54 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 invention provides an abnormity identification method and device for an electric drive axle of a vehicle, electronic equipment and a medium, and the method comprises the steps: obtaining the operation data of the electric drive axle of the vehicle under a plurality of operation conditions, the operation data comprising the detection data of each motor of the electric drive axle at each sampling time point under each operation condition; based on the acquired operation data, constructing a test matrix corresponding to the electric drive bridge; extracting operation data under the target operation condition from the test matrix to form a test sub-matrix; for each column in the test sub-matrix, determining whether each detection data of the column falls into a normal cluster, the normal cluster being determined based on sample detection data of the motor corresponding to the column under the target operation condition; and based on the number of the detection data falling into the corresponding normal cluster, identifying whether the electrically driven bridge is abnormal or not. According to the invention, the abnormity identification of the electric drive bridge is realized.

The invention discloses a method for automatically testing the real-time performance of a PreemptRT kernel. The method comprises the following steps of: pre-configuring a mirror image package and a test tool set of the PreemptRT kernel for a central control node to complete environment preparation; mirror image package deployment and remote environment configuration of a to-be-tested PreemptRT kernel are carried out on the to-be-tested equipment through the central control node; generating a test matrix of the to-be-tested equipment according to the test strategy, and calling the test tool set to test the to-be-tested equipment according to the test matrix to obtain a test result; and analyzing the test result through the central control node to obtain a key index of the PreemptRT kernel to be tested, and further determining whether the performance of the PreemptRT kernel to be tested is improved or not. According to the invention, the whole process of environment preparation, kernel deployment, test execution, parameter tuning and result analysis can be automatically completed, and rapid and accurate evaluation of the real-time performance change of the PreemptRT kernel is realized.

The present application relates to the field of intelligent temperature control technology, specifically to a method, device, and system for controlling the temperature of large-volume fan foundation concrete. The method comprises: acquiring temperature data at each preset location at each preset depth within the fan foundation in real time; acquiring a linear eigenvector at each acquisition moment; comprehensively analyzing the changing trends of the temperature data at each preset location at each acquisition moment and all previous acquisition moments to acquire a cumulative trend test matrix at each acquisition moment; acquiring a stratified monitoring difference coefficient at each acquisition moment; and acquiring an error adjustment matrix at each acquisition moment by analyzing the difference between the temperature data at each preset location at each acquisition moment and a preset standard temperature, and combining the distribution of the stratified monitoring difference coefficients at each acquisition moment and all previous acquisition moments; thereby controlling the temperature of the fan foundation concrete. The present application aims to improve the accuracy of temperature control of large-volume fan foundation concrete.

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 relates to the technical field of high-temperature testing systems, in particular to a high-temperature testing system for maintaining the temperature of a circulating system in an internal and external circulation mode, which comprises a bottom plate, a product testing system integrally arranged on the bottom plate, and a high-temperature circulating system butted with the product testing system, the product testing system comprises a testing base body, a lower needle disc plate installed on the testing base body, a product testing plate installed on the lower needle disc plate and a testing pressure bar jig which is in butt joint with the lower needle disc plate and can be opened upwards, and a testing bin with the open left side and the open right side is formed between the testing pressure bar jig and the testing base body. An internal circulation system is arranged by ingeniously utilizing the first three-way regulating valve and the second three-way regulating valve in combination with the valve assembly, heat can be recycled in the system in the product taking and placing process, the situation that a large amount of cold air is reheated to recover the temperature of a test bin like a traditional system is not needed, energy consumption is greatly reduced, and cost is reduced. And the production cost is reduced.

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 network card stability test method and system, and the method comprises the steps: constructing a flow test matrix according to preset flow test parameters, and carrying out the port test parameter extension processing of the flow test matrix, and obtaining a dynamic asymmetric flow test scene set; performing a network card load test according to the dynamic asymmetric flow test scene set, and acquiring network card performance data to obtain a performance index data set; according to the performance index data set, performing multi-stage verification test and signal analysis on the network card to obtain collapse point feature description; and obtaining a network card asymmetric flow stability evaluation report through multi-dimensional data analysis and visualization processing according to the crash point feature description. According to the invention, through construction of a dynamic asymmetric flow test scene, multi-stage verification test and multi-dimensional data analysis, comprehensive test and evaluation of the stability of the network card in a complex asymmetric flow environment are realized.

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 present invention relates to the technical field of vehicle chassis system performance optimization, and in particular to a method for optimizing the mechanical properties of a leaf spring suspension, comprising the following steps: S1: establishing a finite element analysis model of a leaf spring suspension based on CAE technology, and verifying the accuracy and effectiveness of the finite element analysis model of the leaf spring suspension. S2: performing simulation analysis under a double full load condition to determine the optimization target. S3: combining the mechanical design theory of the leaf spring suspension, constructing a three-factor three-level test matrix, obtaining significant influencing factors, and determining the optimal parameter range of the significant influencing factors. S4: establishing a Kriging prediction model in combination with the Kriging interpolation algorithm, and using a genetic algorithm for multi-objective optimization to obtain the optimal parameter combination of the three factors. The advantage of the present invention is that a Kriging prediction model of the objective function of the leaf spring suspension is constructed based on the Kriging interpolation algorithm, and a genetic algorithm is used for multi-objective optimization to obtain the optimal structural parameter combination. The mechanical performance of the optimized leaf spring suspension is significantly improved.

The invention relates to the technical field of vehicle chassis system performance optimization, in particular to a plate spring suspension mechanical property optimization method which comprises the following steps: S1, establishing a finite element analysis model of a plate spring suspension based on a CAE technology, and verifying the accuracy and effectiveness of the finite element analysis model of the plate spring suspension; and S2, performing simulation analysis under a double full-load working condition, and determining an optimization target. S3, a three-factor three-level test matrix is constructed in combination with the mechanical design theory of the plate spring suspension, significance influence factors are obtained, and the optimal parameter interval of the significance influence factors is determined. And S4, establishing a Kriging prediction model in combination with a Kriging interpolation algorithm, and performing multi-objective optimization by adopting a genetic algorithm to obtain an optimal parameter combination of three factors. The method has the advantages that the Kriging prediction model of the target function of the leaf spring suspension is constructed based on the Kriging interpolation algorithm, the genetic algorithm is adopted for multi-target optimization, and the optimal structure parameter combination is obtained. The mechanical property of the optimized plate spring suspension is remarkably improved.

The invention is suitable for the technical field of engine performance calibration, and provides an engine transient performance optimization calibration method based on response curved surface design, comprising the following steps: setting decision variables and target variables to construct an experimental matrix; performing experimental test according to the test matrix; fitting and evaluating a quadratic model; performing simplified selection on the fitting model; performing prediction optimization calculation and experimental verification; and performing all-condition Map calibration according to the rotating speed range. The method can be practically applied to transient performance optimization in the research and development test process of the engine, the performance of the engine in the real vehicle running process can be optimized, the validity of test data is visually displayed through a mathematical model, and excessive test resources are not needed.

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 discloses an adsorption performance evaluation method and device of an oxygen production molecular sieve, and relates to the technical field of gas adsorption separation, the method comprises the following steps: obtaining an environmental influence parameter set of oxygen adsorption and purification of the oxygen production molecular sieve, and constructing a multi-parameter space; randomly generating a first environment influence parameter group in the space, and performing iterative search, adjustment and cross update to obtain a plurality of environment parameter groups; carrying out an adsorption test based on the parameter groups to obtain an adsorption test parameter set; carrying out maximization and standardization processing on the data, constructing an adsorption test matrix and calculating scores; and calculating an adsorption performance evaluation result of the oxygen production molecular sieve according to the plurality of scores, and giving a weight according to the actual frequency and the search frequency of the environment parameter group and the deviation between the environment parameter group and the preset parameter group for final calculation. Therefore, the technical effects of improving the flexibility of the evaluation process and improving the reference value of the evaluation result are achieved.

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.