1399 results about "Test report" patented technology

The invention relates to the technical field of data processing, and discloses a steel structure welding seam quality ultrasonic detection method and system. The method comprises the following steps: scanning a welding seam to obtain digital parameters, constructing a virtual model to generate an ultrasonic response database, optimizing a detection parameter forming scheme, executing distributed acquisition to obtain a signal matrix, extracting defect features by using a neural network, and outputting a digital detection report through transfer learning. According to the method, automatic optimization of detection parameters and accurate extraction and intelligent analysis of defect features are realized, the accuracy, efficiency and reliability of detection are improved, and the dependence on artificial experience is reduced.

The invention discloses an unmanned aerial vehicle electric power inspection image intelligent analysis method and system based on deep learning and multi-modal fusion and a medium thereof, and relates to the technical field of electric power equipment detection. The method comprises the following steps: planning an optimal inspection path by adopting an A * algorithm to realize multi-sensor synchronous data acquisition; adaptive histogram equalization and defogging processing are carried out on the visible light image, non-uniformity correction and temperature calibration are carried out on the infrared image, and filtering and registration are carried out on point cloud data; constructing a multi-scale feature fusion network based on improved VGGNet-16, and introducing deformable convolution and a cross-modal attention mechanism to realize multi-source data fusion; defect detection is carried out based on a three-level template library and a feature map cross-correlation algorithm, and the precision is improved in combination with non-maximum suppression and sub-pixel positioning; and finally generating a detection report containing defect types, positions and maintenance suggestions. According to the invention, the automation level and the detection precision of power inspection are obviously improved.

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

The invention discloses a salt mist airflow field prediction method and system in an ocean atmospheric environment, and relates to the technical field of ocean wind power plant salt mist corrosion trend prediction.The system divides a wind power plant into a plurality of salt mist monitoring areas, collects environmental data, constructs a salt mist airflow field model by adopting three-dimensional modeling and CFD simulation, and obtains the salt mist corrosion trend of the wind power plant. A digital twinborn model is generated through multi-physics field coupling, and dynamic deduction is carried out; constructing an AI corrosion prediction model by using historical data and simulated deduction data, extracting a corrosion risk feature vector FCV, and performing dynamic training to predict a corrosion trend; salt mist concentration and wind speed data are monitored in real time, a corrosion coefficient is calculated and compared with a threshold value for analysis, and a corresponding protection strategy is formulated; in combination with real-time data and digital twinborn deduction, evaluating a wind-driven salt mist coupling deposition risk, triggering early warning and optimizing a strategy; and a test report is automatically generated, future test parameters are optimized through an AI prediction model, and the corrosion resistance and the operation efficiency of the wind turbine are improved.

The invention discloses an integrated verification and test system and method for complex rules of a substation monitoring system, and the system comprises a rule editing module which provides a visual interface to support a user to edit the complex rules containing various types of variables and time sequence constraints; the analysis and verification module is used for performing grammar, variable conflict and business compliance multi-level verification on the rules; the intelligent test case generation module is used for automatically generating test cases covering normal, boundary and abnormal conditions based on the rule tree structure; the simulation test interface module converts the use case into a standard test script, submits the standard test script to a simulation tool for execution, and outputs the standard test script to a monitoring system through protocol conversion; the result analysis module is used for comparing an execution result with an expected result and generating a structured test report; according to the invention, full-process automation of rule verification and testing is realized, the verification efficiency is remarkably improved, and the test requirements of various transformer substation business scenes are met.

The invention relates to an AI server cooling water pump vibration quantity self-adaptive calibration test method and system, an intelligent test platform integrates a six-dimensional force sensor and a temperature compensation vibration exciter, the platform rigidity is automatically calibrated, a water pump-pipeline system transfer function is obtained, and a rotating speed-lift-modal frequency three-dimensional mathematical model is established; a three-axis MEMS accelerometer array is arranged at sensitive parts such as a water pump bearing seat and a motor shell, and vibration, current and pressure signals are synchronously collected; carrying out time-frequency domain signal processing by adopting variational mode decomposition in combination with self-adaptive S transformation, and extracting a 128-dimensional full-frequency domain feature vector containing a modulation side frequency band; effective values of vibration acceleration, speed and displacement are calculated through a frequency domain integration algorithm, and current harmonic interference is corrected through an electromagnetic vibration compensation model; and finally, a vibration health degree evaluation model containing 18 characteristic parameters is established based on a support vector machine, the test system comprises an intelligent test platform unit, a multi-source sensing unit, an edge calculation unit and a data management unit, and microsecond-level synchronous acquisition and GB-level data throughput are realized through a time sensitive network. And online incremental learning and automatic generation of a test report are supported. The method has the effect of improving the water pump vibration quantity test precision.

The invention discloses a hospital project intelligent management and collaborative operation optimization system based on an AI algorithm technology, and the system comprises a multi-modal data collection module which is used for obtaining hospital operation data, medical equipment data, patient vital sign data and medical staff operation records in real time; the data fusion engine, the dynamic resource scheduling module, the risk prediction unit and the collaborative work platform provide intelligent task distribution, conflict detection and emergency plan generation functions; the self-adaptive optimization controller is used for continuously updating system parameters through an online learning mechanism; the method breaks through the limitation of traditional single-mode data processing, constructs a cross-department data association model through a graph neural network, integrates heterogeneous data sources such as radiation images, inspection reports and equipment logs, realizes dynamic mapping of diagnosis and treatment paths and resource states, introduces a space-time attention mechanism, and improves the diagnosis and treatment efficiency. Equipment operation cycle characteristics and patient movement tracks are subjected to combined modeling, so that the sensing precision of the system is improved to a minute level.

The invention relates to the technical field of electrical variable testing, in particular to a high-precision performance testing processing method and system for a low-impedance voltage transformer. The method comprises the following steps: constructing a controllable test excitation signal, and synchronously collecting a corresponding primary side voltage and a secondary side voltage of a mutual inductor; space electromagnetism elimination is carried out according to the primary side voltage and the secondary side voltage of the mutual inductor, and frequency domain characteristic decomposition and signal instantaneous offset calculation are carried out at the same time, so that a mutual inductor signal characteristic matrix is constructed; acquiring environment parameters corresponding to the low-impedance voltage transformer; constructing a neural network model based on Bayesian optimization, and predicting and outputting a performance parameter set corresponding to frequency response and load characteristics; and comparing the performance parameter set with a preset standard threshold value, feeding back, generating a calibration compensation coefficient, testing and evaluating, and generating a high-precision performance test report corresponding to the low-impedance voltage transformer. According to the invention, high-precision performance testing of the low-impedance voltage transformer can be realized.

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

Disclosed herein are system, method, and computer program product embodiments for detecting anomalies during software testing. The methods include generating a plurality of test reports for the software program by executing one or more test cases on a plurality of versions of the software program, generating a control chart based on the plurality of test reports, generating an alert when at least one testing characteristic includes an anomaly over the plurality of versions of the software program as determined based on the control chart. The control chart includes a plot associated with at least one testing characteristic of the software program, and a historical context associated with execution of the one or more test cases on the plurality of versions of the software program.

The invention discloses a graphical user interface test case generation method based on a multi-agent framework, and relates to the field of graphical user interface tests.The graphical user interface test case generation method based on the multi-agent framework comprises the following steps that S1, a user demand document is obtained, and file text content and file format information are analyzed and extracted; s2, performing paragraph segmentation on the file text content to form logic semantic units; s3, carrying out correlation analysis on the segmented paragraphs, and obtaining a ternary file group; s4, performing paragraph annotation addition on the ternary file group, and constructing a semantic annotation result set; s5, extracting the agent framework to generate a graphical user interface test case, performing test recording, and storing a test result; s6, the result is verified, and a test case list and a software test report are generated. By conducting multi-dimensional analysis on the text content and the format structure in the document, the reduction efficiency from natural language description to structural semantic construction is improved.

The invention relates to artificial intelligence generation content AIGC, in particular to an AIGC test case self-adaptive generation system based on risk feedback, which comprises a semantic variation generation module for selecting a variation operator from a variation operator library according to a self-adaptive strategy, performing variation processing on a seed case provided by a basic test case library by using the variation operator, and generating a semantic variation result; generating a new test case; the AIGC model takes the test case as model input and performs model output to the risk assessment and quantification module through an AIGC model interface; the risk assessment and quantification module is used for performing multi-dimensional risk assessment on a model output result by utilizing the risk detection model library, calculating a risk level and generating a test report; the risk feedback processing module is used for storing the high-risk test case, performing feature extraction and converting a risk assessment result into an operable risk feedback signal according to extracted features; according to the technical scheme provided by the invention, the defects of low efficiency and difficulty in automatically adapting to environment change can be overcome.

The invention belongs to the technical field of cloud computing and software testing, and particularly discloses an automatic fault injection and recovery testing method based on cloud native, which comprises the following steps: acquiring test basic data of a to-be-tested cloud native system; constructing a fault test execution model according to the test basic data; according to the fault test execution model, executing an automatic fault injection operation; generating an abnormal alarm log according to the system running state after the fault injection operation, and synchronously recording a fault injection operation log; according to the abnormal alarm log, executing automatic fault recovery operation; and generating a fault test report according to the fault injection operation log, the system monitoring data and the recovery operation process log. The invention aims to solve the problems of low automation degree, narrow scene coverage, weak monitoring evaluation and passive recovery in cloud native system fault test in the prior art, and provides a comprehensive, automatic, monitorable and evaluable fault injection and recovery test scheme.

The embodiment of the invention relates to the technical field of electrolytic copper foil testing, and particularly discloses a continuous testing method and system for warping of an electrolytic copper foil. The method comprises the following steps: periodically cutting an electrolytic copper foil sample; adjusting a test environment, and carrying out leveling positioning and reference calibration on the electrolytic copper foil sample; performing three-dimensional panoramic scanning and multi-point scanning supplement on the electrolytic copper foil sample; reconstructing a three-dimensional surface model, carrying out reference comparison, and calculating a plurality of warping key indexes; and performing qualification judgment and trend analysis on the plurality of warping key indexes, generating a warping test report, and performing feedback control of a continuous test. According to the method, the defect evolution rule is visually presented by automatically generating the three-dimensional surface diagram and the distribution curve visual report; the electroplating parameters are dynamically adjusted by triggering the process feedback control module, a test-analysis-regulation closed loop is formed, the warping degradation trend is inhibited from the source, and the product yield and the production continuity are improved.

The invention discloses a test case generation method and device, equipment and a medium, and relates to the technical field of software test optimization. According to the scheme, the multiple initial test cases are obtained, and the test reports corresponding to the initial test cases are generated through the first preset test tool, so that the time for manually compiling the test cases is effectively shortened; when it is determined that a to-be-supplemented test case of which the corresponding code coverage rate index does not meet a preset requirement exists according to each test report, code uncovered information of the to-be-supplemented test case is determined, and test case optimization parameters are configured in combination with project requirements; and based on the parameter, calling a second preset test tool and a large language model to supplement the to-be-supplemented test case to obtain a complete test case. According to the scheme, the availability of the test case is improved through combination of multiple tools; workflows of test cases covering complex environments such as a function calling relation and a control flow structure are generated by utilizing the inference capability of a large language model, and the code coverage rate of the test cases is remarkably increased.

The invention discloses a performance test method and device of a storage device, an electronic device and a storage medium, and relates to the technical field of data storage, and the performance test method comprises the steps of controlling the storage device to execute data operation in response to test input; wherein the data operation comprises read operation and / or write operation; in the process of executing the data operation by the storage device, obtaining performance data of the storage device through the performance test model; wherein the performance data comprises performance data of a data link of the storage device and performance data of the storage controller, the storage controller is electrically connected with the storage device through the data link, the data link is used for transmitting data between the storage controller and the storage device, and the performance test model comprises at least one performance monitoring tool. The at least one performance monitoring tool is used for performing performance monitoring on the data link and the storage controller; and generating a performance test report of the storage device according to the performance data. The technical effect of improving the performance test efficiency of the storage device can be achieved.

The invention discloses a method and a system for realizing hosted API automatic testing by an API gateway, belongs to the technical field of computer software, and aims at solving the technical problems of how to realize non-intrusive and automatic API testing, ensuring that monitoring and verification can be directly carried out on an API flow level, improving the testing efficiency and the coverage rate and improving the testing efficiency. According to the technical scheme, the method comprises the steps of test case generation, wherein an interface structure is automatically analyzed based on an API document, and a basic test case set is generated; flow capturing: monitoring the actual calling condition of the API in real time, and recording the specific content of each request and the corresponding response data; carrying out flow playback: carrying out playback test based on the captured historical flow, and verifying the compatibility of the API; assertion verification: assertion judgment is performed on indexes of the return value and the response time through an assertion mechanism, and abnormity is found; and test report generation: aggregating test result data, generating a test report containing success rate, response time and error log detailed information, and supporting HTML / PDF / JSON export.

The invention provides a charging pile testing method and device, a new energy automobile and electronic equipment, and the method comprises the steps: constructing a corresponding CAPL script according to the testing demands of a charging pile; performing version identification on the CAPL script to obtain a DBC file; defining message logic of the DBC file; dynamically configuring a protocol state machine corresponding to the DBC file after the message logic is defined; and after the dynamic configuration is completed, switching the configuration according to a test requirement, and generating a test report. The method can be applied to charging protocols of multiple versions, is higher in adaptability, improves the fault detection intensity, can be compatible with various different test scenes and test requirements, can dynamically adjust the test path according to the test requirements, and is higher in flexibility and higher in practicability.

The invention discloses a test method, device and equipment and a computer readable storage medium, which are applied to the technical field of computers, and comprise the following steps: obtaining multi-source data of a distributed storage cluster, the multi-source data comprising hardware state data, service associated operation data and business dependence data; constructing a relation dependency graph among the hardware nodes, the service nodes and the service nodes based on the multi-source data; adjusting the chaos test script according to the real-time state of the distributed storage cluster and the dynamic adjustment strategy to obtain a target chaos test script; and executing the target chaos test script, determining a fault range and a recovery mechanism based on the relation dependency graph, and outputting a test report. According to the method, comprehensive and accurate presentation of the dependency relationship of each node is realized, and the chaos test script can adapt to the dynamic change of the cluster, so that the test scene is more practical, the invalid test is avoided, the effectiveness, reliability and efficiency of the cluster chaos test are remarkably improved, and the high availability and service continuity of the cluster are powerfully guaranteed.

The invention relates to the technical field of titanium alloy detection, and discloses a titanium alloy wire performance detection method, equipment and system. The method comprises the following steps: acquiring real-time force value displacement data of a tensile test and echo signal data of ultrasonic detection, and processing to obtain smooth force value displacement data and spectrum characteristic parameters; performing feature layer fusion on the yield strength, the tensile strength, the peak frequency and the amplitude attenuation rate to construct a first multi-dimensional feature matrix; inputting a pre-trained deep belief network model, and predicting mechanical properties such as elongation and hardness value; and comparing with a preset threshold value, marking unqualified items and generating a detection report. According to the method, through multi-source data fusion and advanced algorithm processing, the comprehensiveness and accuracy of detection are improved, efficient evaluation of the performance of the titanium alloy wire is achieved, and the method is suitable for the strict detection requirements for the quality of the titanium alloy wire in the fields of aerospace, medical instruments and the like.

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 embodiment of the invention discloses an automatic acceptance method and system for relay protection equipment, and relates to the technical field of power system automation, and the method comprises the steps: obtaining a preset acceptance outline template and a configuration description file to which target relay protection equipment belongs; analyzing the configuration description file to extract actual signal information related to the target relay protection equipment; automatically associating the actual signal information with a preset signal in the acceptance outline template to generate an instantiated acceptance outline; in response to the acceptance instruction, automatically interacting with the target relay protection equipment according to the instantiated acceptance outline to execute the test item; automatically acquiring a response result of the target relay protection equipment in the process of executing the test item; comparing the response result with an expected result preset for the test item in the instantiated acceptance outline, judging a test conclusion and generating a structured test report; automation of the acceptance process of the relay protection equipment can be realized, and the accuracy, reliability and efficiency of testing are improved.

The invention belongs to the technical field of performance testing, and particularly discloses an intelligent testing system and method for the impedance performance of an HDI circuit board, and the method comprises the steps: immediately starting an interlayer collection module after the lamination of each line layer, carrying out the electrical precise alignment through a POFV test structure, and collecting the in-situ impedance data; the diagnosis prediction module analyzes and processes the data, generates an impedance deviation parameter set, calculates an impedance performance standard coefficient fused with a layer influence factor, and analyzes and outputs a trend result through a time sequence; the impedance state judgment module carries out abnormity judgment based on a preset rule according to the standard coefficient and the trend result; when the judgment result is abnormal, an adjustment triggering marking module is started; and finally, a test report output module generates a test report containing the impedance performance score and the impedance performance distribution of the whole board. According to the invention, layer-by-layer, real-time and closed-loop intelligent test and regulation of impedance performance are realized, and product quality and production efficiency are effectively improved.

The invention provides a vehicle lamp test case intelligent generation method and system based on a knowledge graph, and relates to the technical field of vehicle lamp test. Comprising the steps of analyzing a test demand according to a customer product demand document, generating a test case according to a vehicle lamp test knowledge graph, filtering invalid test cases and performing case verification, feeding back a test report and updating the vehicle lamp test knowledge graph. According to the method, the test requirements and the index parameters are extracted through the natural language processing technology, intelligent generation of the test cases is achieved in combination with the knowledge graph, invalid cases are filtered through the reinforcement learning agent, the effectiveness and the test efficiency of the test cases are improved, and industrial standards and regulation requirements are met.

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 relates to the technical field of agent testing, and particularly provides an agent dynamic behavior safety testing method and system based on a risk conduction quantification model, and the method comprises the steps: collecting agent behavior data which comprises a plurality of pieces of risk operation information and a risk association relationship; constructing a behavior risk association map by taking the risk operation as a node and the association relationship as an edge, labeling a risk attribute and an aging factor for the node, and labeling risk conduction intensity for the edge; constructing a risk rule base based on the risk labeling result and a preset risk judgment logic; inputting the behavior data, the behavior risk association map and the rule base into a trained quantitative model, and calculating a risk conduction probability, an influence range and a critical node; monitoring a behavior track in real time, suspending a task when a multi-dimensional risk threshold is triggered, backtracking an inference chain and generating an intervention record; and fusing the multi-dimensional data to generate a test report. According to the method, the problems of correlation risk missed judgment and response lag in the traditional test are solved, and the pertinence and reliability of the safety test are improved.

The invention discloses an automatic test method, system and device applied to a WSDL sending interface and a medium, and the method comprises the steps: associating a single test case into various scenes through a scene page preset parameter rule, and verifying the coupling between interface response and scene logic in real time during automatic execution; a WSDL interface definition and parameterization rule engine is dynamically analyzed, and automatic execution of multiple test cases is achieved; encrypted feedback data flow returned by an interface is captured in real time, key indexes are dynamically analyzed and extracted, automatic comparison and root cause tracing are carried out based on a multi-dimensional verification rule, and a test report is generated. According to the method, the problems that interface testing depends on manual coding, the process is split and the maintenance cost is high in aerospace engineering can be solved, zero-code rapid verification, forward and reverse closed-loop testing and interface change self-adaptive maintenance are achieved, and the aerospace software testing efficiency and reliability are remarkably improved.

The invention relates to an automatic test method of an FTTR optical link, which comprises the following steps: acquiring specified parameters of the FTTR optical link to be detected, establishing communication connection between a test control center and FTTR equipment, dynamically generating an optical link test instruction and sending the optical link test instruction to the FTTR equipment, and testing the optical link according to the received optical link test instruction. The test control center performs comparative analysis on the received test data and preset standard data, inputs the test data into a machine learning model for training and updating, judges whether the optical link has a fault based on a comparative analysis result and a prediction result, and marks a fault type and a fault position by using a fault positioning algorithm if the optical link has the fault; and generating a test report based on the comparative analysis result, the fault judgment result, the fault type and the fault position, and automatically generating a fault solution according to the fault type. According to the method, automatic and intelligent testing of the FTTR optical link is realized, and the fault diagnosis efficiency and accuracy are improved.

The invention discloses a one-key performance test method, medium and equipment based on JMeter and template configuration, and the method comprises the steps: obtaining a parameterized performance test template from a template configuration center in response to a test instruction, injecting runtime parameters through a template engine, and generating an executable JMeter test plan; parsing the plan to identify a load pressure demand, thereby dynamically scheduling resources from a distributed load injector cluster and distributing a test plan; uniformly triggering test execution on the cluster, and synchronously acquiring a performance data stream from the JMeter and a resource data stream of the tested system; and finally, timestamp alignment and fusion are carried out on the two types of data streams, intelligent diagnosis is carried out on a formed monitoring data set based on a diagnosis rule base or an intelligent analysis model, and a visual test report containing bottleneck positioning, resource association and link tracking analysis results is generated. According to the invention, full-process automation and intelligentization of performance testing are realized, and the testing efficiency is remarkably improved.

The invention discloses an automatic test method and device based on a camera and an electronic device, and the method comprises the steps: configuring a test environment which comprises an adjustable light source and a standard test graphic card; the brightness and color temperature of the adjustable light source and the focal length and exposure parameters of the to-be-detected camera are automatically adjusted through the control module; controlling the to-be-tested camera to acquire an image of the standard test graphic card, and transmitting the acquired image to an image processing module; the image is analyzed through an image processing module, and the resolution, the color rendition degree, the noise level and the distortion rate are calculated; and generating a test report according to an analysis result, and judging whether the to-be-tested camera is qualified or not. According to the scheme provided by the invention, the adjustable light is automatically controlled to test the camera, the cost of a test task is reduced, the test efficiency is improved, and in addition, the camera test precision is improved through various abundant test conditions.