365 results about "Online test" patented technology

An online testing and diagnosis method for vibration characteristics of blades of wind turbine is disclosed. Steps of testing and diagnosing blade vibration comprises: S1: installing vibration sensors at key positions of a blade, designing an adaptive data acquisition strategy, and automatically adjusting a sampling rate according to a vibration amplitude and environmental changes monitored in a real time; S2: extracting key features reflecting health status of the blade from massive data, and evaluating an impact of wind speed, temperature, and environmental factors on vibration characteristics; S3: designing a customized deep learning model for damages of the blade of a wind turbine, extracting a time sequence data and a vibration signal, identifying a damage among different types of damages and evaluating a damage degree; and S4: automatically adjusting a warning threshold based on a real-time data stream and a historical trend, and drafting a preventive maintenance plan.

The invention provides an embedded device online test and remote maintenance method and system, and relates to the technical field of device maintenance, and the method comprises the steps: collecting multi-source heterogeneous data, selecting a sampling period based on Shannon entropy, employing wavelet transform and fractal theory to extract features, inputting an anomaly detection model to generate an anomaly degree vector, and carrying out the detection of the anomaly degree vector; extracting features by using a capsule neural network and performing fault type probability distribution prediction; calculating system state indexes by combining a phase-space reconstruction technology; inputting a causal reasoning network to generate a fault diagnosis report; retrieving a maintenance scheme based on the fault diagnosis report; and the maintenance effect is evaluated through the twin neural network, and the maintenance instruction is iteratively optimized according to the effect until the maintenance effect reaches the standard.

The invention provides a vocational ability assessment system based on a skill map, and relates to the field of human resource technology and knowledge map application. The evaluation main system comprises a skill star map generation module, an occupational trajectory simulation module, a skill challenge module, a skill authentication chain module, a future skill navigation module, a skill collaborative ecological module, a skill evolutionary tree module, an occupational story generation module, a skill energy pool module, an occupational time capsule module and a control flow management module; according to the invention, the dynamic skill star map is constructed and the 5G network is combined to transmit data in real time, so that the occupational experience, learning records and test data of the user can be collected in time, and the node weight is dynamically adjusted through the semantic analysis algorithm and the weighted scoring algorithm; the problems that traditional manual evaluation and online testing are high in subjectivity and low in efficiency, and the capability cannot be accurately quantified are effectively solved.

The invention relates to a power device online test system and a power device test control method. The system comprises an upper computer, a test board and a digital signal generator, the test board and the digital signal generator are connected with the upper computer, n aging circuits, driving circuits and measuring circuits are integrated on the test board, and the upper computer is used for determining test parameters of periodic tests of at least one to-be-tested power device and determining the test parameters of the to-be-tested power device for each test. Determining a performance test type of the to-be-tested power device according to the test parameters, generating a performance test instruction corresponding to the performance test type, and sending the performance test instruction to a digital signal generator; generating a corresponding pulse test signal, and transmitting the pulse test signal to the driving circuit; a relay in a test channel is controlled to be switched on and / or switched off according to the pulse test signal, a performance test corresponding to the performance test type is achieved for the to-be-tested power device through the test channel, and the test channel comprises an aging circuit and a measuring circuit.

The invention provides a blade lightning protection channel online test method and system based on a pulse current method, and belongs to the technical field of blade lightning protection detection.The method comprises the steps that a pulse waveform is generated through a pulse current generator to simulate lightning impulse, and the lightning impulse is injected into the surface of a lightning arrester of a blade lightning protection system; measuring channel currents at different positions of the surface of the lightning arrester in the length direction by using a distributed sensor; a high-voltage differential probe is used for collecting and measuring the waveform of an incident wave and the waveform of a reflected wave of an injection point; detecting blade surface potential distribution by using a capacitive coupling sensor; comparing the waveform of the incident wave, the waveform of the reflected wave and the theoretical waveform, determining a time domain reflection coefficient and a frequency domain impedance spectrum, and determining a fault type; after the fault type is determined, the fault point is positioned based on the channel current and the blade surface potential distribution, the lightning impulse is simulated through the pulse waveform, the lightning protection channel is further tested, shutdown is not needed, the testing efficiency of the blade lightning protection channel is effectively improved, and the power generation efficiency is ensured.

The invention belongs to the field of examination systems, and particularly relates to an online examination automatic test paper composition method based on a knowledge graph, and the method comprises the following steps: S1, data collection; s2, constructing an atlas; s3, collecting and analyzing examinee information; s4, analyzing examination requirements; s5, formulating a test paper generation strategy; and S6, test paper generation and verification. According to the online examination automatic test paper composition method based on the knowledge graph, knowledge materials are widely collected through multiple channels, data mining and semantic network technologies are used for carefully analyzing knowledge point relations, and the constructed knowledge graph is distinct in hierarchy and rich in semantics. And formulating a strategy by using an intelligent algorithm according to knowledge level evaluation and examination requirements of examinees during paper composition. For weak or important examination knowledge points of examinees, the number of questions, score weights and difficulty levels can be accurately controlled, blindness of traditional test paper composition is avoided, test paper is made to closely fit the reality of the examinees, and the knowledge mastering and application ability of the examinees is accurately evaluated.

The invention relates to the technical field of electronic component testing for investigating or analyzing internal microstructures and physical properties of materials by utilizing an electrical means, and discloses an online testing and analyzing method for physical properties of electronic component materials, which comprises the following steps of: constructing a composite excitation signal formed by linearly superposing a main carrier voltage and a perturbation wave voltage; applying the signal to a to-be-tested electronic component and acquiring response current; and extracting an intermodulation current amplitude at an intermodulation frequency point in the frequency spectrum of which the linear response interval is excluded, calculating a nonlinear response coefficient of the material in combination with the excitation amplitude, and comparing the nonlinear response coefficient with a preset degradation threshold so as to judge whether the nonlinear response coefficient is qualified or not. By extracting intermodulation components which cannot be generated by linear contact resistance, physical isolation of external contact noise in a frequency domain is realized, and the problem that contact resistance fluctuation and material intrinsic aging cannot be distinguished in a traditional linear impedance test is solved.

The invention discloses an information system security online test method, system and device and a medium, and the method comprises the steps: carrying out the vulnerability scanning of an information system, and generating a vulnerability report according to a vulnerability scanning result; performing simulation attack on the information system, and generating an attack simulation report according to a simulation attack result; and generating a risk assessment matrix according to the vulnerability report and the attack simulation report. According to the method, the system, the equipment and the medium, comprehensive security verification can be carried out before the information system is online.

The invention provides a semiconductor chip on-line test device, and particularly relates to the technical field of chip performance test.The semiconductor chip on-line test device comprises a test box, a main controller is installed at the top of one side of the test box, and a vertical heat insulation plate is fixedly arranged in the middle of an inner cavity of the test box; a test space is divided into a low-temperature test area and a high-temperature test area which are independent through a vertical heat insulation plate and a horizontal heat insulation plate, an annular groove is formed in the position, corresponding to the permanent magnet ring, of the top face of the horizontal heat insulation plate, two symmetrically-arranged permanent magnet blocks are arranged in the annular groove in a sliding mode, and the positions of the two permanent magnet blocks correspond to the position of the permanent magnet ring in an up-and-down mode. The test board can enter different temperature zones at the same time for synchronous test under the driving of the circular ring plate, the problem of temperature fluctuation caused by environment exposure during environment switching in the prior art is avoided, the temperature of the temperature zones does not need to be frequently adjusted, the stability of the test environment is ensured, and the test efficiency of the semiconductor chip is improved.

The invention relates to the technical field of big data management, and particularly provides a data rule design method and device for intelligent visual online testing, and the method comprises the following steps: S1, defining a data rule: defining the rule from three aspects of custom quality dimension, a basic rule base and a business rule base; s2, the JavaScript script is verified, and the JavaScript S3, performing matching by using a regular expression, and searching and replacing a complex text mode; s4, online testing and formatting are carried out, regular expressions or JS scripts are selected to carry out online testing and editing on data rule contents, meanwhile, the rule contents are displayed as verification or processing results of the data, in addition, the JS scripts carry out parameter analysis on rule methods, and attribute classification and filling are carried out on parameters; and S5, task scheduling and optimization. Compared with the prior art, the method can provide data meanings and business rule standards which are commonly obeyed by an upper business level.

The invention relates to the technical field of power system protection equipment testing, in particular to an online testing method for a backup protector special for a surge protector, and aims to solve the problem that in the prior art, spectral characteristics under actual fault conditions such as lightning stroke or short circuit cannot be comprehensively reflected only by depending on power frequency testing. A high-frequency dynamic frequency sweeping signal is injected through the non-contact coupling unit, a multi-source signal fusion judgment mechanism is combined, the physical contact risk is avoided, meanwhile, real working condition simulation is achieved, the problems of test distortion, weak anti-interference capacity and aging monitoring deficiency in a traditional method are effectively solved, and the test accuracy is improved. The method has the technical effect of remarkably improving the test safety and accuracy.

A pressurized water reactor core oxidation corrosion product deposition multi-physical coupling hardware-in-loop device comprises a corrosion product accelerated deposition system, an element online testing system and an axial power offset digital mirror image system. According to the method, the complex multi-physics field coupling process of hydrochemistry, material corrosion, flow heat transfer, neutron physics and the like involved in oxidation corrosion product deposition can be achieved, off-line data transmission between single physics fields is avoided, the growth rule of a deposition layer is directly obtained, the deposition mechanism of oxidation corrosion products is analyzed, and the deposition efficiency is improved. The defects that an existing device cannot perform entity verification and cannot obtain element concentration and distribution in a corrosion product deposition layer are overcome.

The invention discloses an on-line monitoring and early warning method for a bus capacitor of an electric driving system, and belongs to the field of electric driving systems. The electric driving system sequentially comprises an isolating circuit, a full-wave bridge rectifier, a bus capacitor bank, an inverter, an actuator and a capacitance online testing device; the capacitor online testing device comprises a relay, a load resistor, a voltage acquisition module, a current acquisition module and a master control calculation unit. When the electric drive system is idle, a load resistor is connected to construct a test path, and current and voltage signals are collected; disconnecting a test path, constructing a degradation characterization quantity of multi-index information fusion through time-frequency domain feature extraction, and constructing an equal-length time interval sequence degradation curve; and the TCN-BRU-GRU combined prediction model carries out trend feature learning and training on the degradation curve. According to the method, waveform fitting and local and global data feature capturing of non-equal-interval time sampling are achieved, trend prediction of bus capacitor performance degradation is achieved, early warning is conducted before failure of the bus capacitor, and safe and reliable operation of an electric drive system is guaranteed.

The invention relates to the technical field of charge and discharge detection, and discloses a multichannel EIS charge and discharge in-situ test system and method, and the system comprises a DC charge and discharge module which is used for carrying out the constant-current, constant-voltage or cyclic charge and discharge test of a battery; the alternating current impedance test module is connected in parallel with the direct current charging and discharging module and is used for applying an alternating current disturbance signal to the battery and collecting impedance response in the charging and discharging process; and the unified clock module is used for providing a synchronous triggering reference signal for the direct current charging and discharging module and the alternating current impedance test module. The direct current charging and discharging module and the alternating current impedance test module are designed to be of a parallel connection normally-connected structure, no relay switching is needed, continuous and uninterrupted online EIS test in the charging and discharging process is achieved, contact resistance drift and transient errors caused by physical circuit switching in a traditional scheme are effectively avoided, and the reliability of the EIS test is improved. And the stability and repeatability of the test are obviously improved.

A system and method automatically evaluate participant online testing and automatically provide feedback regarding test results of a participant. Automatic evaluation includes processing video frames, audio, timestamped screenshots, and initial test results of the participant answering multiple test questions and transcribing audio. The system and method utilize optical character recognition on the screenshots to generate a set of text for each screenshot and compare the set of text from each timestamped screenshot to determine which screenshots are associated with each test question. The system and method further determine time periods for each question, segment the transcribed audio, the screenshots, and the video frames by question and select a screenshot and a video frame for each test question from the segmented screenshots and video frames. The system and method utilize a first AI tool and a second AI tool to determine whether the participant demonstrated mastery for each test question.

A high-safety and fast charging method for lithium batteries based on deep reinforcement learning, which uses an SP+ model to model lithium batteries; according to the pulse working conditions set for lithium batteries in different degradation stages, the SP+ model parameters under different SoHs, different SoCs, different temperatures and different rates are identified; an improved deep reinforcement learning SAC algorithm is constructed, and a reward function is defined; the SP+ model is used as an interactive environment for an intelligent agent of the improved SAC algorithm, and the intelligent agent is trained offline based on the reward function, so that the intelligent agent of the SAC algorithm learns to provide the optimal safe and fast charging strategy under different SoHs, different SoCs, different temperatures and different rates; and the method is used for lithium batteries, and online tests are performed under different SoHs, different SoCs, different temperatures and different rates to output the optimal safe and fast charging strategy; the present invention can better understand and handle complex environments, and has better generalization ability and adaptability.

The invention relates to a material ignition effect on-line test system and a method thereof, belongs to the technical field of material ignition effect research and application, and solves the technical problems of low heat flow loading level and insufficient material pyrolysis and ignition characteristic on-line test capability in the material ignition effect research process. The test system comprises a heat flow loading subsystem, an effect on-line test subsystem and a combustion chamber. The heat flow loading subsystem is used for applying heat flow irradiation to a to-be-tested material, the effect on-line testing subsystem is used for collecting ignition effect parameters of the to-be-tested material, and the combustion chamber provides an irradiation space for the to-be-tested material. The testing method comprises the steps of self-inspection of the testing system, preparation of a to-be-tested material, placement of the to-be-tested material in the combustion chamber, arrangement of the testing system, arrangement of the heat flow loading system, and acquisition and analysis of material ignition effect data. The device is used for on-line testing of the material ignition effect.

The invention discloses a group relative strategy optimization-based dynamic optimization scheduling method, system and equipment for a park power distribution network, and a medium. The method comprises the following steps of: acquiring basic data of a park power distribution network system; constructing an optimization scheduling model based on the basic data, converting a multi-objective optimization model into a Markov decision process, and defining a state space, an action space and a reward function; and solving the Markov decision process by using a group relative strategy optimization algorithm, optimizing and verifying the optimization scheduling model by using the group relative strategy optimization algorithm through offline training and online testing, and generating a dynamic optimization scheduling scheme of the power distribution network of the park. According to the method, the stability and convergence speed of reinforcement learning training are improved through a group relative strategy optimization algorithm, the photovoltaic and load uncertainty is adapted in combination with off-line training and on-line testing, the operation cost of the power distribution network in the park is reduced, the income is improved, the energy storage life is prolonged through energy storage health state management and control, and the dynamic scheduling effect is optimized.

The invention discloses a sample uncertainty estimation-based self-adaptive target recognition method during online testing, which belongs to the technical field of computer vision and comprises the following steps of: firstly, downloading a data set and augmenting the data set; then sequentially sending each batch of data into the source domain model, evaluating the current batch of data twice through the source domain model, and calculating an uncertainty value of each sample; carrying out model learning on the batch of samples and carrying out model training updating; and finally, predicting the samples by using the model which learns the current batch of target data to obtain a classification result of the batch of samples. According to the invention, the problem that the target domain data cannot be obtained and real-time identification needs to be carried out in the adaptive framework during the online test at present is well solved, and the accuracy of identifying the vehicle target object by the intelligent traffic during the online test is improved.

The invention provides a PCBA testing machine which comprises a testing rack, a testing assembly, an electrical assembly, a computer assembly and a power supply assembly, a transmission mechanism is arranged in the middle of the testing rack in a penetrating mode, and the testing assembly is arranged below the transmission mechanism and provided with a probe. The probe is used for being inserted into a test point of the PCBA so as to input a first test signal or output a second test signal; the electrical assembly is connected with the test assembly and is used for driving a probe of the test assembly to be inserted into a test point of the PCBA or pulled out of the test point according to a control instruction of the computer assembly; the computer assembly is used for generating the first test signal and receiving the second test signal to complete on-line test and function test of the PCBA. The power supply assembly supplies power to the test assembly, the electrical assembly and the computer assembly. The PCBA testing machine integrates ICT testing and FCT testing, the testing efficiency is improved, the turnover loss is reduced, and the cost of the testing machine is also saved.

The invention relates to the technical field of motor testing, and discloses a motor dynamic characteristic compensation test method and platform based on multi-modal data, the method collects motor data through a multi-modal synchronous test system, and a processing module executes the following steps: constructing a state observer model to estimate winding temperature and loss torque; in the online test, the accuracy of the model is monitored by calculating the residual error between the model prediction and the measured value; and when the residual dynamic characteristic exceeds a threshold value, generating and applying an adaptive excitation sequence according to the residual characteristic, collecting high-resolution data to update model parameters on line, forming a self-optimization closed loop, after the test is finished, adopting a fixed interval smoothing algorithm to be combined with a final model to obtain a global optimal state track, and calculating a dynamic characteristic compensation result according to the global optimal state track. According to the invention, through adaptive excitation of residual error driving and online model updating, accurate identification and compensation of dynamic characteristics of the motor are realized, and the test automation level and accuracy are improved.

The invention relates to the technical field of artificial intelligence, in particular to an online test adaptation method and device for time sequence prediction. Comprising the following steps: establishing and maintaining a historical sample memory bank, storing historical time sequence data, and updating the memory bank through a first-in first-out strategy; screening a historical sample set in a historical sample memory bank, wherein the similarity between the historical sample set and the test sample in the potential space meets a preset condition; performing frequency domain-based mixed data enhancement on the test sample and the historical sample set to generate an enhanced sample set; inputting the enhanced sample set into a time sequence prediction model for batch training, dynamically adjusting model parameters to adapt to distribution offset, and outputting a final prediction result generated through fusion; and evaluating the performance of the model through the loss function. According to the method, the adaptability of the model to new distribution can be enhanced, the robustness of the model is improved, the noise sensitivity is suppressed, data enhancement is performed on the time sequence, and damage to a time domain of the time sequence is avoided.

The invention provides an under-pressure operation machine turntable torque online test method and device, and relates to the field of petroleum equipment detection and evaluation, and the device comprises a tool module, a monitoring module, an acquisition module, a data transmission module, a control platform and an early warning module. The monitoring module, the acquisition module and the data transmission module are controlled by taking the control platform as a center, the monitoring module is used for monitoring torsion frequency signals of a mandrel under different output torques of a turntable, the acquisition module and the data transmission module are used for acquiring and sending the data, and an analysis result is analyzed and calculated through the control platform. And finally, early warning information is sent out through the early warning module, automatic real-time monitoring of the torque change condition of the rotary table can be achieved without disassembling and assembling the rotary table, and the real output torque of the rotary table of the under-pressure operation machine can be accurately measured in real time and early warned.

The invention discloses online lithium ion battery water content detection equipment and method. A metal cavity is additionally arranged on an exhaust pipeline of a vacuum oven for baking, high-temperature gas in the vacuum oven is fed into the metal cavity through a vacuum pump, and after being mixed in the metal cavity, the high-temperature gas enters a Karl Fischer moisture measuring instrument through a pipeline with a gas flow meter for testing. According to the invention, the moisture measurement of the battery cell can be changed from an off-line test to an on-line test, so that unnecessary procedures are reduced, the automation degree of a production line is increased, and the labor cost investment is reduced; a non-sampling inspection mode is adopted, the water content of the battery cells is represented through the water content of the battery cells baked by the whole tray or even the whole drying oven, meanwhile, all detection is controlled by equipment, and the detection result is more accurate; and meanwhile, a false battery cell is not needed during testing, and non-destructive testing is realized, so that the material cost input is reduced.

Disclosed in the present invention is a personalized online test question recommendation method based on student emotion perception. The method comprises the following steps: S1, collecting answering behaviors of students for online learning and corresponding emotion records, and carrying out data cleaning to extract effective information; S2, on the basis of the emotion data of the students, using PCA to classify the complex emotions of the students, adjusting the impacts of the emotions on the students by means of the weight of a self-attention module, and performing modeling on the external cognition of the students; S3, integrating the external cognition of the students and the inherent cognition of the students, introducing an NCB-IRM framework, and comprehensively predicting the personalized response of the students; S4, using PMF to decompose the answering generality of the students, and jointly predicting the response of the students to test questions on the basis of the predicted personalized response of the students; and S5, on the basis of the predicted response of the students, providing test questions with appropriate difficulty for the students, and forming a final recommendation list. In the present invention, on the basis of PMF and NCB-IRM in combination with the personality and answering generality of students, the accuracy and reasonability of test question recommendation are realized in accordance with the test question mastering condition of the students.

The invention discloses a circuit board general online test method and system. The system comprises a master control system, a tool box, an online conveying device, an automatic docking device and a circuit board general test device. A general control system, an automatic docking device and a circuit board universal testing device are arranged on the side of the near end of the online conveying device, the automatic docking device is located on the other side, and the general control system is in communication connection with the online conveying device, the automatic docking device and the circuit board universal testing device; the tool box loaded with the circuit board to be tested is conveyed to the automatic butt joint device through the online conveying device, and the automatic butt joint device automatically achieves electrical butt joint between the tool box and the circuit board universal testing device. Test and data processing software is arranged in the circuit board general test device, and the test software is used for testing voltage, current, resistance, frequency and / or waveform of different circuit boards and carrying out data acquisition, statistical analysis, test report generation and the like. According to the invention, automatic on-line testing of different circuit boards is realized.

The invention relates to the technical field of dynamic balance testing of rotating machinery, and discloses a dynamic balance state testing system based on equipment operation data, which comprises a synchronous sampling module, a fundamental frequency vector analysis module and an influence coefficient self-adaptive calibration module, the synchronous sampling module collects key phase pulses and original vibration signals of the rotating equipment; a fundamental frequency vector analysis module extracts an instantaneous rotating speed and a real-time fundamental frequency vibration vector; the influence coefficient self-adaptive calibration module stores a weight matrix representing rotor supporting characteristics, monitors a rotating speed fluctuation variance, corrects the weight matrix according to complex deviation of a vibration vector when the variance exceeds a preset threshold value, solves a net unbalance vector of the controlled rotating equipment, and outputs the net unbalance vector. According to the method, the rotating speed micro fluctuation in the operation process is used as an excitation increment source, and the sensitivity model reflecting the rotor bearing characteristics is constructed, so that the dynamic balance test gets rid of the limitation of adding a physical test weight, and the online test requirement under the continuous working condition is met.

The invention discloses a plug-in function and online test method for a pre-training model of a power system, and designs a pre-training model oriented to the power industry by combining NLP, BERT and reinforcement learning technologies, and realizes a data-driven intelligent control strategy. Through semi-supervised learning, labeled data and unlabeled data are integrated, the generalization ability of the model is improved, and a high-quality initialization model is provided for reinforcement learning agents. The pre-training model is disassembled into independent plug-in modules, and the plug-in modules are integrated with a simulation platform through an API, so that on-demand loading and scene switching of the modules are realized, and the flexibility of the system is ensured. A dynamic event and a system fault are simulated on an HIL platform, and a reinforcement learning agent is pre-trained in combination with an MPC controller, so that the strategy optimization process can continuously adapt to a system state. In addition, model parameters and control strategies are continuously updated through a particle swarm optimization algorithm, and it is ensured that the RL agent and the plug-in module are always kept synchronous with system requirements.

The embodiment of the invention discloses an online self-healing test system. The system comprises an operation and maintenance master station, a power distribution terminal and a self-healing tester deployed for testing the power distribution terminal, wherein the operation and maintenance master station is used for generating a self-healing test case for the power distribution terminal and sending the self-healing test case to the self-healing tester; the self-healing tester is used for executing a received self-healing test case aiming at the power distribution terminal and uploading a collected first terminal signal of the power distribution terminal to the operation and maintenance main station; the power distribution terminal is used for uploading a self-acquired second terminal signal to the operation and maintenance master station; and the operation and maintenance master station is also used for comparing the received first terminal signal with the received second terminal signal and comparing with a preset power distribution network self-healing strategy so as to test the power distribution network self-healing strategy. According to the technical scheme of the embodiment of the invention, the online test of the self-healing strategy of the power distribution network can be realized.

The utility model discloses an intelligent crude oil moisture content on-line tester which comprises a tester box body, an oil inlet pipeline is arranged on one side of the tester box body, and an oil outlet pipeline is arranged on the other side of the tester box body; a water content detection mechanism is arranged between the oil inlet pipeline and the oil outlet pipeline; by means of the oil inlet pipeline, crude oil in the main pipeline can be conveniently sampled into the equipment for water content measurement, measurement errors caused by flow velocity and pressure changes and the like in the pipeline are avoided, and therefore the measurement accuracy is improved; meanwhile, the crude oil is sent back to the crude oil main pipeline through the oil outlet pipeline after detection; the moisture content measurement is high in accuracy: the moisture content measurement adopts field calibration, and the instrument can be corrected according to different working conditions; errors caused by working condition changes in primary calibration are avoided. The test precision is improved; and a 485 communication interface is reserved, so that a client can conveniently transmit data such as the equipment operation state and the water content to an upper computer, and the functions of data analysis, report printing and the like are realized.