534 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 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 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.

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 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 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.

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.

The invention relates to an intelligent detection method and device based on an upper computer, computer equipment and a medium, and the method comprises the steps: receiving a test instruction, obtaining the historical use data of test equipment, judging whether to trigger a maintenance prompt or not according to the historical use data, and triggering a chip test instruction if the state of the test equipment is normal; performing power-on detection on the to-be-tested chip based on the chip test instruction, reading firmware version information of the to-be-tested chip, and generating a radio frequency test instruction under the condition that the firmware version information is matched; executing a radio frequency test according to the radio frequency test instruction, judging whether the to-be-tested chip triggers a parameter compensation program or not according to test data, ending the test when the to-be-tested chip does not need to be compensated or after compensation is completed, and generating a test result; and analyzing a test result, if the test is passed, recording and uploading test data to the MES system, and updating historical use data of the test equipment at the same time. The method has the effect of improving the chip production quality.

The invention relates to the technical field of probe testing, in particular to a PCB probe positioning method and system and a storage medium, and the method comprises the steps: obtaining a three-dimensional contour of a bonding pad, screening interference nodes, evaluating a contact error in combination with a probe structure, analyzing the density of test points, dividing a compression region, and carrying out the statistics of a space interference probability. And probe positioning and contact verification are completed according to the error and probability sorting path. The method has the beneficial effects that the dot matrix height on the surface of the bonding pad is comprehensively sampled, the space contour of the bonding pad is reconstructed, and the edge point residual error is extracted, so that the identification of the interference node is more accurate. And in combination with CAD boundary identification of a probe end face structure, comparing a node set formed by three-dimensional sampling points of a bonding pad, and establishing a contact area error evaluation mechanism in normal distance standard deviation calculation to realize multi-dimensional contact adaptation judgment. And forming a density evaluation sequence by the ratio of the spatial distribution to the projection area of all point locations in the test area, mining a local abnormal compression state, and completing the calibration of the high-density interference area.

The invention relates to a civil aircraft fatigue condition-oriented analysis system and analysis method, and provides a set of standardized fatigue analysis data management and control system, so that the normalization of an analysis process and the reliability of a result are ensured; a system preset to-be-called algorithm and basic data resources are called through an algorithm calling arrangement module to generate a fatigue analysis algorithm corresponding to a to-be-analyzed object, so that analysis of different analysis target objects and different fatigue analysis items can be met, and the flexibility of fatigue analysis is guaranteed; the civil aircraft fatigue condition-oriented analysis system and analysis method can automatically respond to the to-be-analyzed test data information and the to-be-analyzed object information and execute automatic analysis operation, so that the analysis accuracy and efficiency are effectively improved, and the operation of operators is more convenient.

The invention relates to the technical field of wireless network testing, and discloses a wireless router complete machine one-stop testing method and system and electronic device.The wireless router complete machine one-stop testing method comprises the steps that a typical network application characteristic flow mode library is constructed, and different flow modes are dynamically combined through the Markov decision process; creating a novel attack mode by using the generative adversarial network; constructing a multi-agent cooperative attack system; dynamically adjusting the test intensity according to the real-time response of the router; constructing a multi-dimensional evaluation index system and analyzing a test result; according to the invention, by combining artificial intelligence and network security technologies, the performance and security protection capability of the wireless router in a complex and changeable network environment and attack scene are comprehensively tested, potential stability problems and security holes are found in advance, and the product quality and the user experience are effectively improved.

The invention relates to the technical field of network security, in particular to an adaptive penetration test method and system based on reinforcement learning, and the method comprises the steps: constructing a state space model, defining an action space, designing a reward function, optimizing a strategy model, and analyzing a test result. According to the method, a reinforcement learning mechanism is combined with target environment feedback, so that multi-step attack path planning and adaptive strategy adjustment are realized, and the intelligence and coverage depth of penetration testing are remarkably improved. And meanwhile, through backtracking analysis of the state transition sequence, the potential threat path is comprehensively identified, and accurate guidance is provided for security protection.

The invention provides an automatic software testing method combining natural language processing (NLP) and natural graphics processing (NGP). According to the method, a demand document is analyzed through NLP, key functions are extracted, test case description is generated, meanwhile, a software user interface is recognized and analyzed through NGP, interface elements and interaction logic are extracted, and an interface model is constructed. And automatically generating a test case and a script based on a demand analysis and interface modeling result, executing, recording and analyzing a test result through an automatic test framework, identifying defects, and proposing optimization suggestions. Experiments show that the method can significantly improve the test coverage rate and efficiency, and is suitable for automatic testing and complex interface interaction verification in a continuous integration environment. Through combination of NLP and NGP, intelligence and automation of software testing are realized, and the method has a wide application prospect.

The invention relates to the technical field of memory test, and provides a test system for a parallel interface NOR FLASH memory, which comprises the following steps of: acquiring verification information of test data of a test data block in a storage area and verification operation in a test process of the NOR FLASH memory, and judging whether the test data block has an error or not; dividing the test data blocks with errors, and determining secondary to-be-analyzed test data blocks; the method comprises the following steps: marking target test data, identifying high-frequency error test data, dividing a secondary to-be-analyzed test data block needing to be adjusted into a tertiary to-be-analyzed test data block, and repeatedly judging and dividing until the data block cannot be continuously divided or the judgment result of the data block is that the data block is not divided, thereby realizing the setting of a block verification mode of a full-step method. And evaluating the durability of the NOR FLASH memory of the parallel interface by using a one-step method. According to the invention, a block verification mode can be adaptively set, and the accuracy of a durability test result is improved.

The present application discloses a method for purifying high-purity propylene, comprising: passing an industrial-grade propylene raw material into a condensation device for at least one condensation treatment to remove heavy components therefrom; analyzing and testing the product that has undergone at least one condensation treatment, and if the analysis fails, returning it for further condensation treatment until the analysis passes; passing the qualified product into an adsorption device for adsorption treatment to remove carbon dioxide and water therefrom; passing the adsorption-treated product into a distillation device for distillation treatment to remove light components therefrom; passing the distillation-treated product into a buffer tank for filling, thereby obtaining the high-purity propylene. The high-purity propylene purification method of the present application utilizes a combination of low-temperature liquefaction, adsorption, and distillation to directly purify industrial propylene with a purity of ≥2.5N into electronic-grade high-purity propylene with a purity greater than 4N.

The invention relates to the technical field of food component analysis and testing, in particular to a fruit pectin sampling and testing method which comprises the following steps: step 1, directionally freezing and crushing, and calculating a target freezing temperature according to a tissue freezing point temperature and cell structure characteristics of a to-be-tested fruit; step 2, gradient centrifugal separation: mixing the crushed particles with a low-temperature protection buffer solution, and maintaining the temperature to be lower than the critical gelation temperature; executing three-stage centrifugation; parameters of each stage are corrected in real time according to physical characteristics of a preorder isolate; 3, dynamic turbidity detection: mixing a pure pectin component with a reaction solution containing a chelating agent and positive ions; calculating the pectin content according to the geometrical characteristic parameters of the characteristic inflection points, and calibrating a calculation model through a standard atlas database. The method can effectively solve the problems of tissue damage and impurity interference in berry fruits and seed-containing fruits, ensures the accuracy and reliability of pectin detection, and has important technical advantages and application prospects.

The invention discloses a metallogenic prediction method and device based on fluid parameters and fluid field modeling, a medium and a product, and relates to the field of metallogenic prediction. The method comprises the following steps: firstly, carrying out lithofacies research on a fluid inclusion sample in a target area to determine a metallogenic stage; analyzing and testing the fluid inclusion samples at different mineralization stages to obtain a plurality of fluid parameters; exploratory data analysis is conducted on the multiple fluid parameters, and key fluid parameters closely related to the content of the main metallogenic elements are screened out; modeling the numerical relationship between the key fluid parameters and the main metallogenic elements by adopting a machine learning or deep learning algorithm, and determining an optimal numerical model; processing the key fluid parameters by adopting different spatial interpolation algorithms, and establishing a three-dimensional fluid field model; according to the three-dimensional fluid field model and the optimal numerical model, three-dimensional metallogenic prediction is carried out in combination with the metallogenic geological elements, and a prospecting target area is determined; the fluid parameters are introduced as predictive variables, so that the precision of metallogenic prediction is improved.

The invention discloses a wafer bonding strength characterization method, and relates to the field of wafer bonding tests.The method comprises the steps that a three-dimensional test model of interface fracture mechanics is built, the total deflection and shear modulus generated by a loading point in the test process are analyzed, and a compliance simulation calculation model corresponding to the three-dimensional test model is generated in combination with the crack length; optimizing the compliance simulation calculation model based on the actual model state of wafer bonding to obtain a compliance calculation model, and constructing an energy release rate calculation model in combination with the relationship between the compliance and the crack length; and loading the bonded sample by using a tensile machine, analyzing the peak load of the bonded sample according to the loading result, and obtaining the bonding strength of the bonded sample in combination with the compliance calculation model and the energy release rate calculation model. According to the method, the sample compliance calculation crack length obtained through experiments is substituted into the compliance calculation model and the energy release rate calculation model to obtain the bonding strength characterization result, the measurement method is simple, and the measurement result is more accurate.

The invention relates to a field effect transistor channel mobility determination method and device and computer equipment. The method comprises the following steps: acquiring a transfer characteristic curve of a target field effect transistor; determining a target effective electric field intensity interval corresponding to the grid voltage of the target field effect transistor according to the transfer characteristic curve of the target field effect transistor; determining the transistor body mobility of the target field effect transistor according to the body mobility model; based on the target effective electric field intensity interval, the coulomb scattering mobility, the phonon scattering mobility and the surface roughness scattering mobility of the target field effect transistor are determined according to a target coulomb scattering mobility model, a target phonon scattering mobility model and a target surface roughness scattering mobility model; and determining the channel mobility of the target field effect transistor based on a channel mobility model. According to the scheme, the performance of the device can be quickly and effectively evaluated, complex analysis testing is avoided, and the development speed of the device process is increased.

The invention provides a multi-mode adaptive attack test method and system for an automatic driving model, and the method comprises the steps: obtaining a to-be-tested automatic driving perception model uploaded by a user, and adapting the to-be-tested automatic driving perception model to a test environment through an automatic analysis technology; according to a test data set and an attack strategy selected by a user, generating a diversified test scene, and performing a multi-modal attack test on the to-be-tested automatic driving perception model; executing the multi-modal attack test by adopting a distributed computing architecture, and dynamically allocating computing resources to process a test task; and monitoring the process of the multi-modal attack test in real time, analyzing a test result, and generating a test report containing vulnerability analysis and optimization suggestions. According to the method, an intelligent and automatic test platform is constructed by aiming at a comprehensive robustness test of an automatic driving perception model and fusing style migration data enhancement, a self-adaptive multi-modal attack strategy and a distributed concurrent test technology.

The application provides a MEMS differential thermal analysis sensor and a DTA / DSC testing method, the sensor comprising a detection thermocouple, a reference thermocouple, an ambient resistance and a shielding ring, wherein the detection thermocouple and the reference thermocouple each comprise a single crystal silicon substrate, a heat insulation cavity, a plurality of single crystal silicon thermocouple pairs and a supporting film, the heat insulation cavity is located in the single crystal silicon substrate, the plurality of single crystal silicon thermocouple pairs are connected in series and are supported by the supporting film to be suspended above the heat insulation cavity to achieve thermal isolation, and the single crystal silicon thermocouple pair comprises an N-type single crystal silicon thermocouple and a P-type single crystal silicon thermocouple connected in series, the temperature and power sensitivity of the sensor are significantly improved, reach 28 mV / K and 100 V / W, and the noise equivalent temperature difference and the noise equivalent power reach 0.5 mK or 0.2 muW. Based on the output signal of the sensor, differential thermal analysis testing and differential scanning calorimetry testing on physical or chemical processes of material heat absorption and release can be realized, the sample consumption is small, and the testing precision is high.

The invention discloses a high-end memory chip asynchronous test system based on a distributed architecture, which relates to the technical field of chip testing, and comprises a state modeling module, a master control end initialization and test end access, memory chip test task pool construction, test end state analysis in combination with historical test load and historical fault information, and memory chip asynchronous test. Generating an optimized scheduling strategy; the scheduling module is used for performing task division and asynchronous scheduling on the memory chip test task pool by adopting an intelligent scheduling algorithm based on an optimized scheduling strategy to generate an asynchronous data flow queue; according to the issuing module, the test end receives the asynchronous data flow queue in an asynchronous mode to carry out protocol unpacking and task mapping, and a memory chip function test task is obtained and issued; according to the method, the test throughput rate and the resource utilization rate are improved by asynchronously sequencing and scheduling tasks, the task scheduling delay is reduced, the load of each test end is balanced, and meanwhile, the horizontal expansibility and the fault-tolerant capability are enhanced.

Cloud computing architecture is described for implementing test modules in a communication-controlled cloud environment with access to private data. The test modules perform synchronous tests on the private data and export test results to an analytic environment subject to data export policies. An analytic application is used to asynchronously analyze the test results in the analytic environment. The cloud computing architecture alternatively or additionally includes an interface for deploying investigation-bound cloud environments in restricted subnets. A collection of software is instantiated in the investigation-bound cloud environment, and the investigation-bound cloud environment may be accessed with remote access credentials using a remote access protocol for testing the collection of software. Information about the investigation-bound cloud environment displayed in the analytic application, and the analytic application and the restricted subnet are forcibly deleted when the investigation is complete.

The invention relates to a method for analyzing and testing chlorine content in a ternary precursor battery material, and belongs to the technical field of chemical analysis of ternary materials. The method comprises the following steps: distilling a sample, separating a part of solution, adding nitric acid, acetone and a silver nitrate solution, diluting with water to prepare a test solution, drawing a standard working curve, determining the content of the chlorine element and the like. The analysis and test method adopts silver chloride turbidimetric spectrophotometry for testing, has the advantages of high sensitivity, strong anti-interference capability, good selectivity, high accuracy, wide applicable concentration range, low analysis cost and simplicity, convenience and rapidness in operation, and can be used as a conventional method for analyzing and testing the chlorine content in the ternary precursor battery material. The samples suitable for the method comprise ternary precursor battery material products of NCM series, NCA series, NCM90, NCMA series and the like.

The invention discloses a semiconductor chip test information automatic analysis system and method, and relates to the technical field of information analysis, and the method comprises the steps: calculating a parameter reference value according to a standardized test data set, carrying out the multi-dimensional discrimination feature extraction based on the parameter reference value, generating a test feature vector, and carrying out the analysis of the test feature vector; injecting the test feature vectors into the parameter influence network model, analyzing a dynamic interaction relationship among test parameters through an anomaly propagation simulation algorithm, performing root cause sorting and influence path tracking based on the dynamic interaction relationship, generating an anomaly analysis report, calling an intelligent diagnosis mechanism according to the anomaly analysis report, and performing fault diagnosis on the test parameters according to the intelligent diagnosis mechanism. Generating a structured conclusion through historical case library matching, and synchronously activating a visualization function to perform interactive presentation on the structured conclusion; according to the method, comprehensive representation of multi-dimensional discrimination information is realized through multi-dimensional feature extraction, the defect that an existing method is limited to single-parameter statistics is overcome, and the test feature vector expression capability is improved.

The invention discloses a comprehensive intelligent test method and system for the performance of a high-load bearing, and relates to the technical field of mechanical engineering, and the test method comprises the steps: carrying out the loading test of the rigidity performance of a wind power heavy-load industrial bearing according to a loading working condition script parameter constructed according to the working condition specification requirement of the wind power heavy-load bearing, obtaining an original test data set; in combination with a Hilbert transform method, analyzing the phase coupling degree of a micro-seismic signal and a charge signal of the wind power heavy-load industrial bearing within the test duration so as to judge whether the contact behavior of a rolling body in the wind power heavy-load industrial bearing and a raceway is normal or not, and sending out a rigidity attenuation analysis instruction; and analyzing the rigidity attenuation degree of the wind power heavy-load industrial bearing in the test duration by combining the loading working condition script parameters, obtaining a test rigidity attenuation value Zsj to judge whether the rigidity performance of the currently tested wind power heavy-load industrial bearing is qualified or not, and marking the wind power heavy-load industrial bearing as a rigidity performance bearing of a corresponding grade.

The invention discloses a water quality measuring device and method, and belongs to the technical field of analytical testing, the water quality measuring device comprises a light source, a first signal receiver and a buffer pool, the buffer pool is provided with a liquid inlet and a liquid outlet, the liquid inlet of the buffer pool is used for continuously inputting a to-be-tested sample, and the liquid outlet is used for continuously outputting the to-be-tested sample; the buffer pool is arranged in the buffer pool, water flow at a liquid outlet of the buffer pool forms a stable liquid column, the light source is arranged on the first side of the liquid column, the first signal receiver is arranged on the second side of the liquid column, light emitted by the light source penetrates through the liquid column and is received by the first signal receiver, and the first signal receiver is used for measuring the light intensity of the received light. Parameters to be tested in a water sample are tested in a non-contact mode, light emitted by the light source penetrates through the liquid column, and the change of a signal is detected through the first signal receiver and can be converted into the content / value of the parameters to be tested in the water sample, so that long-term reliable, accurate and stable water quality testing in various scenes can be met; the key technical problem urgently needing to be broken through in the current water quality monitoring field is solved.