optimization method and system for power signal creation development, which comprises the following steps: S1: acquiring data in a signal creation environment, identifying interface differences and performance bottleneck points among various components through a compatibility test matrix, and establishing a standardized adaptive interface specification; S2: acquiring a standardized business object model based on the standardized adaptive interface specification; defining the attributes, relationships and constraint rules of various business entities based on the business object model, forming a data dictionary and an interface specification special for the power field; S3: constructing a power visual field-specific language DSL based on the data dictionary and the interface specification special for the power field; S4: converting the visual operation into a DSL configuration file by adopting a drag-and-drop interactive design; and S5: automatically converting the DSL configuration into a React or Vue component code by a code generation engine, and performing compatibility optimization on a signal creation browser kernel. The application effectively improves the power signal creation development efficiency.

The invention provides a function logic test case generation method, a test method and a device, and the method comprises the steps: automatically generating a directed conversion diagram containing the conversion relation between different hardware power states, and a test matrix containing the specific information of each software logic function through analyzing a demand document of the device; in the process of generating parameter difference information, hardware power supply states and software logic functions are tightly coupled, all possible state conversion paths are traversed through a directed conversion diagram, and functional parameter changes under different hardware power supply states and software logic functions are automatically identified. Therefore, basic test cases corresponding to different functions in each power supply state can be generated; on the basis, boundary parameters and a conversion relation are further adjusted, and a boundary test case and an abnormal test case are generated, so that the test case capable of realizing full-scene coverage is automatically generated, and high-coverage-rate efficient full-automatic test is conveniently carried out on functional logic of the equipment in a multi-power-supply state.

The invention provides a method for supporting batch satellite data analysis in a batch production satellite manufacturing process, and the method comprises the steps: automatically generating a satellite test matrix table according to a satellite test station, a satellite SN serial number and test feature data; collecting batch-produced satellite telemetry data of the listed test item lines based on the satellite test matrix table; analyzing the satellite telemetry data, and judging whether the data is normal or abnormal; calculating the maximum value, the minimum value, the average value and the range value according to the important telemetering parameters with the data in the normal value range in the test matrix time range of each satellite; and performing data analysis on the calculation result to obtain an evaluation result of the current batch of satellites. The analysis method mainly has an integration and analysis process for the data of the batch-produced satellites, the analysis of the data of the satellites is further carried out in the stages of average value, maximum value and minimum value, further comparison of telemetering parameters is realized through software, and the data deviation condition of the current batch-produced satellites is obtained through data analysis.

The invention discloses a test point optimization method and system based on an improved binary particle swarm genetic algorithm, and relates to the field of testability design. The method solves the problem that an existing single algorithm is prone to falling into local optimum or low in search efficiency in a high-dimensional discrete solution space. The method comprises the steps that a fault test matrix is constructed; defining a testability index; establishing an optimization model; initializing parameters and a value permission range in the improved binary particle swarm genetic algorithm; carrying out fitness calculation on the test points; the fitness of the current individual and the fitness of the historical optimal test point are compared; adjusting a test point selection scheme according to a speed and position updating rule of the particle swarm, executing genetic algorithm operation after updating the particle swarm algorithm, and performing selection-crossover-mutation on a population after updating the particle swarm; setting a stagnation restart mechanism to divide the fitness of the test points; and when the number of iterations reaches the maximum number of iterations, outputting the optimal test point set and the current detection rate and isolation rate.

The invention belongs to the technical field of terminal testing, and particularly relates to a mobile intelligent terminal compatibility testing method which comprises the following steps: S1, aggregating terminal hardware configuration, software environment and network state data through federal learning, and constructing a real-time testing matrix; s2, synthesizing an edge scene test case based on the generative adversarial network; s3, synchronously collecting a touch track, a display frame rate and an audio synchronization deviation, and quantifying user interaction experience in combination with eye tracker data; s4, deploying a lightweight virtualization intermediate layer between the gap / Android / iOS, automatically converting an equipment interconnection instruction, and verifying cross-chain compatibility; and S5, tracking the privacy data flow by adopting dynamic taint analysis, and detecting illegal behaviors in real time. According to the method, through dynamic environment modeling, real-time test matrix construction and hierarchical aggregation architecture, terminal nodes encrypt and upload local data by using differential privacy and homomorphic encryption technologies, so that the security of the data is ensured.

This application discloses an automated testing method and system based on matrix switching. The method includes: establishing an internal communication connection for the system; issuing a switching command to the microcontroller based on the acquired current test pin; the microcontroller parsing the switching command, pulling down all control pins electrically connected to the relay test matrix, and after a preset safety dead time, pulling up the corresponding control pins to close the target test path; executing a zero-point calibration process after the target test path is turned on, and acquiring the dynamic current offset of the target test path; the host computer dynamically adjusting the test voltage output by the programmable voltage source to obtain real current data; after the test is completed, the host computer automatically generates a test report containing a standardized IV characteristic curve. This application balances safety, versatility, high precision, and high efficiency through flexible reconstruction of matrix switching, "disconnect-then-connect" safety timing, precise calibration of dynamic zero points, and fully automated report generation.

A system for diagnostic screening of a chronic disease includes a test matrix and a user device. The test matrix has a calibration surface including one or more calibration elements and one or more reagents. The user device has image capturing and processing capabilities configured to capture an image and a processor configured to locate, based on the plurality of calibration elements, the test matrix in the image, determine if the test matrix indicates the presence of the chronic disease by comparing a detected contrast of the one or more reagents with the test matrix to an augmented reality trained database, and generate a screening report based on the determination.

The application belongs to the technical field of semiconductor chip testing, and particularly relates to a test matrix instant stop method based on target result triggering, which is suitable for a test matrix scene, and realizes instant termination of a test process by relying on a preset hardware signal line designed by connecting a pull-up resistor to Vcc and comprises the following steps: S1, a pre-test configuration stage, S2, a test matrix preparation execution stage, S3, a test matrix execution stage, and S4, an instant stop stage. A flexible configuration mechanism of test target event registration and stop event binding is constructed, and a special hardware signal line of connecting a pull-up resistor to Vcc is matched to realize global synchronous triggering and stopping across a board card, the traditional fixed sequence test mode is abandoned, and the core problems of executing redundant test items after a test target is achieved in the prior art, causing invalid consumption of test time and equipment resources, and lacking of unified synchronous stopping capability in multi-board card cooperative testing and high parallel / multi-station test period being greatly lengthened are solved.

The present disclosure provides a training method of a chemical genetic toxicity prediction model, which can be applied to the technical field of chemical environmental health risk assessment. The training method of the chemical genetic toxicity prediction model comprises: obtaining original data about chemicals with known genetic toxicity, wherein the original data comprises chemical codes of the chemicals, differential gene expression data of the chemicals, and in vitro high-throughput test data of the chemicals; generating a training sample data set according to the original data, wherein the training sample data set comprises an atomic feature matrix, a connection relationship matrix, a differential gene expression matrix, an in vitro high-throughput test matrix, and label information of the chemicals; and training an initial model using the training sample data set to obtain a chemical genetic toxicity prediction model. The present disclosure also provides a prediction method of chemical genetic toxicity.

A non-transitory computer readable medium and related method includes processing circuitry that executes an ordered error correction code construct. The processing circuitry receives a first plurality of matrices. The processing circuitry is to generate a second plurality of matrices based on the at least one additive candidate matrix and each respective matrix of the first plurality of matrices. The processing circuitry then generates a third plurality of matrices based on the at least one additive test matrix and each respective matrix of the second plurality of matrices. Each respective weight indicating a respective scalability of each matrix in the second plurality of matrices is determined based on the third plurality of matrices. The processing circuitry then selects at least one matrix from the second plurality of matrices based on the determined weights. The processing circuitry then generates an error correction code based on one of the at least one selected matrix.

The invention provides a circular water film-based low-pressure nozzle impact performance optimization method, which comprises the following steps of: establishing a coordinate system by taking a jet flow impact point as an original point, and selecting at least four parameters from geometric parameter vectors of a nozzle to construct a joint objective function, the combined target value adopts a weighted product form of stagnation point pressure, water film area and jet flow hitting power; constructing a test matrix, changing at least four geometric parameters at the same time, and obtaining multi-dimensional response data of the joint target value through numerical simulation; building an explicit second-order model of the joint target value by using multivariate nonlinear regression; performing global optimization by adopting a genetic algorithm or a response surface method, and outputting an optimal geometric parameter combination which maximizes the joint target value; the improved nozzle is obtained through machining according to the optimal geometric parameter combination; and if the hitting power coefficient of the improved nozzle is greater than that of the original nozzle, the optimization is completed. According to the method, parallel search can be carried out in a multi-dimensional parameter space, and the optimization period is remarkably shortened.

The invention discloses a short message sending optimization system based on big data, and relates to the technical field of big data marketing, and the system comprises a compliance pre-verification module, a multi-version content generation module, a space-time test matrix construction module, a dynamic flow distribution module, and a strategy decision feedback module. The method comprises the following steps of: screening user portrait features, accurately selecting features with high correlation with a short message response rate by applying a Pearson's correlation coefficient, dividing a target user group into K homogeneous groups, strictly verifying internal homogeneity and inter-group heterogeneity of the groups, and on the basis, mapping each group user to a test unit matrix according to a proportion; and the consistency between the sample feature distribution and the target group is verified by calculating the feature statistics, so that the sample of the test unit can be ensured to represent the target group to the maximum extent, and the data on which the subsequent strategy decision feedback module depends is more representative and scientific.

The purpose of this invention is to provide a method for formulating an airworthiness compliance verification test matrix. By employing a joint machine learning model and an iterative test dataset, the prediction accuracy of the machine learning model on the test set is used as an indicator. The test dataset is continuously updated until the prediction accuracy meets the indicator, and the set of training operating points is output as the airworthiness compliance verification test matrix for aero-engines. This ensures that the airworthiness compliance verification test matrix can cover the vibration characteristics of the blades throughout the entire flight envelope. This method for formulating an airworthiness compliance verification test matrix can reduce the number of test operating conditions while obtaining the dynamic stress response of the engine blades throughout the declared flight envelope.

This invention discloses a big data-based SMS sending optimization system, belonging to the field of big data marketing technology. The system includes: a compliance pre-verification module, a multi-version content generation module, a spatiotemporal test matrix construction module, a dynamic traffic allocation module, and a strategy decision feedback module. In terms of user grouping and traffic allocation, this invention uses user profile feature screening and Pearson correlation coefficient to accurately select features highly correlated with SMS response rate, dividing the target user group into K homogeneous groups and rigorously verifying the internal homogeneity and inter-group heterogeneity of the groups. On this basis, each group of users is mapped to a test unit matrix proportionally, and the consistency between the sample feature distribution and the target group is verified by calculating feature statistics. This ensures that the samples of the test units represent the target group to the greatest extent, making the data relied upon by the subsequent strategy decision feedback module more representative and scientific.

The embodiment of the invention discloses a multi-environment adaptive front-end automatic testing method and device and a medium, and relates to the technical field of automatic testing, and the method comprises the steps: receiving an automatic testing request, obtaining environment configuration data from a multi-environment configuration center according to the automatic testing request, so as to generate a multi-environment adaptive testing matrix, the test matrix comprises a plurality of test scenes, and each test scene is associated with a scene identifier, a test step and an expected result; for each test scene in the test matrix, obtaining DOM structural features of the current test environment through a test script adaptive engine, and dynamically adjusting the test script according to the DOM structural features and environment type parameters of the current test environment to determine an adjusted test script; and executing a test by using the adjustment test script, comparing the environment consistency verification data of the same operation in different test environments, and generating a cross-environment difference report based on the environment consistency verification data.

The invention belongs to the field of structural strength design of composite materials, and particularly relates to a thermal damage comparison detection method for a composite material. The method comprises the following steps: planning a thermal damage test matrix, wherein the test matrix comprises a plurality of different combinations of thermal damage temperatures and thermal damage time; performing a thermal damage test on the composite material standard test piece; measuring the porosity and one or more residual mechanical properties of each standard test piece subjected to the thermal damage test; establishing a corresponding relation database among the thermal damage temperature, the thermal damage time, the porosity and the residual mechanical properties; measuring the porosity of the actual composite material structure to be evaluated; the measured actual porosity is compared with the corresponding relation database, and the thermal damage degree and / or the residual mechanical property of the actual composite material structure are / is determined. The method provides a scientific and reliable basis for thermal damage assessment and maintenance decision of the composite material structure.

This invention discloses a method for selecting test points for flowmeter devices based on an optimized test matrix. It collects multiphase flow parameters and test points under different conditions as training and testing data, establishing a model combining artificial neural networks and genetic algorithms. The performance of the neural network is reflected in the mean square error of the training results. An intelligent learning algorithm is used to optimize the test evaluation matrix, reducing the selection of duplicate test points, maximizing test point coverage, and achieving automatic test point selection. This reduces the influence of human factors and allows for more targeted analysis of factors affecting flowmeter measurement performance, improving the reliability of flowmeter test evaluation. This invention makes the evaluation of standard devices more intelligent and digital, resulting in more scientific and reasonable test evaluation results.

The application discloses a boundary scan test matrix generation method based on heuristic search, which comprises the following steps: firstly, counting the number of networks in the measured circuit board and calculating the normalized distance between any two networks; then, calculating the short-circuit probability between the networks through the normalized distance between any two networks, so as to construct a short-circuit probability matrix between the networks; then, setting a test matrix and generating a plurality of row test matrices according to the test matrix; finally, searching for the test matrix with the minimum cost through the establishment of a search tree based on the test cost and the heuristic function value.

The invention relates to the technical field of automobile engineering and artificial intelligence crossing, and discloses an AI training dataset construction method for a constraint system simulation model, which comprises the following steps of: performing modular division and simplification on the constraint system simulation model to obtain simplified part sub-modules; performing parameterization setting, establishing a parameterization subsystem embedding basic model, defining key parameters and a value range, and generating a test matrix containing multiple groups of parameter combinations; then generating a CAE parameterized model of multiple groups of different parameter combinations through a space distance measurement and in-vehicle space and constraint system parameter batch modification method; and finally, reproducing a collision test passenger response by using the parameterized model, and obtaining damage data to construct a data set. According to the method, the coverage, uniformity and quality of the data set are improved, the cost is reduced, support is provided for AI passenger injury prediction, and the passive safety research and development efficiency of the automobile is improved.

The embodiment of the invention provides an Ethernet protocol test method and device, a medium and a product. The method comprises the following steps: sending a service message to a tested device, and obtaining a service response message returned by the tested device; determining a service mapping table of the tested equipment based on the service response message, and constructing a corresponding test matrix based on the service mapping table; configuring an Ethernet protocol test strategy corresponding to the tested device based on the test matrix, and sending a test message to the tested device based on the Ethernet protocol test strategy; and determining an Ethernet protocol test report of the tested equipment based on a test response message corresponding to the test message. The method is used for guaranteeing the comprehensiveness of Ethernet protocol testing, avoiding redundant operation and effectively guaranteeing the compatibility and stability of vehicle-mounted Ethernet communication.

The invention discloses a confrontation sample generation and robustness automatic verification system for an industrial visual inspection model, and the system comprises four core modules: a confrontation sample generation module, a three-dimensional test matrix construction module, a robustness automatic evaluation module, and an improved report generation module, and an optional closed-loop iterative optimization module. The method comprises the following steps: generating a high-fidelity adversarial sample of which the SSIM is greater than or equal to 0.85 and the PSNR is greater than or equal to 25dB through the synergy of a generative adversarial network (CGAN / DCGAN) and a physical imaging model containing illumination, noise and shielding simulation; a full-dimension test matrix is constructed by'defect type-imaging condition-interference intensity ', and indexes such as mAP and omission ratio are automatically calculated and visually presented; and outputting an improved report containing weak link analysis, parameter adjustment and sample supplement suggestions, and supporting'generation-evaluation-optimization 'closed-loop iteration. The system is compatible with a mainstream framework model, is suitable for various industrial detection scenes, can shorten the model verification period by more than 70%, improves the mAP by 8-12%, significantly reduces the missing detection / false detection rate, and guarantees the reliable landing of the model industrial scene.

The application provides a kind of rail transit vehicle composite material structure virtual analysis method and system, belong to rail transit technical field.The virtual method includes: according to the basic provision made to the physical and mechanical characteristics of rail transit structure characteristics and composite material, virtual model establishment rule method, material parameter characterization acquisition method and test matrix, load boundary application method, virtual model checking method, strength analysis process, result output and result evaluation.The application realizes the virtual analysis verification and output evaluation of rail transit composite material structure, solves the problem of low result simulation precision of large composite material rail transit equipment, verifies the accuracy to reach the engineering requirement, effectively increases the one-time passing probability of full-size strength test, reduces the development test cost.