880 results about "Analytical Testing" patented technology

The invention relates to the technical field of cable asset management and fault prediction, and discloses a cable fault positioning method based on deep learning clustering analysis test waveform characteristics, and the method comprises the steps: collecting waveform and environment data in a cable operation period, and constructing a historical feature library comprising waveform, environment and position features; a self-adaptive detection model is adopted, and parameters are dynamically adjusted to adapt to different working conditions; multi-dimensional feature fusion and matching analysis are combined; a fault point distance is calculated through a signal propagation model and a time difference positioning algorithm, precise positioning is realized by fusing environment compensation and multi-point cross validation, and a three-dimensional geographic coordinate is generated by combining a laying path; and after multiple verifications, a structured report containing a fault type, a risk level, a prediction position, confidence and operation and maintenance suggestions is generated. According to the system, intelligent monitoring, fault risk prediction, asset optimization management and operation and maintenance decision support of a cable operation state are realized, and scientificity and economy of cable management in a complex environment are improved.

The invention relates to the technical field of software testing, in particular to a self-adaptive software testing environment configuration method and system.The method comprises the steps that before software testing is started, a sensing layer analyzes testing requirements through a prediction model, and a preliminary environment configuration scheme is generated by analyzing codes, configuration, requirement documents and historical data; the containerization and virtualization management module creates a virtual machine and deploys applications according to the scheme, the SDN control module sets network topology and strategies, and the automatic configuration module executes environment establishment; in the testing process, a dynamic monitoring module monitors resource use in real time and feeds back the resource use to a decision-making layer based on a data interaction protocol, a test demand perception prediction model in the decision-making layer generates a resource adjustment strategy and a network optimization strategy based on monitoring data, and a test strategy and a case execution sequence are dynamically adjusted. And the optimization feedback module evaluates the environment configuration effectiveness and transmits the environment configuration effectiveness to the decision-making layer for adjustment. According to the invention, the beneficial technical effect of a more efficient, accurate and reliable software testing process is realized.

The invention relates to the technical field of storage batteries, in particular to a storage battery monitoring, detection, treatment and evaluation integrated system and a storage battery management method, and the system comprises a plurality of accompanying modules, a collection power distribution control module, a storage battery management capacity checking host and a remote platform; the internal resistance analysis test of the system is based on multi-frequency-point alternating current excitation (0.5 Hz-7. 5kHz), a complex impedance spectrum of not less than 20 frequency points can be constructed, and the internal polarization characteristics of the battery are analyzed; the system adopts a feed network type discharge capacity checking, so that discharge electric energy is fed back to a power grid, and the capacity detection precision is improved to 98%; according to the system, EIS data and an LSTM neural network are fused, and a battery state of health (SOH) prediction model is established; the system is based on a DSP digital power supply technology, and can realize 50A active equalization topology.

The invention provides an automatic software testing method and system based on artificial intelligence. The method comprises the following steps: analyzing a software demand document by using an NLP technology, converting the software demand document into structured data, extracting a key function point, and identifying a software function point; generating a test case covering all function points through a deep learning model in combination with historical test data training; automatically executing a test operation, analyzing a test result, analyzing a test log by using a machine learning algorithm, identifying and classifying potential defects by using a data mining and pattern recognition technology, and generating a repair suggestion report; and analyzing feedback data in the test process, dynamically adjusting a strategy according to a test result by using a reinforcement learning algorithm, and optimizing a test case and the strategy. According to the invention, intelligent analysis of test data, automatic generation of test cases and automatic execution of a test process are realized; flexible configuration and expansion can be carried out according to the actual condition of software; the test efficiency and quality are improved, and the test cost and manpower consumption are reduced.

The invention discloses an automatic test method based on natural language processing, which comprises the following steps: S1, generating a test case: performing semantic analysis on a software requirement document or a test requirement by utilizing a natural language processing technology, extracting key information, and combining the extracted test information and a preset test case template to generate a test case; a preliminary test case is automatically generated; the key information comprises a test purpose, an operation step and an expected result; s2, analyzing the test case; s3, generating a test script; s4, executing the test script; and S5, analyzing a test result. According to the automatic test method based on natural language processing, the test requirements described by the natural language can be automatically analyzed, the test case is generated, the test is automatically executed, and the test report is finally generated, so that the software test efficiency is improved, the workload of manually compiling and executing the test case is reduced, and the test efficiency is improved. And the coverage rate and the accuracy of the test are improved, more software defects can be found, and the quality of software products is guaranteed.

The invention discloses a method for testing the content of platinum in a platinum compound solution, and belongs to the technical field of analytical testing. According to the test method, an ammonium chloride precipitation gravimetric method is replaced by a hydrogen reduction gravimetric method, platinum ions in a platinum compound solution are reduced into elemental platinum in a hydrogen reduction mode, and the content of platinum in the solution is calculated by weighing the weight of a reduced platinum sinter and subtracting the content of impurity elements in the platinum sinter at the same time. According to the method, the platinum content in the platinum compound solution can be accurately and quantitatively analyzed, the operation process is simple, good repeatability is achieved, the range of multiple analysis results of the same sample is smaller than or equal to 0.05% and is far lower than the repeatability limit 0.2% of a national standard method, the analysis accuracy is guaranteed, and meanwhile the analysis efficiency is greatly improved.

The invention belongs to the technical field of PCB testing, and discloses a performance testing method of an AI server PCB. Comprising the following steps: acquiring power-on operation temperature data of the PCB to construct a temperature distribution image, determining hot spot region characteristics based on the temperature distribution image to obtain heating test parameters, performing heating test on the PCB based on the heating test parameters, acquiring thermal resistance of each position of a hot spot region, drawing a thermal resistance characteristic curve, and analyzing the thermal resistance characteristic curve to obtain a thermal performance grade of the PCB. The bending rate of the bending test is determined according to the basic parameters of the PCB, the bending force is adjusted in real time according to the bending rate during the test, the test is stopped when the stress or the strain reaches a threshold value, the test data is analyzed to obtain the bending resistance grade of the PCB, and the PCB is divided into different grades by combining the thermal performance grade. According to the method, the efficiency and reliability of PCB testing are remarkably improved.

A microfluidic device for analysing a test liquid comprises: a sensor provided in a sensing chamber; a sensing chamber inlet channel and a sensing chamber outlet channel, each connecting to the sensing chamber for respectively passing liquid into and out of the sensing chamber, and a reservoir forming a sample input port to the microfluidic device, the reservoir being in fluid communication with the sensing chamber inlet channel; a liquid collection channel; a barrier between an end of the sensing chamber outlet channel and the liquid collection channel; a first seal, covering the sample input port; a second seal, covering the end of the sensing chamber outlet channel, thereby preventing liquid from flowing from the sensing chamber, over the barrier, into the liquid collection channel; wherein the microfluidic device is filled with a liquid from the first seal at the sample input port to the second seal at the end of the sensing chamber outlet channel, such that the sensor is covered by liquid and unexposed to a gas or gas / liquid interface; and wherein the first and second seals are removable to cause the liquid to flow between the reservoir and the end of the sensing chamber outlet and over the barrier.

The invention relates to a data processing method and device, electronic equipment, a storage medium and an automobile, and relates to the field of data processing.The method comprises the steps that when terminal equipment is in communication connection with the automobile, an Ethernet original message is obtained from the automobile; extracting a real-time protocol message from the Ethernet original message; extracting theme information from the real-time protocol message; determining a message type corresponding to the real-time protocol message; and when determining that the real-time protocol message is valid data according to the theme information, analyzing the real-time protocol message according to the message type and a preset user-defined standard file to obtain an analysis result. According to the invention, real-time analysis of the DDS data is realized, and the analysis and test efficiency of test personnel on the DDS data is greatly improved.

The invention relates to the technical field of encoder operation and maintenance management, in particular to an absolute value encoder operation error analysis method and system, which are used for more accurately identifying whether a specific source causing an error is an internal equipment problem or an external environment factor through environment external cause influence exclusion analysis; the method is applied to an encoder operation monitoring system, an error analysis instruction is generated when the encoder operation monitoring system monitors that an absolute value encoder has an error, and the method comprises the following steps: in response to the error analysis instruction, analyzing the error analysis instruction to obtain an error analysis result; obtaining an absolute value encoder address, an absolute value encoder model and an error analysis time window which need to be subjected to error analysis; configuring an error analysis test strategy based on the absolute value encoder model and the absolute value encoder address; and testing in the error analysis time window based on the error analysis test strategy, and comprehensively evaluating a test result to obtain a first error test result.

The invention relates to a low-code application automatic test system and method based on machine learning, and the method comprises the following key steps: firstly, receiving a test demand of a low-code application, and obtaining an interface element graph; secondly, processing the interface element graph through an image processing and semantic recognition technology, and extracting an interface model; then, automatically generating and executing a test case according to the interface model, and collecting test result data; and finally, analyzing test result data and generating a detailed test report. The invention further relates to construction and use of a framework recognition network and a text extraction network to accurately recognize the category of interface elements and text meanings, and test data are deeply analyzed through clustering analysis and a decision tree algorithm, so that abnormal modes, error reasons and paths are effectively recognized. The method can be widely applied to the field of software development, in particular to application testing of a low-code platform, and the software quality and the testing efficiency are improved.

The invention relates to the technical field of data storage, and discloses a solid state disk total write-in data volume testing method, which comprises the following steps of: initializing a testing environment and self-adaptive parameter configuration of a solid state disk; creating a plurality of parallel data acquisition threads, acquiring test data through the data acquisition threads, and storing the acquired test data into a database; establishing a preset health degree evaluation model, analyzing the collected test data in real time according to a preset health degree index system, dynamically adjusting a test load based on a dynamic acceleration stress model and according to the real-time state of the solid state disk, executing a corresponding test operation according to an adjustment result, and recording a test result; and analyzing the test result, and automatically generating a test report according to the analysis result. According to the method, the dynamic acceleration stress model is introduced, so that the test load is dynamically adjusted according to the real-time state of the SSD, and the test efficiency and accuracy are improved.

The invention belongs to the technical field of material forming and mold design, and provides a mold flow analysis method and system for a plastic mold, and the method comprises the steps: carrying out N times of mold flow analysis tests on the plastic mold to obtain melt filling data, carrying out processing analysis on the melt filling data to obtain a filling completion value, comparing the filling completion value with a filling completion threshold value to generate an analysis signal, acquiring monitoring data during melt filling, analyzing and processing based on the monitoring data to obtain a filling performance value, comparing the filling performance value with a filling performance threshold value to generate an adjustment signal, and adjusting the melt based on the adjustment signal. The melt filling time and the injection pressure value are processed to obtain a filling influence variance, the filling influence variance is compared with a filling influence variance threshold value, if the filling influence variance is smaller than the filling influence variance threshold value, it is indicated that the abnormal injection pressure value is the reason for insufficient melt filling, and according to the filling influence ratio and melt filling time analysis, the abnormal injection pressure value is the reason for insufficient melt filling. And obtaining an injection pressure adjustment value.

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 large language models, provides an automatic flight simulator interface code generation method, system and device based on a large language model and a storage medium, and solves the problems of low generation efficiency, poor accuracy and poor system adaptability of flight target interface codes. The method comprises the steps of obtaining interface data of multiple external devices of a flight target, and converting the interface data into structured input data after noise filtering and key information extraction; deeply analyzing the data by using a deep learning and semantic understanding algorithm, extracting key semantic information and generating an interface code template; instantiating the template content in combination with the example data and the interaction rule to generate a target code; generating a multi-scene test case based on a test case algorithm, and verifying code correctness, stability and performance; testing and performance results are comprehensively analyzed, model parameters and training data are dynamically adjusted, and closed-loop automatic code generation is achieved. According to the method, the generation efficiency, accuracy and system adaptability of the flight target interface code are improved.

The invention provides a circuit board test method and device based on a flying probe tester. According to the method, a test point set is determined by obtaining a design file of a circuit board, establishing an electrical connection model and identifying components and pins on the circuit board. And generating test combination set data by analyzing the conduction relationship between the test points, and further generating test scheme data. And based on the test scheme data, a test path is generated by using a path optimization algorithm, finally, the flying probe tester is used for testing, and a test report is generated according to a test result. The flying probe tester adopts the combination of an annular probe and a sharp needle probe, the annular probe is used for a pin connector to ensure accurate contact, and the sharp needle probe is used for other types of components to improve the test precision and adaptability. Compared with a traditional test method, the test scheme can be generated more efficiently, the test path can be optimized more efficiently, the test time is remarkably shortened, and the reliability and accuracy of circuit board testing are improved.

The invention relates to a method for evaluating the cyclic adsorption performance of a carbon dioxide adsorbent, which comprises the following steps: S1, performing multiple adsorption and desorption tests on a to-be-tested adsorbent after impurity removal treatment in a thermogravimetric analyzer to obtain a thermogravimetric cycle curve; s2, parameters E1, F1, Hi and Ii are obtained according to the thermogravimetric cycle curve and a formula; s3, obtaining a first fitting curve and a second fitting curve; s4, evaluating the performance of the adsorbent to be tested according to one or more of E1, Ei, H2, I2, F1, Fi, the first fitting curve function and the second fitting curve function. By adopting the method, a relatively standard evaluation method for evaluating the performance of the adsorbent based on the thermogravimetric analysis test can be established, a plurality of adsorbents can be qualitatively analyzed by selecting proper parameters according to actual use conditions, proper adsorbents are selected by comparing qualitative analysis results, and the method is wide in use range and high in applicability.

The invention provides a risk analysis method and system for software project management, and relates to the technical field of software project management. The method comprises the following steps: collecting test record data of a target software project and a target test resource allocation strategy; extracting defect density features and test coverage features respectively corresponding to the plurality of functional modules; obtaining system architecture data of the target software project, and constructing a module association map of the target software project about the plurality of functional modules; generating a plurality of resource allocation influence indexes of each functional module, and processing through the resource allocation association analysis model to generate a reference allocation strategy of the target software project; and performing resource allocation risk analysis on the target test resource allocation strategy through the reference allocation strategy, and generating a risk analysis result of the target software project about the target test resource allocation strategy. According to the invention, the potential risk of the test resource allocation strategy is accurately analyzed.

The invention provides a rock mineral analysis test management method and system, and the method comprises the steps: collecting rock mineral sample multi-modal data, and constructing a digital twinborn model; constructing a geological knowledge map, and injecting and fusing the two knowledge to generate a virtual test data set; performing self-supervision pre-training by using the data set to obtain a self-adaptive mineral phase recognition model; deploying the model to a block chain-Internet of Things double-chain traceability system to obtain an identification result and an optimization instruction; and executing a sample preparation process and removing unqualified samples. According to the method, diffusion steps are adjusted through adaptive noise scheduling and a space-time alignment algorithm, data are integrated, a high-reality-sense virtual test data set is generated, and a self-supervised pre-training and knowledge distillation technology is combined, so that the model has space-time feature extraction and dynamic optimization capabilities; and finally, full-process closed-loop control is realized through a double-chain traceability system and a modular robot, and the recognition precision of a complex scene is improved.

An object is to provide a liquid chemical exhibiting excellent defect inhibitive performance even in a case of being applied to a resist process by KrF excimer laser exposure and ArF excimer laser exposure. Another object is to provide a method for analyzing a test target solution and a method for producing a liquid chemical.A liquid chemical includes an organic solvent; and metal-containing particles containing a metal atom and having a particle size of 10 to 100 nm, in which the number of the metal-containing particles contained is 1.0×10−2 to 1.0×1012 particles / cm3.

This item is a mouthpiece for a personal tester (personal testing device), and is a mouthpiece for a personal tester that has the function of detecting, measuring, analyzing, and testing, for example, breath (alcohol), biological information, intoxicants, drugs, etc.

The invention discloses a differential lock comprehensive testing device, relates to the technical field of automobile power assembly detection, solves the problems that manual differential lock testing is troublesome in operation and inaccurate in testing result, adopts a material conveying line body and a material carrying table to convey a differential lock to a jacking assembly, and utilizes a robot carrying assembly to clamp and move the differential lock to a bearing table. A shell of the differential lock is limited, then the test piece moves downwards until the spline rod is inserted into the differential lock, the spline rod is connected with one half shaft gear, then the drive motor drives the shell of the differential lock to operate, meanwhile, the hysteresis brake gives out test load force, and a planetary gear in the differential lock is limited; detection can be carried out through the torque sensor and the pressure sensor, obtained data are transmitted to the control system in the electric cabinet to be recorded and analyzed, carrying is carried out through the robot carrying assembly after testing is completed, manual carrying and testing are not needed in the whole operation process, and therefore the problems that manual testing of the differential lock is troublesome in operation and inaccurate in testing result are solved.

To provide a system capable of streamlining generation of delivery messages and delivery images in official account operation and providing effective messages and images.SOLUTION: A data processing system includes a data processing device 12 and a smart device 14, where a specific processing unit 290 of the data processing device 12 uses an AI module to generate delivery messages and delivery images. Then, an AB test is performed in order to verify effectiveness of the generated delivery messages. Further, results of the AB test are analyzed, and messages and images with high response rates are selected.SELECTED DRAWING: Figure 2

The embodiment of the invention provides an RTL parallel test method and system for an RISC-V DSP chip and a medium, and the method comprises the steps: obtaining a plurality of test items, classifying the plurality of test items based on a classification rule, and obtaining different types of test items; constructing a plurality of test channels based on an RTL test framework, and obtaining test parameter information of each test channel; matching different types of test items with the test parameters of each test channel to obtain a matching degree, and judging whether the matching degree is greater than or equal to a set matching degree threshold; if yes, the corresponding test channel is matched, and if not, unmatched test items are shielded through the test channel; testing the plurality of test items in parallel according to the matched test channels; the test items are classified by analyzing the categories of the test items, and different test items select different test channels, so that parallel testing of different categories of test items is realized, and the test efficiency is improved.

The present disclosure relates to a static cone penetration test device. The device includes a housing, an optical window and a friction cylinder coaxially connected. Light sources are mounted in the optical window and a static cone penetration assembly is disposed in the friction cylinder to detect a resistance the device suffers when the device is pressed into soil. An optical fiber sensor, a wireless transceiver, a data processing chip and a power supply are disposed in the housing. The optical fiber sensor is used to receive the reflected light of a target object and output spatial position information and spectrum information. The wireless transceiver is used to upload test data and receive a control signal. The data processing chip is used to analyze the test data. The present disclosure has the advantages of compact structure, high spectral resolution, quick imaging speed, and strong immunity to interference.

The invention discloses a detection system of a PCB (Printed Circuit Board). The detection system comprises PCB detection equipment, a data storage module and analysis and test equipment, the PCB detection equipment is used for acquiring current detection data of a to-be-detected PCB according to a preset detection index of the PCB and uploading the current detection data to the data storage module; the preset detection indexes of the PCB comprise the types and the number of the components, the positions and the resistance directions of the preset components, the plugging directions of the direct plugging components, the welding spots of the components and the board surface of the PCB; the data storage module is used for storing current test data, historical test data of the PCB, scoring standards and scores; the analysis test equipment comprises an abnormality diagnosis module used for determining the current abnormal data of the PCB to be tested according to the current test data; and the scoring module is used for obtaining the score of the tested PCB according to the current abnormal data and the scoring standard, so that the detection of the PCB can be automatically completed.

The invention relates to the technical field of automated testing, and discloses an automated testing method, device and equipment based on an embedded Linux system gateway machine and a storage medium, the method comprises the steps that an automated testing script is generated by using a Bash script language, a testing process, testing parameters, a testing instruction and result judgment logic are defined in the automated testing script, and the result judgment logic is stored in the Bash script; various operations under actual working conditions are simulated, and test results are automatically recorded and analyzed; based on the automatic test script, a cross-platform graphical programming language is used, module testing is conducted on the functions of the gateway machine to be tested, and simultaneous testing of different test items is achieved. According to the method, the gateway machine can be comprehensively, efficiently and accurately tested through the execution of the automatic test software based on the written automatic test software.

The invention relates to a battery pack fault detection method and system and an electric vehicle. The battery pack fault detection method and system and the electric vehicle are simple in structure and ingenious in design, and the safety performance of a battery pack can be effectively improved. The state of the battery pack can be comprehensively known by monitoring the total voltage, the monomer voltage, the temperature and the current in real time; by screening out the battery cells with abnormal temperature, voltage or current and then diagnosing and analyzing whether the abnormal battery cells are subjected to micro short circuit, the abnormal battery cells can be quickly identified, unnecessary inspection on normal battery cells is reduced, and the detection efficiency is improved; battery faults can be comprehensively detected through a physical model, machine learning, time sequence analysis, ICA testing and EIS testing, and the accuracy and reliability of detection are further improved; according to the method, the safety and reliability of the battery pack are improved, the intelligent level of the battery management system is enhanced, and better use experience is provided for a user of the electric vehicle.

The invention provides an automatic management interaction method, system and device of a whole vehicle software version and a medium, and relates to the technical field of vehicle software engineering.According to the method, functions of version monitoring, change analysis, test management and version management are provided through an integrated main interface, and a user can check the software version state and tasks to be done in real time; and performing multi-dimensional version comparison and risk assessment to generate a detailed change and risk report. In addition, the method supports configuration of a test strategy, execution of an automatic test and generation of a test report and a defect positioning list, and the test efficiency and accuracy are effectively improved. And in the aspect of version management, the whole process operation from creation to release is realized, the timeline and historical report of the whole life cycle can be displayed, and the transparency and traceability of version control are ensured. On the whole, the method effectively improves the efficiency and reliability of whole vehicle software version management, simplifies the operation process, and enables the version control to be more efficient, more accurate and easier to manage.

The invention provides a fluorescent / photo-thermal dual-mode sensor constructed based on an entropy-driven DNA molecular machine as well as a construction method and application of the fluorescent / photo-thermal dual-mode sensor, and belongs to the technical field of sensor construction and analytical testing. The fluorescent / photo-thermal dual-mode sensor is constructed on the basis of Ag (at) Au NPRs with good photo-thermal performance, CdTe QDs with strong fluorescence signals, a Fe3O4 (at) SiO2 nano material with superparamagnetism and an entropy-driven DNA molecular machine signal amplification strategy capable of being specifically combined with miRNA; the fluorescence detection range of the fluorescence / photo-thermal dual-mode sensor is 1 fM to 50 pM, the detection limit is 0.34 fM, the photo-thermal detection range is 1 pM to 1 nM, and the detection limit is 0.5 pM; the fluorescent / photo-thermal dual-mode sensor is simple in construction method, convenient and rapid in detection and high in selectivity, has very good practicability and has very good application in miRNA detection.