Acta Metrologica Sinica

Office Online

Manuscript Tracking

Editor-in-chief

Journal Online

Current Issue

Advanced Search

Archive

Read Articles

Download Articles

Traffic

Quick Search

2022 Vol. 43, No. 11 Published: 2022-11-28

	1389	On-line Prediction of Grinding Surface Roughness Based on Fuzzy Neural Network and Principal Component Analysis
		CHI Yu-lun,WU Yao-yu,JIANG Huan,YANG Lei
		DOI: 10.3969/j.issn.1000-1158.2022.11.01
		Based on acoustic emission and vibration signals, a surface roughness prediction method is proposed to improve the accuracy of workpiece surface roughness identification in grinding process by using the fuzzy neural network and the principal component analysis. Firstly, the acoustic emission and vibration signals are measured in the grinding process, and the relevant time-domain features, the frequency-domain features and the wavelet packet feature parameters are extracted from these signals. The extracted feature parameters are reduced and optimized by using principal component analysis. Then, the fuzzy neural network prediction model of surface roughness is constructed, and the signal feature parameters and the surface roughness are taken as the input and output of the prediction model. Finally, the model is used and trained to verify the prediction accuracy of surface roughness model. The experimental results show that five principal components of the acoustic emission and vibration signal feature parameters are reduced and obtained by using the principal component analysis (PCA) method. Based on the five principal components, the effect accuracy of the fuzzy neural network surface roughness prediction model can reach more than 91%. Compared with locally linear embedding and multidimensional scaling methods, the PCA method is better, and the prediction accuracy is higher.
		2022 Vol. 43 (11): 1389-1397 [Abstract] ( 214 ) HTML (1 KB) PDF (3230 KB) ( 197 )

	1398	Physical Preparation Methods of Ag Tips for Tip-Enhanced Raman Spectroscopy
		ZHU Min-hao,GAO Si-tian,HUANG Lu,HU Jia-cheng,SUN Xiao-shuang,LIU Lin-wei
		DOI: 10.3969/j.issn.1000-1158.2022.11.02
		Two Raman tips and their physical preparation methods that can be applied to the tip enhanced Raman spectroscopy (TERS) system are proposed, namely Ag and Ag-plated tips. Based on finite difference time domain (FDTD) simulation, without interlayer and four different interlayer materials, a simulation study of Ag-plated tips with different film thicknesses and Ag tip points with different tips point curvatures is carried out. The influence of the angle between the incident ray and the tip of the tip and the distance between the tip and the sample on the enhancement of the electromagnetic field is explored. The results show that the Ag-plated tip with a thickness of 45nm with titanium and copper as the intermediate layer and the Ag tip with a tip curvature of 55nm have the best electromagnetic field enhancement effect. The angle between the incident light and the tip is 39.27°, and the distance between the tip and the sample is less than 1nm, which has the best electromagnetic field enhancement effect. Based on simulation, magnetron sputtering is used to successfully prepare Ag-plated tips with titanium as the intermediate layer, and focused ion beam (FIB) cutting to successfully prepare Ag tips.
		2022 Vol. 43 (11): 1398-1403 [Abstract] ( 175 ) HTML (1 KB) PDF (2610 KB) ( 193 )

	1404	Surface Defect Detection of Wheel Hub Based on Improved YOLOv4 Algorithm
		WU Feng-he,CUI Jian-xin,ZHANG Ning,ZHANG Zhi-liang,ZHANG Hui-long,GUO Bao-su
		DOI: 10.3969/j.issn.1000-1158.2022.11.03
		The surface defects produced during the processing of automobile wheels seriously affect the aesthetics and service performance of the whole vehicle. Aiming at the problems of low manual defect detection efficiency and high missed detection rate at this stage, a method for detecting wheel surface defects based on the improved YOLOv4 algorithm is proposed. Constructed a wheel defect data set, including six types of surface defects, composed of 2346 images of 4928×3264pixel, using K-means method for priori box clustering, and focusing on YOLOv4 algorithm on small-scale defects such as fiber and sticky aluminum insufficient detection accuracy. In the Neck part of the original network, a thinned U-shaped network module (TUM) and attention mechanism are introduced to enhance effective features and suppress invalid features, strengthen multi-scale feature extraction and fusion, and improve the possibility of feature processing small target information loss problem; based on self-built data sets, training and testing the defect detection performance of different algorithms and verify the effectiveness of the improved modules, the results show that the average defect detection accuracy of the method reaches 85.8%, and it greatly improves small-size defects such as aluminum sticking. The detection ability of, the detection accuracy is the highest among many comparison algorithms.
		2022 Vol. 43 (11): 1404-1411 [Abstract] ( 203 ) HTML (1 KB) PDF (3246 KB) ( 331 )

	1412	Wheel Hub Recognition Based on ResNet50 and Transfer Learning
		ZHANG Dian-fan,YANG Zhen-hao,CHENG Shu-hong
		DOI: 10.3969/j.issn.1000-1158.2022.11.04
		Aiming at the problem of false identification in manual wheel hub sorting, a neural network model based on ResNet50 and transfer learning is adopted to identify the model of automobile wheel hub.The parameters of the pretraining model are migrated to the ResNet50 convolution neural network, the output layer of original network is modified, and the transfer learning model based on ResNet50 is constructed.By comparing the training efficiency and accuracy of AlexNet, VGG11, VGG16 and ResNet50 when different volume convolution layer parameters are not fine-tuned, used fine-tuning and frozen, it is proved that the ResNet50 transfer model can not only shorten training time when the parameters of the seven bottleneck fragments are frozen but also achieve higher accuracy under the same iteration cycle.Under the freezing strategy, the TL-ResNet50 transfer learning model is trained to predict each of the eight hubs, and the average accuracy of each hub is over 99%.
		2022 Vol. 43 (11): 1412-1417 [Abstract] ( 189 ) HTML (1 KB) PDF (3043 KB) ( 281 )

	1418	Development and Performance Test of High Precision Potassium Heat Pipe Furnace for Aluminum Fixed Point
		LIU Ying,YAN Xiao-ke,ZHANG Jing,WANG Ning,ZHANG Wen
		DOI: 10.3969/j.issn.1000-1158.2022.11.05
		As isothermal furnace liners, heat pipes can be used to improve the temperature uniformity of the fixed point furnaces. In order to improve the reproducibility of the freezing point of aluminum, a potassium heat pipe fixed point furnace for aluminum freezing point was developed. The production processes of potassium heat pipe and fixed point furnace were introduced, and the performance of the potassium heat pipe furnace was tested. The results show that there was no obvious temperature overshoot during the heating process of furnace startup, which can effectively extend the service life of the aluminum fixed point cell. The vertical temperature uniformity was 6.6mK. The repeatability of aluminum freezing point realized by the furnace was 0.02mK.
		2022 Vol. 43 (11): 1418-1423 [Abstract] ( 170 ) HTML (1 KB) PDF (1121 KB) ( 144 )

	1424	Development of a New High Temperature Thermocouple Performance Testing System
		CHEN Qing-qing,PAN Jiang,YUAN Ding-kun
		DOI: 10.3969/j.issn.1000-1158.2022.11.06
		A high temperature thermocouple testing system is developed, including a new structure of high temperature tube furnace, a temperature control module and a temperature measuring module, and the temperature stability and uniformity of the constant temperature section are experimentally studied. The temperature stability of the test system is better than ±0.25℃ in the range of 400℃ to 1000℃; The temperature uniformity of the constant temperature section with a length of 150mm is better than ±0.35℃. The experimental results show that the performance of the test system can meet the requirements of thermocouple performance test.
		2022 Vol. 43 (11): 1424-1430 [Abstract] ( 171 ) HTML (1 KB) PDF (2460 KB) ( 214 )

	1431	Temperature Controlling for Guarded-hot Plate Devices
		WANG Ming-kai,WANG Jin-ku,WANG Jing-hui,ZHANG Jin-tao
		DOI: 10.3969/j.issn.1000-1158.2022.11.07
		The low level of temperature measurement and control of guarded-hot plate devices is an important reason for the deviation of measurement results. Guarded-hot plate devices inherits intrinsic thermal inertia, and multiple units being mandatory temperature controlling. Those units thermally interact via heat conduction and transfer appearing in non-linear interaction, thus, proper setting of controller parameters is critical for suppressing temperature fluctuations. On the temperature control system composed of domestic precision industrial thermometer, thermometer, DC power supply and LabVIEW virtual PID controller, the temperature control parameters of guarded-hot plate devices are studied.The PID control parameters of the system are optimized in segments, and the influence of the temperature control sequence of each component of the guarded-hot plate devices on the overall temperature control effect is studied. According to the setting parameters, in the range from room temperature to 400℃, each unit of the guarded-hot plate device can be controlled within ±0.01℃ in long times. The experimental results show that the parameter setting method can meet the technical requirements of high precision guarded-hot plate devices.
		2022 Vol. 43 (11): 1431-1437 [Abstract] ( 202 ) HTML (1 KB) PDF (2944 KB) ( 429 )

	1445	Numerical Simulation and Experiment Study on Resistance Characteristics of Coriolis Mass Flowmeter for 35MPa/70MPa Hydrogen Dispensers
		ZHAO Yue-jing,HE Guang-li,XU Zhuang
		DOI: 10.3969/j.issn.1000-1158.2022.11.09
		Aiming at the problem that the resistance coefficient of Coriolis mass flowmeters accounts for the largest proportion in the flow resistance characteristics of the main refueling line in 35MPa/70MPa hydrogen dispensers, numerical simulation and experiment of Coriolis mass flowmeters under the operating condition of hydrogen dispensers is carried out. The mathematical and physical models of Coriolis mass flowmeters including inlet section, measuring tube and outlet section are established. And the real hydrogen model is used for numerical simulation under different flow rates of hydrogen dispensers. The pressure distribution and velocity distribution is obtained under actual working conditions of Coriolis mass flowmeters, and then the resistance coefficient is calculated according to the differential pressure and hydrogen flow velocity. Moreover the comparison result indicates that there is a good agreement between the numerical simulation results and the experimental results, and the relative error is less than 5%.
		2022 Vol. 43 (11): 1445-1449 [Abstract] ( 201 ) HTML (1 KB) PDF (1719 KB) ( 173 )

	1450	Research on Intelligent Verification System of Pointer Pressure Meter Based on Machine Vision
		WU Kai-yu,ZHU Hai-qing,SHEN Xiao-dong,SHEN Wei,FANG Ming
		DOI: 10.3969/j.issn.1000-1158.2022.11.10
		In order to solve the problems of low efficiency of traditional calibration device of pointer pressure meter, data can not be kept and traced, an intelligent detection system of pointer pressure meter based on machine vision technology is designed. Firstly, the hardware architecture and software design of the system are introduced, and then the technical principle and solution of image analysis are expounded. At the same time, the intelligent control process of the system and the retrospective review method of verification data are put forward, and the technical scheme of simultaneous verification of 2~10 pieces of pressure meters with the same inspection point is realized. The experimental results show that the average speed of image analysis is 467ms per frame, and the verification efficiency can be increased by more than 2 times compared with manual verification. The relative error of the system reading is 0.08% and 0.2% respectively for the class 0.4 precision pressure meter and class 1.6 general pressure meter with a range of 2.5MPa range.
		2022 Vol. 43 (11): 1450-1455 [Abstract] ( 199 ) HTML (1 KB) PDF (1710 KB) ( 320 )

	1456	Fault Diagnosis System of Numerical Control Machine Based on Incremental Learning
		ZHANG Yu-ying,LU Yi,ZHAO Jing
		DOI: 10.3969/j.issn.1000-1158.2022.11.11
		In order to solve the problem of fault diagnosis when the spindle bearing and tool in numerical control machine malfunction at the same time or working conditions of numerical control machine are changed, a fault diagnosis model named deep convolutional neural network based on incremental learning was proposed. First, the vibration data sets of spindle bearings and tools at common speeds were input into a one-dimensional convolutional neural network, which combined a batch normalization algorithm. Secondly, manually judged the unknown fault type during cross-speed diagnosis, tagged it and re-entered the network. Incremental learning was used to retain old knowledge and learn the characteristics of new data to improve model performance. The fault diagnosis accuracy rate of the model at different speeds is between 76.49% and 86.09%. Compared with the two classic cross-domain algorithms of fine tuning and joint training, deep convolutional neural network based on incremental learning improves accuracy and shortens training time.
		2022 Vol. 43 (11): 1456-1463 [Abstract] ( 168 ) HTML (1 KB) PDF (3703 KB) ( 203 )

	1464	Prediction of Concrete Mechanical Properties Based on Fusion RBF-PSO-AE Algorithm
		HUANG Chen-liang,GUO Li-qun,Lü Yang-yang,LIU Chang
		DOI: 10.3969/j.issn.1000-1158.2022.11.12
		Aiming at the problem of accurate prediction of concrete material mechanical properties, a particle swarm optimization (PSO) optimization of radial basis function (RBF) and the autoencoder(AE) fusion predicting model (RBF-PSO-AE) is proposed to predict and analyz the fracture energy, instability toughness and crack initiation toughness of concrete. Firstly, RBF and AE are used to accelerate the convergence of data feature dimensionality reduction by using cross entropy loss function. Secondly, PSO is used to quickly optimize the network optimal weight of the model. Finally, the model is compared with a variety of single prediction models. The experimental results show that the prediction accuracy and generalization ability of the algorithm model are significantly improved, and the prediction accuracy is greater than 99.99%, with a root mean square error of 0.006%. It can effectively reduce the error of concrete mechanical property prediction, and has good robustness.
		2022 Vol. 43 (11): 1464-1469 [Abstract] ( 183 ) HTML (1 KB) PDF (3018 KB) ( 675 )

	1470	Method and Improvement of Hardness Test of Heterogeneous Mattress
		LIU Mei,SHEN Li-ming,LU Tao,FANG Jiao-jiao
		DOI: 10.3969/j.issn.1000-1158.2022.11.13
		Three optimization methods for the widely used EN 1957:2012 and QBT 1952.2-2011(LGA) test methods are proposed. First, two experimental comparison groups were set up:one group is 8 spring mattresses, the other is 8 foam mattresses. The loading deflection curves of each mattress were measured by a special tester, and these 2 groups of experimental mattresses were assumed. There were obvious differences in hardness and softness due to different materials. Secondly, the LGA test method and three optimization methods were used to measure the two groups of experimental mattresses. Finally, a better calculation method was obtained by using the between-group and intra-group t tests. The results show that the LGA test method and optimization method two are based on artificial regulations, and the test results are not unique; optimization methods two and three show that there is a significant difference in softness and hardness between the two groups, which is consistent with the hypothesis. The third optimization method is unique in the calculation of the mattress softness and hardness value, and is not affected by the testing equipment, it is an ideal optimization method.
		2022 Vol. 43 (11): 1470-1479 [Abstract] ( 128 ) HTML (1 KB) PDF (3034 KB) ( 186 )

	1480	Study on Near-field Sound Pressure of Frequency Focusing Transducer Based on Laser Holography
		ZHU Shi-yu,WANG Yue-bing,ZHAO Peng,LI Shi-ping,GAO Chu,ZHANG Kai
		DOI: 10.3969/j.issn.1000-1158.2022.11.14
		Based on laser holography, the near-field measurement method of low-frequency focusing transducer was researched, the basic principle of laser holography to measure near-field characteristics was analyzed, and a set of experimental measurement system was constructed. In order to verify the feasibility and accuracy of this method, the sound field of a focusing transducer composed of 25 piezoelectric columns arranged in 5*5 with a frequency of 80kHz and a self focusing acoustic lens on the surface was experimentally tested and calculated by using a laser vibrometer, and the sound pressure amplitude and phase distribution on the vibrating diaphragm 50mm away from the center of the radiation concave surface of the transducer were obtained.Using COMSOL model simulation and hydrophone test, the comparison verifies the high accuracy of the far-field extrapolation results after the laser holographic near-field measurement.
		2022 Vol. 43 (11): 1480-1485 [Abstract] ( 138 ) HTML (1 KB) PDF (2356 KB) ( 499 )

	1486	Design of Abnormal Electronic Beep Recognition System Based on Wavelet Denoising and ResNet Classification Network
		WEN Yi-kai,CHEN Le,FU Ya-qiong
		DOI: 10.3969/j.issn.1000-1158.2022.11.15
		Electronic products usually use electronic beep as an alarm function. In order to detect whether the buzzer notification function is qualified in the quality inspection link of electronic products in the factory environment, wavelet noise reduction combined with ResNet network classification technology is used for buzzer detection. A buzzer sound recognition system is designed, the buzzer signal s1 with the PC sound card and the radio microphone, and uses the wavelet packet scale coefficient comparison method to realize the noise reduction and preprocessing of the collected buzzer signal to obtain the signal s2, and obtain the signal time-frequency characteristics through the wavelet transform of the signal s2 figure p, then use the ResNet18 network model to analyze the feature map p to get the buzzer detection result,the recognition accuracy is 97.5%. The system uses PyQt5 to design a human-computer interaction interface, which mainly includes functions such as signal feature display, signal acquisition parameter setting, identification object selection, data communication, and data persistence. Experiments have proved that the system is simple to operate, stable in operation, and strong in scalability.
		2022 Vol. 43 (11): 1486-1491 [Abstract] ( 144 ) HTML (1 KB) PDF (2806 KB) ( 242 )

	1492	Remaining Life Prediction of Lithium Battery Based on Discharge Process Information
		ZHANG Xuan,FENG Hai-lin
		DOI: 10.3969/j.issn.1000-1158.2022.11.16
		Capacity or internal resistance is an important indicator to measure the health status of lithium-ion batteries. But in the actual operation of lithium-ion batteries, the battery capacity and internal resistance are difficult to obtain in real time. So, a method to obtain new health indicators based on the discharge process information is proposed and the remaining useful life of lithium-ion batteries is predicted. The law of voltage change during the discharging process of lithium-ion batteries is studied. On the above basis, two new health indicators which can be measured online are proposed. The accuracy of the new health indicators is corrected by Box-Cox transformation. The results show that there is a strong correlation between the extracted health indicators and the capacity, which can solve the problem that the battery capacity is difficult to measure online to some extent. In addition, the battery degradation process model based on new health indicators is established, and the remaining useful life of lithium-ion batteries is predicted by the relevance vector machine. The experimental results show that the relevance vector machine algorithm is better than other algorithms in life prediction performance. And the later the prediction time, the more accurate the prediction results. The extracted health indicators can describe the degradation process of lithium-ion batteries well and predict the remaining useful life accurately.
		2022 Vol. 43 (11): 1492-1500 [Abstract] ( 172 ) HTML (1 KB) PDF (3971 KB) ( 279 )

	1501	Research for the Resistively Loaded Monocone TEM Cell
		JIANG Ting-yong,WANG Xiao-jia,ZHOU Heng,ZHANG Shou-long
		DOI: 10.3969/j.issn.1000-1158.2022.11.17
		A novel resistively loaded monocone with wide bandwidth and low reflectivity was proposed in this paper. To solve the time window caused by limited length, eight non-inductance resistors networks were applied for the distributed impedance end-loading. Reflections occurred from either the end of cone or the edge of the ground plane was reduced significantly and the operational frequency band-width was widen effectively after loading, especially for the low frequency. The result shows that the measured maximum S11 is less than -17dB from DC to 1GHz for the resistively loaded monocone with length of 1.5m, which broken the time window constraints caused by limited cone length and greatly extended the application for pulse E-field calibration. Correspondingly, the calibration range of measuring system is pushed from ultra-short pulse limited by time window to NEMP with more than 20ns pulse width, as well as for the gain and bandwidth measurement of regular antenna.
		2022 Vol. 43 (11): 1501-1505 [Abstract] ( 165 ) HTML (1 KB) PDF (1711 KB) ( 133 )

	1501	Low Phase Noise Microwave Synthesizer for Coherent Population Trapping Atomic Clock
		YAO Ming-hao,DUAN Jun-yi,WANG Xue-ying,HAN Qi-na,SHI Yang,ZHOU Kun-li,RU Ning,LIU Xiao-chi,QU Ji-feng
		DOI: 10.3969/j.issn.1000-1158.2022.11.18
		Atomic clock based on coherent population trapping (CPT) could interrogate the atoms without microwave cavity, which significantly reduce the volume of the physical package. One of the main limitations of CPT clock is the phase noise of the microwave synthesizer. Here a low phase nosie microwave synthesizer for CPT clock system is demonstrated. The absolute phase noise of the microwave synthesizer achieved -108dBc/Hz at 200Hz offset frequency. The frequency stability limitation of CPT clock with this synthesizer is calculated to be 8. 2×10-14 with Dick effect formula. This low phase noise microwave synthesizer could be also applied in other types of precision measurement system and standards based on atoms.
		2022 Vol. 43 (11): 1501-1505 [Abstract] ( 200 ) HTML (1 KB) PDF (2316 KB) ( 428 )

	1512	The Monte Carlo Modeling and Experimental Verification of the 90Sr/90Y Source and the Extrapolation Chamber
		TENG Zhong-bin,SONG Ming-zhe,WANG Hong-yu,WEI Ke-xin,LIU Yun-tao
		DOI: 10.3969/j.issn.1000-1158.2022.11.19
		The Monte-Carlo (MC) model of the 90Sr/90Y source used in the BSS2 β-ray secondary standard and the PTW 23392 extrapolation chamber was constructed. The depth-dose curves produced by the 90Sr/90Y source at the calibrated distance were calculated using BEAMnrc and compared with the experimental results. According to the difference between the simulation results and the experimental results, the MC model of the 90Sr/90Y source was revised. In addition, the extrapolation curve of the extrapolation chamber, the tissue transmission factor and the tissue absorbed dose rate at the calibration position were simulated. Under the condition of 30cm away from the source and using the beam flattening filter, the calculated extrapolation curves are in good agreement with the experimental results. The differences between the simulated results of the transmission factor and the absorbed dose rate in tissue and the calibration certificate values are within 1.43%and 2.11%, respectively. The mentioned study constructed a more accurate MC model of the 90Sr/90Y source and extrapolation chamber. The results can provide a reference for the calculation of the β fluence spectrum, dose conversion factor and correction factors of the extrapolation chamber in β reference radiation field.
		2022 Vol. 43 (11): 1512-1517 [Abstract] ( 180 ) HTML (1 KB) PDF (1656 KB) ( 296 )

	1518	Calibration of Synchrotron Radiation X-ray Energy from 6keV to 70keV
		HUANG Lin-ru,YAO Xin-bo,WANG Ji,CHEN Can,GUO Si-ming,GUO Xiao-wei,WANG Kai,SHOU Xia
		DOI: 10.3969/j.issn.1000-1158.2022.11.20
		In order to establish relevant national standards in the field of synchrotron radiation X-ray measurement with high fluence rate, the calibration method of synchrotron radiation X-ray energy was studied.Three energy points of 6, 10 and 20keV were selected on the Beijing Synchrotron Radiation Facility for experiments, and the relationship curve between the calibration factor of the transfer standard detector and the radiant energy was approximated to a straight line, and the change trend showed a linear decrease. The calibration experiment at 20keV energy point and different diameter aperture conditions verified that the calibration factor of the transfer detector is related to the photon flux when the light source irradiates to the reference ionization chamber and the transfer detector. 10～70keV energy calibration experiment was conducted on Shanghai Synchrotron Radiation Facility, the fitting curve of transfer standard detectors calibration factor was obtained. The change trend of the energy in 10～20keV is consistent with the change trend of the calibration factor obtained in the Beijing synchrotron radiation device. The calibration factor of the 30～70keV energy segment increases steadily and slowly with the increase of energy. The class A uncertainties of the calibration expriment of each energy point were evaluated, which provided technical data for subsequent establishment of the national measurement standard synchrotron radiation X-ray air specific release kinetic energy value transmission system.
		2022 Vol. 43 (11): 1518-1523 [Abstract] ( 170 ) HTML (1 KB) PDF (1145 KB) ( 135 )

	1524	Research Progress of DNA Methylation Measurement Technology and Accuracy Evaluation
		YANG Yi,YANG Jia-yi,GAO Yun-hua,DONG Lian-hua,YANG Jing-ya
		DOI: 10.3969/j.issn.1000-1158.2022.11.21
		DNA methylation is the most important epigenetic mechanism that has been deeply studied. DNA methylation analysis based on sequencing has laid the foundation for describing a relatively complete DNA CpG map. In the past few decades, the emergence of a large number of DNA methylation measurement technologies has greatly improved the research of genome methylation analysis. However, due to the great differences in equipment and personnel operations of different laboratories, it is difficult to compare the measurement results between laboratories. At the same time, due to the lack of standard analysis procedures and reference materials for evaluating genome methylation, it is not clear whether the current methylation specificity is as accurate as the usual recognition sequence implies. Therefore, the development and problems of DNA methylation measurement technology are discussed, and the importance of DNA methylation measurement accuracy evaluation and reference materials is proposed.
		2022 Vol. 43 (11): 1524-1532 [Abstract] ( 185 ) HTML (1 KB) PDF (670 KB) ( 349 )

	1438	Flow Characteristics Analysis and Flow Pattern Recognition of Two-phase Flow Based on Recurrent Plot
		ZHANG Li-feng,WANG Zhi
		DOI: 10.3969/j.issn.1000-1158.2022.11.08
		Based on the experimental data of gas-liquid two-phase flow in vertical pipeline collected by digital electrical resistance tomography (ERT) system, one-dimensional time series are generated by calculating the mean value of the data collected at different times, and the phase space is reconstructed to draw its recurrent plot. After threshold segmentation, the two-phase flow characteristics can be analyzed effectively. At the same time, the range of image information entropy of different flow patterns corresponding to threshold free recurrent plot is calculated as follows:bubbly flow, 0.570~0.650; transition flow pattern from bubbly flow to slug flow, 2.300~3.200; slug flow, 3.650~4.100; plug flow:4.300~4.600, and flow pattern from plug flow to mixed flow:4.650~4.950.The range of information entropy of each flow pattern recursion graph image is obviously separated, which can effectively identify five flow patterns.
		2022 Vol. 43 (11): 1438-1444 [Abstract] ( 175 ) HTML (1 KB) PDF (6518 KB) ( 154 )

News

Download

Links

Copyright © Editorial Board of Acta Metrologica Sinica
Supported by:Beijing Magtech