Abstract:In view of the very popular robot technology, relying on the existing resources of the laboratory, a small six degree of freedom (DOF) robot arm system is built. The 6-DOF robot arm system consists of five modules: power supply and conditioning module, MCU control module, mechanical structure of 6-DOF robot arm, attitude control Bluetooth handle, 720p high-definition camera module. Subsequently, through the forward kinematics and inverse kinematics analysis of the manipulator system based on D-H model, the attitude control of the manipulator is further strengthened. Finally, through SP2 Bluetooth handle and Zide_Mini (v1.33) upper computer control software realizes the precise control of the 6-DOF manipulator system. The above research has laid the most important foundation for the further research of the robot arm system.

Abstract:In order to solve the problem of optimizing the cost of data network layout in urban agglomerations, this paper uses the data of urban Internet industry size and population structure to build an evaluation model of urban network access value, and puts forward an optimization method of network layout in urban agglomerations based on network access value. According to the Internet usage scenarios, the network demand indexes of urban industry and consumer data are obtained, the network access value indexes of different cities are evaluated, and the minimum spanning tree algorithm is improved by combining the network topology, urban geographical location, and K-means clustering. The population and industry data of 21 cities in Guangdong Province are taken as examples to verify the method proposed in this paper. The layout decision results show that the cost is reduced by 66.59%. It is suitable for data network layout decision among urban agglomerations of different regions and different development levels, which ensures the urban development and achieves the lowest overall layout cost, and has high reliability and application value.

Abstract:Aiming at the problem of large useless power of equipment in power grid operation, in order to improve this situation and increase the active power output of the system, this study designed a comparison scheme of micro-control (MCU) correction circuit and intelligent power module (IPM) correction circuit in the power grid. The result is that the MCU uses a micro-control unit and PWM combined control technology; IPM uses high-power transistors for circuit verification and correction. The amplitude-frequency characteristics and power distortion correction effects of the two circuits are compared; then the parameter changes of the two circuits are compared. The advantages and disadvantages of the two correction circuits and their respective scope of application are analyzed. The results show that through Proteus simulation, it is found that the critical point of the test power of the MCU correction circuit and the IPM correction circuit is 3.5KW; the stability of the two correction methods is analyzed using MATLAB, and it is found that the MCU critical stability correction power is 3.0KW, and the IPM critical stability correction power is 2.8KW. After comparative study and analysis of the advantages and disadvantages of the two correction methods, the applicable conditions of the two correction circuits are clearly defined.

Abstract:A novel monopole antenna possesses miniaturization, super-wideband (SWB) and unidirectional properties simultaneously is proposed. The antenna is designed to increase the high-frequency impedance bandwidth while reducing the antenna size through the equal cutting angle design of the radiating plate; the short-circuit plate loading technology is adopted to expand the low-frequency bandwidth by adding two short-circuit plates between the radiating plate and the metal ground.，and further realize the miniaturization of the antenna, combined with the equal slit angle design to obtain a super broadband; through the corner reflector and inclined radiation plate to achieve unidirectional radiation. The antenna sample was designed and processed. Simulation and testing showed that the antenna size without/including the reflective surface was 0.18λ×0.15λ×0.13λ and 0.18λ×0.26λ×0.31λ, where λ is the low end of the antenna working frequency band Corresponding wavelength; its |S11|<-10dB impedance bandwidth ratio reaches 25.7:1 (0.97-25GHz); it has a good unidirectional radiation pattern, and the actual gain in the working frequency band is about 1.6~11.3dBi. The antenna structure is simple, and its good performance makes it have great application prospects in the fields of broadband wireless communication.

Abstract:In view of the huge central air-conditioning system, it is difficult to carry out remote control, sharing billing and other issues, this article is based on the embedded platform, using B/S architecture, design and implement a central air-conditioning control management system with sharing billing function. From the hardware interface design, software communication process analysis, to the improvement of the charging algorithm, the design idea of the system is elaborated. The system uses the B/S architecture, which reduces the complexity of deployment while satisfying the use of cross-platform equipment; With FPGA, while ensuring the communication rate, expand the accessible devices to 4096 units; Use SQLite database and improved charging algorithm to complete functions such as apportioned charging storage display. The actual operation shows that the remote control function of the system is efficient and stable, and the apportionment billing function is reasonable and accurate, which solves the problems faced by the current central air-conditioning management system.

Abstract:The phase consistency of mm wave band network is affected by processing accuracy, roughness of copper foil and inconsistent thickness of sheet, resulting in phase difference in the cable output port of iso phase design, and the traditional phase adjustment method increases circuit complexity, which is high cost and not convenient for late adjustment. In this paper, a method of precisely adjusting phase by rectangular defected ground structure(DGS) is proposed, modeling simulation analysis and parameter scanning are carried out by electromagnetic simulation software, and the results show that the load-rectangular defected ground structure of the ribbon port voltage stop wave ratio is less than 1.3 insertion loss is less than 0.7dB, at 30 to 34GHz, two rectangular defected ground structures are used to precisely adjust the phase of the two transmission lines with a phase difference of 14.5 degrees to the phase difference of less than 0.1 degrees, and the structure can adjust the different phases precisely according to the actual processing results, simplify the circuit structure and reduce costs.

Abstract:Arduino is used as the core controller and 2D lidar sensor is used as the external environment detector in the construction of mobile robot SLAM.The collected signal is processed by Arduino and transmitted to ROS operating system through WiFi. The environment map is constructed through processing by the upper computer.The traditional RBPF-SLAM algorithm was optimized, and the map was constructed by the mobile robot test platform under the ROS robot operating system in two different environments. The composition effects before and after the algorithm optimization were compared to compare the performance of the two algorithms.In this paper, one of the experimental environments was measured. By comparing the scale accuracy of the map constructed by the two algorithms, the performance of the algorithm before and after optimization was quantified.It can be seen that the optimized algorithm has better effect of 2D plane map construction through the demonstration of two methods of visual map construction effect and map construction accuracy.

Abstract:Liquid lens has many advantages over the traditional glass lens , and its aberrations have always been the focus of research. In this paper, a liquid lens is proposed to further improve the imaging quality and reduce aberration. This liquid lens is composed of PDMA thin film, pure water, dimethyl silicone oil liquid and F2 glass. This lens designed and emulated by ZEMAX, which shows the geometrical aberration, spherical aberration and so on. The forces on the films of different shapes are analyzed by COMSOL so that to Select the appropriate film as the preferred material for liquid lens. The results indicate that the thin film in the middle is more suitable for making liquid lenses. The liquid lens compared with the traditional lens can reduce aberration and shows better image quality.

Abstract:In order to analyze the dynamic characteristics of the exhaust system in the whole speed range (0-6000r/min), a dynamic characteristics test-bed was designed and a finite element numerical model of the exhaust system was established. Through simulation and experiment, the natural frequency and mode shape of exhaust system in the corresponding speed and frequency range are obtained. The natural frequency error of simulation and experiment results is less than 10%, and the vibration mode is basically the same, which shows that the finite element model of dynamic characteristic analysis is accurate. Then, the finite element numerical model including the power train is established to calculate the dynamic force of the power train from starting to idling and stable operation, and the exhaust system to the vehicle body. The results show that after the power train starts to idle, the dynamic force transmitted by the rubber hanger to the body is less than 5N, and the natural frequency of the system is staggered with the power train excitation frequency to avoid resonance and meet the design requirements.

Abstract:A new fault feature extraction method based on empirical mode decomposition (EMD) and composite multi-scale entropy (CMSE) is proposed, according to the characteristics of analog circuits, such as high integration, nonlinearity and easy to be affected by environment. Firstly, the output signal of the circuit is obtained by simulation. Secondly, the limited intrinsic mode components and a residual component are obtained by empirical mode decomposition. Then, the composite multi-scale entropy algorithm is used to calculate the sample entropy values of these limited intrinsic mode components in different time scales, and the feature vectors which can reflect the circuit fault are constructed. Finally, these fault feature vectors are input into BP neural network for training and testing, and the fault categories of the circuit are diagnosed. The results show that the method can effectively extract the fault characteristic parameters in the circuit, and has a high accuracy in identifying different types of circuit faults.

Abstract:Multi-sensor information fusion technology can effectively improve the ability of radar to find and detect targets, and the prerequisite of successful multi-sensor information fusion is system error registration. Too large system error of radar will bring fuzziness and difficulty to track correlation and fusion, which makes the performance of fusion system degrade seriously. Aiming at the problem of multi-sensor error registration, this paper presents the solutions of time error registration and spatial error registration. By transforming the spatial error registration problem into a nonlinear optimization problem, the genetic algorithm is used to search for the approximate optimal solution of the problem. Through the real radar observation data and MATLAB simulation experiments, the effectiveness of genetic algorithm in solving the problem of multi-sensor error registration is verified.

Abstract:As a self-developed UHV power transmission technology, large cross-section wire transmission and transformation is widely used, but after the completion of the crimping of the transmission line wire, the internal defects of the crimping tube are not easy to find, and the internal aluminum strand surface is scratched, stranded and other internal defects Seriously reduce the current carrying capacity and mechanical strength of the transmission line. In order to solve the existing problems, a simulation method for crimping and breaking of large cross-section conductor steel core aluminum stranded wire is proposed. Taking the JL/G1A-400/35 wire as an example, the damage of the aluminum stranded wire after crimping is modeled and calculated, and the strands are broken, the surface is damaged, and the aluminum stranded wire is not damaged. Stress condition at the time of breaking. The simulation results show that when the aluminum stranded wire is broken, the maximum stress of the broken aluminum strand reaches 802.6Mpa; when the aluminum strand is damaged, the maximum stress of the broken aluminum strand reaches 829.3Mpa; When the stranded wire is not damaged, the maximum breaking stress of the aluminum stranded wire is 865.2Mpa, which is the maximum value of the three cases. In the simulation calculation where the aluminum stranded wire is crimped first and then broken, when a pressure of 1010Mpa is loaded, the aluminum stranded wire can withstand the largest breaking force after crimping. The above simulation analysis results can provide a reference for the optimization of the crimping process of large cross-section conductor steel core aluminum stranded wire!

Abstract:Ultra-wide band (UWB) radar, as a new method of vital sign detection, can monitor human respiratory signs in real-time and non-contact mode. It is of great medical significance. To solve the problem that the distance gate of radar echo signal cannot be extracted accurately and automatically in complex scenes. A fast time domain distance gate filtering method for radar echo signals using neural network is presented. The network structure of the fully connected neural network is analyzed and designed to improve the accuracy of real-time detection of human respiratory signs. Data is collected using PulsON-440 UWB radar module. In the actual scene, the comparative analysis of experiments is completed. The results show that this method can effectively remove the non-breathing distance gate signal. It can further improve the quality of respiratory signals and robustness of detection.

Abstract:TDOA and SDS-TWR are commonly used ranging methods in UWB indoor positioning systems, aiming at the difficulty of clock synchronization in TDOA and the slow speed of SDS-TWR ranging in hardware, a new ranging method based on the fusion of TDOA and SDS-TWR is proposed. This method divides the known anchor nodes into communication master node and secondary node, and can directly measure the communication time from the master node to the target node and the time difference between the target node and the secondary node required for positioning, and the distance between all anchor nodes and the target node in the positioning area can be calculated accordingly. Through error analysis, it is found that the proposed method is accurate enough in indoor positioning, and the simulation results show that its positioning accuracy is within 25cm, which is smaller than the error of TDOA ranging and improves the slow speed of SDS-TWR ranging.

Abstract:The flue gas flow is an important parameter to determine the capacity of waste heat boiler in offshore oil production facilities. In this paper, the excess air coefficient α is calculated by measuring the combustion products (such as O2, RO2, etc.) of gas fuel by gas analyzer on the basis of given gas fuel composition and fuel characteristic coefficient, and then the flue gas flow of gas turbine is calculated . The results show that under different loads, the α value of gas turbine varies from 3 to 7, which is significantly greater than that of boiler. This measurement method has important reference value for engineering application of gas turbine flue gas waste heat recovery in offshore oil production facilities.

Abstract:In view of the abnormality of the inter-ten-year process time of different decoding display mechanisms, the paper analyzes and studies the IRIG-B timecode coding rules and time resolution mechanisms. Focusing on the analysis of the problem through the time-hopping test spanned the whole ten years, combined with the principle of different decoding display mechanism, using the matching method, the annual information display jump phenomenon is the conclusion that the decoding display mechanism is not in harmony with the existing time information coding mechanism. The correctness of the analysis was verified by multiple sets of time-hopping tests. The results show that it is of great significance to study and select the best time resolution display mechanism according to the different requirements of different terminals for time resolution display.

Abstract:Aiming at the problem that data link UAV is limited by take-off and landing mode and site, endurance time, image accuracy and so on, a network UAV based on 5G network technology is designed. The UAV uses the airborne professional equipment, relying on 5G networking technology, to achieve the beyond visual range remote measurement and controllable--periodic, large-area automatic cruise function. In the experiment of geological disaster emergency analysis, the UAV realized the whole process of data acquisition, analysis, preprocessing, spatial calculation, elevation extraction, positive photography production, modeling and output. Compared with data link UAV, 5G networked UAV processed the characteristics of high data transmission rate, low delay, large data transmission capacity, safety and reliability. The results showed that 5G networked UAV is able to grasp the real-time situation of the targeted area, provide first-hand information for the disaster situation, help the accurate assessment of the disaster situation, improve the management efficiency, improve the inspection means, and assist the headquarters in decision-making and command.

Abstract:The acquisition of plant height data mainly relies on manual measurement, which is not only time-consuming and labor-intensive, but also subjective. In order to solve this problem, a plant height measurement system was constructed, by controlling the rotation of the two-dimensional LiDAR, the three-dimensional reproduction of the plant is realized, and the height information is obtained. Using this system, for single plants such as Green dill and Evergreen, use the side overall contour scanning method to obtain the side projection and calculate the height; for the Boxwood Hedgerow and Golden Leaf Ligustrum Hedge, the random sampling consensus algorithm (RANSAC) is used to fit. The algorithm is revised, and then the curve detection-normal nuclear density detection method is used to filter out the outliers in the canopy, and the height is calculated. Experimental results show that the maximum relative deviation between the plant height obtained by this system and the manually measured value is less than 6%. This system has good practical value for plant height measurement.

Abstract:Due to the continuous characteristics of logging data tags, data samples have strong contextual relevance. Aiming at the problem that the basic identification unit constructed by the existing lithology identification methods cannot make full use of the context information provided by the continuity of logging curves, a lithology identification method based on hierarchical clustering meta-object representation is proposed. This method is based on the hierarchical clustering method based on regional growth, comprehensively using multiple conventional logging curves to automatically stratify the target reservoir, and then realize the complete characterization of the meta-object from the perspective of statistical and morphological features. After the features are extracted Lithology identification is performed on the rich feature space formed. Through the comparative experiment of lithology identification with actual logging data in Daqing Oilfield, the performance of various lithology identification of the experimental group using the proposed method has been significantly improved.

Abstract:As the core equipment of traction power supply and transformation system, transformer faults will affect the safety and stability of rail transit operation. Therefore, timely detection of potential faults is conducive to reducing fault costs and improving the reliability of the system. At present, many researches on early fault diagnosis of transformer are focused on the application of monitoring quantity, and the diagnosis and recognition results are fuzzy. In this paper, the technical methods of transformer fault diagnosis and the monitoring parameters used in the fault diagnosis process are summarized. Then the development of transformer fault diagnosis technology is summarized according to the difference of transformer fault diagnosis model method and monitoring state. The shortcomings of transformer fault diagnosis technology as well as the future development direction and challenges are discussed in this paper, which provides some reference value for fault prediction.

Abstract:In practice, traditional metal electromagnetic detection technology is insufficient to detect sheet metal internal defects. In order to solve this problem, a method of recognizing surface and internal defects based on deep learning and electromagnetic detection is proposed in this paper. In our experiment, nine types of surface and internal air-gap defect models with different depths, positions and quantities are built. The feasibility of multi-frequency detection is verified. The relation between excitation voltage and induction voltage detected by array electromagnetic sensor is concerned. Data balance acquisition method is introduced to expand data set before data preprocessing. In order to get the characteristics of measurement data, DNN and CNN are constructed. The appropriate network with suitable parameters is chosen according to the recognition results. The experimental results show that 9 kinds of air-gap defects with different quantities, positions and depths can be recognized by electromagnetic detection applied with DNN or CNN. The recognition accuracy is over 90%. Compared with CNN, DNN is faster and more efficient to classify.

Abstract:In order to solve the problem that the artificial selection of the Convolutional Neural Network tructure in the rolling bearing fault diagnosis is uncertain and the diagnosis accuracy is low, based on the CNN, this paper proposes an applied Genetic Algorithm (GA) GA-CNN, a new method for fault diagnosis of rolling bearings that adaptively selects CNN network structure. This paper first uses Hilbert-Huang Transform (HHT) to extract features of rolling bearing fault signals, and then input the fault features into CNN improved by GA and three groups of CNN with artificially randomly selected network structures for feature recognition. Finally, a conclusion is drawn by comparing the experimental results. GA automatically selects the best structure of CNN network, avoiding the uncertainty of manual selection of CNN network structure, thereby reducing the time required for parameter selection and improving the accuracy of rolling bearing fault diagnosis. Experimental verification shows that the GA-CNN-based rolling bearing fault diagnosis method proposed in this paper greatly improves the efficiency of fault diagnosis and has higher accuracy compared with manual random selection of CNN network structure.

Abstract:By analyzing the behaviors of moving targets in video scenes, video violence detection can determine whether the targets' behaviors belong to violent behaviors such as assault, riot and fight.To detect violence in video, this paper proposed a video violence detection algorithm based on Gray Level Co-occurrence Matrix (GLCM) of optical flow field. The gray level co-occurrence matrix of optical flow obtains the spatial symbiosis distribution information of the motion in the scene and can calculate the important features to describe the behavior in the scene. Firstly, the optical flow of the video was extracted, Then, the Gray Level Co-occurrence Matrix of the grayscale image of the optical flow was extracted, the second moment, contrast, entropy and other features of the Gray Level Co-occurrence Matrix were calculated, and the feature vector was formed. Finally, support vector machines were used to classify the extracted video features into violent or non-violent behaviors. This method is applied to the three public data sets of Hockey, Movies and Violent Flow for 5 fold cross validation, and the accuracy rates are 96.7%, 95.8% and 92.5%, respectively.The experimental results show that the performance of the proposed method is superior to that of similar comparison method.

Abstract:Distribution of fractures, stratigraphy and grains of conglomerate can be analyzed visually in complex reservoirs such as carbonate and sand conglomerate by electrical imaging logging. A fully convolutional deep neural network model is proposed in this paper which captures large volumes of bottom prior statistic features in image and realizes gaps filling in electrical logging images in wells with large caliper to form full borehole covering images by gradually optimizing parameters of neural network model without large number of learning samples. Compared with traditional encoder-decoder model, skip pattern is utilized to connect output of encoder layers with corresponding decoder layer which is helpful for recover local details in images and atrous convolution is adopted to capture multi-scale contextual information. Experiments show that mean error of gray level of pixels is decreased by about 12% and gaps filling effect for images with complex lithology is better in this paper compared with mainstream gaps filling algorithms.

Abstract:In order to solve the problem of low recognition accuracy, the image captured by mobile robot in the process of target recognition has multi-target interference and the target feature is limited in a single perspective. In this paper, a method of Feature fusion of dynamic visual Angle images based on grouping feature weight weights is proposed. In this method, multiple target features are weighted and grouped by progressive K-means clustering, and continuous image features are fused from dynamic perspective by LSTM network, so as to improve the accuracy of target recognition. The verification results show that the first recognition rate on market-1501 data set reaches 93.80%, and the average accuracy reaches 89.13%, with good experimental results.

Abstract:At present, Glass Fibre Reinforced Polymer (GFRP) materials are widely used in oil and gas gathering and transportation, crude oil storage, and sewage treatment due to their superior material characteristics. Due to production complexity, difficulties in quality control and harsh environment, GFRP structures often contain defects (i.e. delamination, water intrusion and crack). Such defects in GFRP storage tanks and GFRP pipelines in oil fields may severely threaten the safety of oil and gas production. In this work, a Capacitive Imaging (CI) system with an arrayed sensor was designed to achieve efficient Non-destructive Evaluation (NDE) of GFRP structures used the oilfields with high accuracy. The proposed system, which includes a software based lock-in amplifier and a channel correction module, were tested using specimens with artificially prefabricated defects. The test results show that the system is compatible with arrayed capacitive probe and is promising in the efficient and high-accuracy NDE of GFRP structures.

Abstract:A fiber optic magnetic field sensor with FBG F-P magnetically sensitive structure combined with optical coherence detection is reported and applied in the field of casing loss detection. The fiber optic FBG F-P interferometer is designed with a long cavity structure with weak reflection to improve the phase shift sensitivity of the magnetic sensor. Based on the differential anti-interference detection structure to eliminate the cross-sensitivity between magnetic field and temperature, the double-layer packaging structure can adapt to the harsh environment. The test platform for casing damage detection was built and the test scheme was formulated. The experimental results showed that the measured results of the magnetic sensor were basically consistent with the actual model defects. The fiber optic magnetic sensor is an all-fiber structure, which can meet the application of underground measurement working environment after being sealed with pressure-proof and water-proof.

Abstract:A real-time monitoring and prediction system of temperature and humidity at each location of bullet storage is designed to aim at the problems of poor real-time monitoring, high power consumption, low detection accuracy, no prediction or inaccurate prediction existing in the traditional bullet storage environment monitoring device. The real-time collection of environmental information of each measurement node is realized by using wireless transmission and low power technology. The environmental information is forecasted by using the maximum similar day algorithm and displayed in the background. The power consumption of the device is low during operation, and the theoretical service time of a 2700mah battery can reach 6 years. The accuracy of measurement is ±0.5℃ and ±2RH%, and the accuracy of prediction is ±1℃ and ±5RH%. The experimental results show that the monitoring device can real-time monitor the environment temperature and humidity of the bullet storage location and effectively predict the temperature and humidity. It has the advantages of good real-time performance, high measurement accuracy, accurate forecasting and other advantages, which effectively solves the problems of difficult information monitoring and low prediction accuracy in the environment of arms and ammunition storage.

Abstract:In order to meet the demand of monitoring for axial stress in high-strength bolts of wind turbine under complex loads, an on-line monitoring system for axial stress in bolts of wind turbine was designed and implemented based on acoustic elastic effect and embedded technology. The system consists of ultrasonic transducers, embedded devices based on ZYNQ and remote monitoring computer. The level comparison method and the maximum peak-zero cross point method are used to calculate the ultrasonic time-of-flight in the bolt. And and a stable and reliable network communication protocol was established based on TCP / IP protocol to ensure the safe and reliable transmission of monitoring data to the remote monitoring computer. Experiments show that the system can realize monitoring of ultrasonic time-of-flight and stress of multi-bolts in real time, and found the problem of loose bolts, which provides technical support for remote fatigue monitoring of wind turbine bolts.

Abstract:The good design of BIT (Built in Test) and Fault diagnosis is an important way to achieve the better testability and maintainability of Phased Array Radar. This paper presents the basic idea of BIT design of radar system. Aim at the composition and function of a multi-functional Phased Array Radar, This paper designed a distributed BIT structure combining centralized control and hierarchical detection and the corresponding BIT workflow, and the selection basis of different fault diagnosis methods. Through the experimental verification based on fault injection, the fault detection rate of the radar BIT system is greater than 95%, the fault isolation rate is greater than 90% in the case of isolation to 3 LRU, greater than 85% in the case of isolation to 1 LRU, and the fault false alarm rate is greater than 5%, which meets the overall requirements and proves the effectiveness of the design of the BIT. At last, It looks forward to the improvement direction of on-line testing and fault diagnosis technology in the Phased Array Radar system.

Abstract:Stacked micro data acquisition systems are widely used in aerospace test analysis, automotive safety testing, biomechanics research, automotive black boxes, etc. These applications require high impact resistance and light weight. In this paper, a new type of stacked high-impact resistant structure is designed in response to this requirement. First, through finite element modeling, a comparative analysis of the high-impact structure under the new composite material of aluminum alloy, gun steel, and carbon fiber was carried out. Second, the impact resistance of the structure composed of the new carbon fiber composite material under different wall thicknesses was simulated. Finally, the impact test proves that its impact resistance is not less than 4000G. The experimental results show that the structure has the advantages of light weight, random increase or decrease of stacking quantity, and easy installation.

Abstract:With the application of millimeter wave radar in auto pilot, FOD detection and other fields, the performance of 92 ~ 96GHz (W-band) PA has attracted much attention. In order to solve the measurement of W-band PA, the paper presents a test scheme based on high-power frequency extender of VNA. Compared with other extenders, the high-power extender contains a build-in PA. The scheme can complete the measurement of all parameters in one measurement system. Compared with the traditional measurement of power parameters and small signal S parameters, it has the advantages of high system integration, simple measurement connection, one-time calibration to achieve all parameters measurement. It also can improve the repeatability of measurement. The paper presents the principle diagram of measurement setup, measurement procedure and some tips for measurement.