365 results about "Dynamic testing" patented technology

The invention relates to the technical field of edge computing, electric automobile testing and the like, and provides an electric automobile instrument testing method based on end-cloud collaboration, which comprises the following steps of: constructing a lightweight virtualized resource isolation environment at an edge computing node, loading signal generation, communication agency and state monitoring micro-service; a test platform with elastic capacity expansion and contraction and fault self-recovery capability is formed; historical test data are collected at a cloud end, and an equipment health degree prediction model is trained and deployed to an edge node to support a local intelligent test; constructing a dynamic test service chain, generating and pre-distorting and compensating an enhanced test signal, and then acting the enhanced test signal on the instrument; through multi-modal signal acquisition and unified preprocessing, in combination with wavelet packet decomposition and a deep neural network, high-dimensional feature extraction is realized, a test report containing a health trend is finally output, and a test process is actively intervened based on a trend prediction result. According to the method, the authenticity of test signals, the health assessment precision and the safety and efficiency of the test process are effectively improved.

The invention discloses an automatic test case generation method and system based on a large model, and the method comprises the steps: multi-modal data fusion: receiving a natural language demand, a UML design drawing, an API document, a historical defect log and system monitoring data, aligning text and image features through a CLIP model, analyzing the interface constraint through CodeBERT, and carrying out the multi-modal data fusion; feature fusion is realized by adopting a cross-modal attention mechanism; a dynamic test scene modeling step: constructing an environment simulator based on reinforcement learning, and simulating high-concurrency, distributed abnormal and other complex scenes; and a layered test case generation step: generating a function test case, a boundary test case and an increment test case through GPT-4, GAN and LSTM respectively, and introducing an entropy evaluation model to quantify the effectiveness of the cases. According to the method, the multi-modal data is brought into the test case generation process for the first time, the test case generation time is shortened by 80%, the complex scene coverage rate is increased to 95%, the semantic matching degree reaches 92%, and the intelligent level and efficiency of software testing are remarkably improved.

The invention discloses a knowledge extraction and envelope coverage-oriented software vulnerability test method and related equipment, and the method comprises the steps: obtaining vulnerability key information of target software, and obtaining sensitive function features through defect dependence analysis and construction based on the vulnerability key information; performing semantic analysis on the analysis report and the code abstract associated with the sensitive function characteristics, screening to obtain a target sensitive function, performing path envelope reverse tracking on the target sensitive function, and constructing to obtain a target path envelope; and obtaining coverage information enveloped by the target path, and carrying out fuzzy testing on the basis of the coverage information in combination with the iteratively optimized variation sample. According to the method, through intelligent closed loop of analysis-positioning-testing-feedback-optimization, static analysis provides accurate guidance for dynamic testing, and the static analysis strategy is inversely optimized by the result of the dynamic testing, so that the maximum improvement of the testing efficiency and the vulnerability discovery accuracy is realized in limited testing resources, and the testing efficiency and the vulnerability discovery accuracy are improved. The method can be widely applied to the technical field of software security.

The invention relates to an automatic driving intelligent safety multi-task dynamic test system based on a Carla simulation platform, and belongs to the field of artificial intelligence safety and automatic driving simulation test. The system comprises an automatic driving perception model integration and training module which comprises a multi-task data collection module, a fine tuning perception model and a compilation perception model Carla API interface; the attack and defense algorithm integration and training module is used for finely adjusting an attack and defense algorithm, writing an attack and defense algorithm Carla API (Application Program Interface) and replacing Carla object textures with an adversarial patch; and the real-time attack and defense deduction and evaluation recording module comprises a sensor for acquiring Carla real-time data, replacing textures, starting a perception model and starting an evaluation record of the success rate and the accuracy rate of defense and attack. According to the method, the robustness of the automatic driving perception model in a complex attack scene can be comprehensively evaluated, security holes of a perception system can be found in time, and the reliability and the security of an automatic driving technology in a complex environment are improved.

The invention relates to the technical field of radiator monitoring, and particularly discloses a radiator heat dissipation performance dynamic test system, which is characterized in that a heat source simulation body is arranged on a heat transfer interface of a radiator, and a high-fidelity dynamic electric power load is applied to the heat source simulation body to simulate an actual working condition; radiating a microwave detection signal to a space where the heat source simulator is located and receiving a multi-path scattering response signal; the three-dimensional dielectric constant dynamic distribution of the heat source simulation body is reconstructed by solving the inverse scattering problem fused with the space-time constraint; according to the material dielectric constant-temperature relation mapping, three-dimensional temperature field dynamic distribution is generated; and finally, intelligently identifying and extracting a migration track and a temperature change curve of the highest temperature point in the space from the continuous time sequence temperature field data, and taking the migration track and the temperature change curve as a direct evaluation basis for the dynamic heat dissipation performance of the radiator. According to the method, lossless, full-field, real-time visualization and quantitative analysis of the migration process of the dynamic hot spots in the hidden heat source are realized, and the authenticity of the dynamic heat test is improved.

The invention provides an intelligent code generation method based on collaborative arrangement of a multi-source knowledge graph and a large model, and the method comprises the steps: uniformly converting the structured and semi-structured business information of multiple sources into a knowledge graph G after conflict resolution, converting a user demand into a structured intention object, and combining with the knowledge graph G after conflict resolution, thereby achieving the intelligent code generation. The method comprises the following steps: constructing a sub-task list, cooperatively driving a plurality of large language models to generate module-level codes according to sub-tasks t in the sub-task list T and initial contexts of the sub-tasks t, performing static check, dynamic test and business consistency check on generated candidate codes O, and generating a feedback prompt F to correct a Prompt template if the detection is not successful. And calling the corrected Prompt template for iteration through a large language model to realize end-to-end automatic generation from a demand intention to front and back end codes, interface documents and deployment scripts, and ensuring generation quality and business consistency through a closed-loop mechanism of ''graph driving-semantic reasoning-check feedback''.

The invention discloses a test system and method for generating capability evaluation based on a large model, and the method comprises the steps: S1, carrying out threat modeling, and generating a test case, including classifying a threat scene and generating an automatic test case, the generation content of the test case including generation of an adversarial sample and generation of a privacy test case; s2, a multi-dimensional test is executed, the multi-dimensional test comprises a dynamic test engine and real-time defense detection, and test indexes of the dynamic test engine comprise a sensitive information leakage rate, a malicious instruction execution rate and a prejudice index; s3, performing vulnerability diagnosis, including analyzing attention weight and tracing privacy leakage; and S4, performing verification and iterative repair, including collecting vulnerability samples, performing mixed training, adjusting a loss function and performing regression testing. Through threat modeling and attack scene classification, various potential attacks can be identified and covered, test comprehensiveness is ensured, neglected potential safety hazards can be found, and test effectiveness is improved.

The invention relates to the technical field of energy testing, in particular to a self-adaptive dynamic energy testing method based on combined heat and power generation, which comprises the following steps: constructing a thermoelectric coupling transfer model and a working condition identification model, and inputting power generation power and heat supply power into the thermoelectric coupling transfer model to correct model parameters, inputting the environmental parameters into a working condition recognition model, recognizing a current working condition type based on a preset working condition feature library, calling an initial test scheme from a test scheme library according to the current working condition type, and generating a dynamic test scheme through a machine learning algorithm in combination with the parameters corrected by the thermoelectric coupling transfer model; and controlling the test equipment to execute a test based on the dynamic test scheme, collecting test data in real time, calculating a system performance index according to the test data, comparing the system performance index with a preset threshold value, and generating feedback information for adjusting the test scheme. Therefore, the problems that in the prior art, a test scheme is fixed and cannot adapt to complex working conditions, and performance evaluation is incomplete are solved.

The invention belongs to the technical field of compressor performance prediction, and particularly provides a method and system for determining a surge judgment critical value of a compressor based on multi-source data fusion. Comprising the steps that a compressor surge test system is built and operated, and a first surge critical value is calculated; obtaining multi-source historical data related to surge of the compressor, selecting characteristic variables to construct historical input vectors, and fitting the multiple regression model by using the historical input vectors to obtain a discrimination model; training the machine learning model to obtain a trained machine learning model; a real-time input vector is constructed based on data, collected in real time, of the to-be-monitored compressor, and then a second surge critical value and a third surge critical value are obtained; and fusing the first surge critical value, the second surge critical value and the third surge critical value to obtain a predicted surge critical value of the to-be-monitored compressor. According to the method, high-precision dynamic testing and historical data regression analysis are combined, and the actual value of the surge critical value is finally and quantitatively determined through multi-parameter coupling measurement and data mining.

The invention relates to the technical field of data processing, in particular to a linear motor positioning precision dynamic test and analysis method, which comprises the following steps of: controlling a linear motor to perform full-stroke reciprocating constant-speed scanning, synchronous high-frequency acquisition of positions, current instructions and speed data; resampling according to a fixed position interval space to generate forward and reverse current and speed sequences; utilizing the characteristic that the friction force directions are opposite to counteract the friction component, calculating the resistance characteristic value of each position by combining the two-way speed stability weight, and constructing a resistance topographic map; the magnetic cogging effect and the mechanical anomaly are decoupled through the space gradient and the statistical deviation, and the mechanical anomaly saliency is determined; and a current feed-forward compensation table is generated and written into a driver, and a fault is marked for a saliency threshold exceeding position, so that dynamic testing and analysis of positioning precision are realized. According to the method, the resistance component is accurately separated by combining the current algebraic operation and the bidirectional speed weight, the topographic map is constructed to decouple the tooth socket and the installation abnormity, and the dynamic test precision and the diagnosis practicability are improved.

The invention discloses a method for testing an electric power steering system assembly, and belongs to the technical field of automobile part testing. The technical problems that in an existing testing method, static and dynamic testing processes are separated, testing efficiency is low, and quantitative evaluation on key dynamic performance parameters is difficult are solved. According to the invention, a test tool comprising a simulation rack, a driving device, an encoder, a torque sensor and a data acquisition card is adopted, and a control and processing module automatically executes a continuous test process: firstly, performing a static assistance test on an assembly, and judging qualification; and if the test is qualified, the test is automatically switched to dynamic test, a torque command signal is sent to the assembly, an output shaft is driven to rotate forwards and backwards, a position and a feedback torque signal are collected, and dynamic response parameters such as a position dispersion error, power-assisted delay time and overshoot are calculated. The method is mainly used for comprehensive performance testing and quality evaluation of the electric power steering system assembly in the production manufacturing or maintenance after-sales link.

The invention discloses a real-time dynamic test optimization method for an embedded environment compiler, which belongs to the technical field of embedded systems and comprises the following steps of: acquiring and processing real-time dynamic data of the embedded environment compiler, and determining real-time dynamic characteristic data of the embedded environment compiler; building a real-time dynamic test identification model of the embedded environment compiler, analyzing the real-time dynamic characteristic data of the embedded environment compiler, automatically identifying potential defects of the embedded system, and determining a real-time dynamic test identification result of the embedded environment compiler; and formulating an embedded system optimization scheme to optimize the embedded system in time. The problems that the running test state of the embedded environment compiler cannot be dynamically monitored and analyzed, potential defects cannot be found and optimized in time, and the running efficiency of an embedded system is reduced in the prior art are solved. According to the method, the running test state of the embedded environment compiler can be dynamically monitored and analyzed, potential defects can be found and optimized in time, and the running efficiency of an embedded system is improved.

The invention relates to the technical field of asteroid simulant testing, and discloses an asteroid simulant spinning process dynamic testing device and a testing method.The asteroid simulant spinning process dynamic testing device comprises a fixed table, a rotating table, a driving assembly, five telescopic assemblies and a measuring plate, the rotating table is rotationally arranged on the surface of the fixed table, and the driving assembly is arranged in the fixed table; five telescopic rods are further arranged on the surface of the rotating table, a measuring plate is arranged at the telescopic end of the telescopic assembly, and a measuring sensor facing the asteroid simulant is arranged in the measuring plate; the five telescopic assemblies and the measuring plate are arranged on the surface of the rotating table, the measuring plate corresponds to the asteroid simulant, and a measuring sensor in the measuring plate is matched, so that synchronous acquisition of three-dimensional axial dynamic deformation data and multi-dimensional measurement covering the periphery and the top of the asteroid simulant can be realized; therefore, a three-axis length and time relation curve of the simulant at different rotation rates and a time-varying curve of the flattening and elongated ellipsoid eccentricity rate are accurately obtained.

The invention discloses a tire high-speed uniformity dynamic test method, device and equipment under multi-axis excitation, and relates to the technical field of vehicles. The tire high-speed uniformity dynamic test method under multi-axis excitation comprises the steps that a tire is installed on a test bed with a rotary drum, the test bed is controlled to apply lateral excitation to the tire according to multiple lateral displacements, a high-speed uniformity dynamic test is carried out, and a first test result is obtained; according to the plurality of longitudinal slip rates, controlling the test bed to apply longitudinal excitation to the tire and perform high-speed uniformity dynamic test to obtain a second test result; according to a plurality of composite parameters obtained by combining a plurality of lateral displacements and a plurality of longitudinal slip rates in pairs, controlling the test bed to apply composite excitation to the tire and perform high-speed uniformity dynamic test to obtain a third test result; and summarizing the three test results to obtain a high-speed uniformity dynamic test result of the tire. According to the method, the high-speed uniformity performance of the tire under the complex working condition can be evaluated more comprehensively.

The invention particularly relates to an exciter virtualization-based airborne application software simulation running environment construction method, which comprises the following steps of: carrying out digital packaging on an operating system interface to realize virtualization running of an embedded real-time operating system; digitally packaging communication interfaces such as a 1553B bus, an ARINC429 bus, discrete magnitude and the like so as to reproduce real avionics communication characteristics in a virtual environment; and simulating a peripheral software and signal interaction process so as to realize virtual generation and response of the multi-source excitation signal. By constructing the simulation running environment, the dynamic test of the airborne embedded software can be carried out under the condition of no real hardware, so that the test sample space is expanded, the test coverage rate and sufficiency are improved, the design and execution efficiency of a dynamic test case is improved, repeated manual operation is reduced, the test cost of the airborne embedded software is reduced, and the test efficiency of the airborne embedded software is improved. The economic benefit is improved.

The invention provides a Beidou satellite navigation positioning terminal dynamic test system and method, and the system comprises a power divider which is connected with a high-precision navigation positioning antenna, and is connected with a standard global satellite navigation system high-precision positioning terminal and a tested Beidou satellite navigation positioning terminal at the same time. The signal receiving module is used for enabling the standard global satellite navigation system high-precision positioning terminal and the detected Beidou satellite navigation positioning terminal to receive consistent satellite navigation signals; the post-data resolving and processing computer is used for being connected with the standard global satellite navigation system high-precision positioning terminal and the tested Beidou satellite navigation positioning terminal and receiving and obtaining test data of the standard global satellite navigation system high-precision positioning terminal and the tested Beidou satellite navigation positioning terminal. And post-resolving processing is carried out based on the test data. The system is simple in structure, easy to deploy, reliable in test result and suitable for a dynamic test scene, and the positioning precision and the test efficiency are remarkably improved.

The invention discloses a clutch torque transmission characteristic dynamic test method, and relates to the field of clutch control, and the method comprises the steps: building a test bench, and separating a clutch, the transmission is put into a direct gear; presetting working condition parameters, wherein the working condition parameters comprise an output dynamometer target rotating speed N, an input dynamometer target rotating speed N and a clutch actuator target initial position P; obtaining a preset target torque loading strategy; according to the preset target torque loading strategy, the current position of a clutch actuator is controlled, a clutch friction pair is made to move relatively, and meanwhile test data are collected; acquiring a preset temperature threshold value; according to the test data, whether the clutch reaches a preset temperature threshold value or not is judged; if not, continuing to execute the preset target torque loading strategy; if yes, acquiring a target test position, and generating test data of the target test position; and preprocessing the test data according to the target test position test data, and generating an all-position test result.

The invention discloses an automatic test system of a power driving chip, and particularly relates to the technical field of automatic test, which comprises a dynamic test control module, a multi-level parallel test module, an abnormal power detection module and a safety verification diagnosis module. Based on cooperative work of a programmable electronic load and a digital signal processor, the dynamic response capability of a chip under different working conditions is verified, abnormal power data under an extreme load condition is generated, electrical parameters and thermal parameters of the chip are synchronously collected, the relevance between abnormal power performance and temperature is analyzed, and the abnormal power performance is analyzed. Temperature rise differences caused by power-off protection and electric leakage are distinguished, abnormal power waveforms are extracted and classified so as to distinguish power-off protection and electric leakage events, the influence degree of environmental charge interference is quantified, finally, response effectiveness of a chip protection circuit in a strong charge environment caused by electric leakage is simulated, and calibration is performed according to a collected correction value. Therefore, the automation degree of the system is improved, and the test robustness is enhanced.

The invention discloses an electromobile electromagnetic compatibility testing device, and relates to the technical field of electromagnetic compatibility testing, the electromobile electromagnetic compatibility testing device comprises a shielding box, the upper side of the shielding box is fixedly connected with a control box, and one side of the control box is provided with a manipulator used for clamping an electromobile motor to go in and out of the shielding box; one side of the manipulator is provided with an opening and closing mechanism used for opening and closing the entrance, the lower side of the control box is slidably connected with a load simulation circuit box used for regulating and controlling a power supply and emitting high-energy pulses through a circuit, and one side of the load simulation circuit box is fixedly connected with a second handle. One side of the second handle is provided with a wiring terminal, and the wiring terminal is fixedly connected with the load simulation circuit box. A dynamic test platform capable of highly simulating a real world complex scene is created, and the tested motor is driven to move along a U-shaped track in the shielding box through a precise mechanical structure; and working conditions such as straight running, steering and backing of the vehicle can be accurately reproduced.

A CNN dynamic test case automatic generation method based on meta-learning guidance comprises the following steps: constructing a hybrid test architecture which decouples the whole system into two logic levels: a static knowledge base and a dynamic exploration engine; according to the static knowledge base, a global'vulnerability map 'is constructed by performing one-time and comprehensive offline static analysis on a tested network DUT, the dynamic exploration engine is composed of a guide network and a generative network, the engine performs coevolution under the guidance of the'vulnerability map', and the dynamic exploration engine performs dynamic exploration on the DUT. The task of the method is to carry out efficient targeted exploration with a clear target and scene synthesis in a fragile area marked on a map. According to the method, data dependence is broken through, unknown risks are explored, and seamless integration with an agile development (MLOps) process is achieved.

The invention belongs to the technical field of identity recognition, and particularly relates to an identity recognition method and system based on cross-domain multi-modal fusion dynamic footprints. Collecting plantar pressure data of a subject, wherein the plantar pressure data comprises a static footprint original pressure image and a dynamic continuous pressure frame sequence; preprocessing the plantar pressure data; constructing a dynamic footprint segment fusion image; training the preprocessed paragraph data through an image modal branch network and an action modal branch network to respectively obtain a static segment-level logarithm value and a dynamic segment-level logarithm value; jointly calibrating temperature scaling parameters, gating thresholds and fusion weights of the image modal branch network and the action modal branch network on the verification set, mapping segment-level logarithm values of the two branches into calibrated posterior probabilities, performing adaptive weighting according to confidence and distribution consistency to obtain a segment-level fusion result, executing individual-level aggregation, and obtaining a segment-level fusion result; and obtaining a final identity recognition result. And high-precision identity recognition under the conditions of static training and dynamic testing is realized.

The invention discloses an autonomous evolution type 5G protocol fuzzy test system based on a large language model, and the system comprises a protocol extraction unit which employs the large language model to analyze a 5G protocol specification document, and extracts structured protocol knowledge elements containing a message format, state machine logic and parameter constraints; the vulnerability analysis unit generates a potential vulnerability description list through big language model reasoning based on the knowledge elements; the test strategy generation unit drives a large language model to generate a targeted test case based on protocol knowledge, vulnerability description and historical test knowledge in the dynamic test knowledge base; the test execution unit executes the use case and captures a result; and feeding back an analysis result of the internalization unit, extracting a causal rule, generating new test knowledge and feeding back the new test knowledge to the knowledge base. According to the system disclosed by the invention, test targets and resources can be autonomously scheduled according to continuous updating of the knowledge base, so that the test process has an iterative optimization capability, and full-process automation and intelligentization of 5G protocol fuzzy testing are realized.

The invention belongs to the technical field of computers, and particularly relates to a dynamically configured cockpit host video test multiplexing method. The method aims at solving the problems that a traditional testing means is poor in universality, incomplete in coverage and low in automation degree. A structural equipment description file is constructed by analyzing a host technical document, an adaptive dynamic test configuration template is automatically generated in combination with a test case library, and flexible configuration of multi-channel video stream parameters, abnormal injection modes and time sequence logic is supported. A containerized virtual signal source is deployed on a universal computing platform, and an analog video stream conforming to an input specification is generated in real time. Through the equipment description driving and virtualization signal generation technology, the multiplexing capability and coverage integrity of the testing system are improved, efficient and automatic testing of multiple types of hosts is achieved, and the hardware cost and the deployment period are remarkably reduced.

The invention discloses a data leakage detection method and device, computer equipment and a storage medium, belongs to the technical field of data security, and is applied to sensitive data detection of a financial system or a health medical system. Firstly, the authenticity and complexity of a test sample are remarkably improved, various scenes such as format change, field splitting, encryption processing, noise interference and semantic camouflage are covered, and a complex attack environment can be effectively simulated; secondly, an adaptive field mapping and dynamic test template mechanism is introduced, so that test data can be flexibly adjusted according to different service scenes or detection products, and the test efficiency and scene adaptability are improved; and finally, through presetting various machine learning algorithms, automatically training to generate a high-precision sensitive data classifier, and realizing accurate identification of sensitive fields in unknown data. According to the method, a set of end-to-end sensitive data detection and evaluation framework capable of being automatically executed is constructed, and the method has the technical advantages of high efficiency, flexibility and intellectualization.

The invention relates to the technical field of folding screen testing, and discloses a reliability testing method and system for a folding screen mobile phone. The system comprises a test partition decision module, a dynamic test strategy module, an abnormal response analysis module and an adaptive enhancement module. The test partition decision module obtains physical structure parameters and historical deformation data of the folding screen and divides the folding screen into a screen center flexible area, a hinge stress concentration area and an edge packaging area; the dynamic test strategy module generates current and target test strength levels for each test partition; the abnormal response analysis module calculates the partition test deviation degree according to the target and actual test strength grade difference; the adaptive enhancement module generates a predicted test strength level for a next test period based on the test deviation and historical test data. The system can improve the test accuracy and efficiency, and meets the reliability test requirements of each region of the folding screen.

The invention discloses a liquid cooling plate testing method, a liquid cooling plate testing device and electronic equipment, and relates to the technical field of heat dissipation performance testing. The liquid cooling plate test method comprises the following steps: taking dynamic heat and / or dynamic pressure during operation of electronic equipment as a to-be-simulated environment, controlling an environment simulation module to construct the to-be-simulated environment to form a dynamic test environment, and controlling a monitoring assembly to monitor a to-be-tested liquid cooling plate in the dynamic test environment, and obtaining a performance parameter combination of the to-be-tested liquid cooling plate in the dynamic test environment. The technical problem that it is difficult to effectively evaluate the performance of the liquid cooling plate due to solidification of a liquid cooling plate test mode is solved, the dynamic test environment is constructed by taking the operation environment of the electronic equipment as the to-be-simulated environment, the performance of the to-be-tested liquid cooling plate in the dynamic test environment can be collected, the reliability of the test result of the liquid cooling plate can be facilitated, and the test efficiency is improved. And the evaluation reliability of the heat dissipation performance of the liquid cooling plate based on the test result can be improved.

A dynamic test publication framework for software development updates can be used to reliably publish test results. A variety of test tools can be used to design and execute a series of software tests for a given software update. An interface can be used to communicate the tests results to one or more producing components. The producing components can stream test results data objects, which can be stored in a queue. The queue can persistently store the test data objects and dynamically scale so that the dynamic test publication framework as a whole can reliably publish test results. A publisher can iteratively receive the queued test results data objects and publish them to a test evidencing platform. In some implementations, components of the dynamic test publication framework can independently and dynamically scale based the observed state of the dynamic test publication framework and / or the test evidencing platform.

The application relates to the technical field of folding screen testing, and discloses a reliability test method and system for a folding screen mobile phone. The system comprises a test partition decision module, a dynamic test strategy module, an abnormal response analysis module and a self-adaptive reinforcement module. The test partition decision module acquires folding screen physical structure parameters and historical deformation data, and divides a screen center flexible area, a hinge stress concentration area and an edge packaging area; the dynamic test strategy module generates current and target test intensity levels for each test partition; the abnormal response analysis module calculates a partition test deviation degree according to the difference between the target and actual test intensity levels; and the self-adaptive reinforcement module generates a predicted test intensity level for the next test cycle based on the test deviation degree and historical test data. The system can improve test accuracy and efficiency, and adapt to the reliability test requirements of various areas of the folding screen.

The invention discloses a composite energy storage offline dynamic test system and test method. The system comprises a flywheel energy storage unit, a compressed air energy storage unit, an energy management and cooperative control unit and a data acquisition and analysis unit. The flywheel energy storage unit is used for simulating dynamic working conditions of a power grid; the compressed air energy storage unit is used for executing charging and discharging and multi-mode operation under the dynamic power grid working condition simulated by the flywheel energy storage unit; the energy management and cooperative control unit is used for coordinately controlling energy interaction and operation modes of the flywheel energy storage unit and the compressed air energy storage unit according to a preset test target and working condition data; and the data acquisition and analysis unit is used for acquiring and synchronously recording key operation parameters of the energy storage unit in the test process in real time, and performing anomaly detection to generate a performance test report. A flywheel energy storage unit is used as a programmable virtual power grid, and an energy management and control algorithm is combined, so that high-precision off-line testing of a compressed air energy storage unit under a complex dynamic working condition is realized.

The invention belongs to the technical field of databases, and relates to a vector database evaluation method and system based on mixed search and a readable medium, and the method comprises the steps: generating multi-modal test data oriented to multiple application scenes according to a real data set; constructing a mixed query task capable of controlling the selection rate and the query correlation; according to the multi-modal test data, aiming at the mixed query task, loading a pre-calculated vector neighbor result, and realizing dynamic test of different selection rates and relevance in a vector database; key performance indexes of the vector database are calculated through dynamic testing, and the vector database is evaluated according to the key performance indexes. The method solves the problems of unreal data distribution, too simple hybrid query tasks and the like, greatly reduces the labor cost of vector database evaluation, improves the database performance analysis efficiency, and accelerates database performance evaluation, optimization and model selection of research institutions and enterprises.