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2024 Vol. 45, No. 2
Published: 2024-02-28
 
145 The Impact of the Electromagnetic Metrology System after the New International System of Units
SHAO Haiming,ZHANG Jiangtao,HUANG Lu
DOI: 10.3969/j.issn.1000-1158.2024.02.01
Since May 2019, the new international system of units (SI) based on the four fundamental physical constants has been formally implemented. The quantization of the basic units and the replacement of the artifact standards by the quantum standards open a new area, which can independently reproduce the fundamental SI units without the Bureau International des Poids et Mesures (BIPM). The major variations of the electrical units between the new SI and the original system in 1990 are mainly introduced. In the meantime, the changes for the electromagnetic measurement activities are also presented.
2024 Vol. 45 (2): 145-149 [Abstract] ( 163 ) HTML (1 KB)  PDF (523 KB)  ( 166 )
150 The Investigation of a Miniaturized Acoustic Gas Thermometer
LI Mingda,XING Li,SI Minghao,FENG Xiaojuan,ZHANG Jintao,WANG Xiaojie
DOI: 10.3969/j.issn.1000-1158.2024.02.02
To promote the practical development of acoustic gas primary thermometry, a miniaturized acoustic gas thermometer with an inner diameter of 10mm, an outer diameter of 12mm and an inner length of 40mm was developed based on the principle of measuring thermodynamic temperature by cylindrical acoustic gas resonant method. An optimized acoustic generator was used to improve the sound pressure intensity. The experiment was carried out from room temperature to 782K at atmospheric pressure. The results showed that the random deviation of the acoustic resonance frequency in atmospheric pressure air at 782K is less than 0.2% using acoustic waveguides. After correcting the boundary layer and duct perturbations, the thermodynamic temperature of 407K to 782K with room temperature as the reference was obtained with an uncertainty of 0.76K to 2.93K (k=1). The investigation provided the possibility for application of the primary acoustic gas thermometer in harsh or special environment.
2024 Vol. 45 (2): 150-156 [Abstract] ( 109 ) HTML (1 KB)  PDF (524 KB)  ( 56 )
157 Development of Ultra-low Frost Point Generator
HU Yanqing,Meng Su,CHAI Yuan,CHEN Jiexin, Lü Guoyi,NIE Jing
DOI: 10.3969/j.issn.1000-1158.2024.02.03
A novel ultra-low frost point generator (CIMM-TH) has been developed by using the two-temperature and two-pressure method in the frost point temperature range from -110℃ to -20℃. The core components of the saturator and thermostat were optimized, and the saturation efficiency of the saturator was verified by using two modes of “evaporation” and “condensation”. Under different saturation temperature and pressure conditions, a cold mirror precision dew-point meter and a micro-moisture meter were used to compare with the generator. The test results show that when the frost point temperature is -90℃, the deviation between the dew-point meter and the generator is 0.02℃. When the saturation pressure is 1MPa and the saturation temperature is -99.60℃, the deviation of frost point temperature between the micro moisture meter and the generator is 0.04℃. The uncertainty factors affecting the measurement results of the generator are analyzed systematically. The expanded uncertainty of the generator is 0.38℃, 0.20℃ and 0.19℃ at the frost point of -110℃, -90℃ and -20℃, respectively, k=2.
2024 Vol. 45 (2): 157-163 [Abstract] ( 114 ) HTML (1 KB)  PDF (670 KB)  ( 66 )
164 An Infrared Temperature Measurement Compensation Method Based on Emissivity Correction Model
MI Songtao,ZHANG Yucun,FU Xianbin,YAN Fang,KONG Tao
DOI: 10.3969/j.issn.1000-1158.2024.02.04
At present, the infrared temperature measurement method is affected by the surface emissivity of the measured object, which makes the measurement results have errors. By analyzing the influence of surface roughness on surface infrared emissivity, an infrared temperature compensation method based on emissivity correction model is proposed. Firstly, an infrared temperature compensation algorithm for surface roughness correction is established based on the principle of infrared temperature measurement. Secondly, in order to determine the surface emissivity correction in the infrared temperature compensation method, a rough surface emissivity correction model is established by two-scale rough surface. Finally, in order to verify the feasibility of the proposed infrared temperature measurement compensation method, the measurement results before and after the compensation algorithm are compared in the infrared temperature measurement experiment of friction stir welding seam. The maximum error of infrared temperature measurement is reduced from 9.64℃ to 2.97℃, and the average measurement error is reduced from 3.57℃ to 0.71℃, indicating that the proposed infrared compensation temperature measurement method can improve the accuracy of infrared temperature measurement.
2024 Vol. 45 (2): 164-169 [Abstract] ( 86 ) HTML (1 KB)  PDF (466 KB)  ( 82 )
170 Research on Laser Detection System and Related Algorithms of Oil Spill on Sea Surface
WU Peiliang,WANG Zhiwei,KONG Deming,CUI Yongqiang,MA Qinyong
DOI: 10.3969/j.issn.1000-1158.2024.02.05
Laser-induced fluorescence (LIF) is one of the most effective techniques for oil spill detection on the sea surface, but the oil film thickness inversion algorithm based on this technique is not suitable for evaluating thick oil films(>800μm). The laser has strong directivity and concentrated energy, and it has been shown to have the ability to evaluate the sea surface oil film. However, the existing detection systems suppress or remove the laser signal as an interference signal. To retrieve the signal to detect the thick oil film on the sea surface, a laser detection system for oil spills on the sea surface is studied, and its coordinated control method is discussed. Based on this system, a model for evaluating sea surface thick oil film using a laser reflection signal is established. By selecting the mixture of crude oil and white oil (150) as the experimental oil, the feasibility of the sea surface oil spill laser detection system and the effectiveness of the oil film thickness evaluation algorithm are verified.
2024 Vol. 45 (2): 170-177 [Abstract] ( 86 ) HTML (1 KB)  PDF (679 KB)  ( 41 )
178 Ultra-close Vehicle Chassis Imaging Measurement under Non-uniform Speed
ZHANG Yueying,YIN Qihao,JING Genqiang,YAN Luxin,WANG Xiangxun
DOI: 10.3969/j.issn.1000-1158.2024.02.06
Aiming at the technical problems of axle-type recognition under the condition of non-uniform vehicle speed, such as ultra-close distance, large area, and low distortion imaging, a method of ultra-close imaging correction and mosaic for vehicle chassis with speed-adaptive ability is proposed. The ultra-wide-angle image sequences of a moving vehicle chassis are collected by a fish-eye camera, and a method of circle fitting by multi-sample points is proposed to extract the region of interest (ROI). The method for image distortion correction is then performed using an isometric projection model based on the 3D imaging geometry model. Aiming at the problem of vehicles non-uniform speed, which leads to large range of the overlap area between videos adjacent frames, a multi-step layered key frame extraction is carried out with image content overlap analysis technology, avoiding the influence of uneven image distribution on mosaic results. The experimental results show that the proposed method can obtain clear and complete vehicle chassis images with lower distortion at the distance of 20～50cm under the condition of non-uniform vehicle speed, with a 5% average measuring error of the vehicle axles distance.
2024 Vol. 45 (2): 178-185 [Abstract] ( 73 ) HTML (1 KB)  PDF (741 KB)  ( 52 )
186 Improved Lightweight Pedestrian Target Detection Algorithm
JIN Mei,REN Tingting,ZHANG Liguo,YAN Mengxiao,SHEN Minghao
DOI: 10.3969/j.issn.1000-1158.2024.02.07
A lightweight pedestrian detection algorithm based on feature fusion is proposed to solve the problem of low detection accuracy caused by dense pedestrian targets, small target scales, and varying background illumination around the target. Firstly, build a new backbone feature extraction network (CSPDarknet53-S), and add a new feature extraction module (REM) to the original backbone network to enhance the networks ability to extract pedestrian features. Secondly, improve the feature fusion structure. After extracting high-low feature maps from the backbone network, add a feature fusion module (RM block) between the backbone network and the feature fusion network to increase the receptive field. And then introduce shallow feature information to retain more small target features to form a new feature fusion network (IFFM). Finally, the fused feature map is processed through YOLO Head to obtain the output results. The above steps are based on the basic framework of TinyYOLOv4. Experimental results show that the proposed algorithm achieves higher detection accuracy and better detection results on pedestrian data sets (PASCAL VOC2007 and VOC2012 person data).
2024 Vol. 45 (2): 186-193 [Abstract] ( 142 ) HTML (1 KB)  PDF (924 KB)  ( 162 )
194 Adjustable Laser Beam Width Device Based on Spatial Light Modulator
MI Chenkun,YANG Zhaohui,LIU Hongxin,WANG Fei
DOI: 10.3969/j.issn.1000-1158.2024.02.08
In order to meet the traceability requirements of the laser industry for the beam width measuring device and improve the laser beam width calibration capability, a device which the laser beam width is continuously adjustable based on spatial light modulator (SLM) has been designed for the calibration of different beam widths of lasers in the 400~700nm wavelength range, which is used for the calibration of beam quality analyzers or laser spot measurement instruments. The experimental results show that the device is continuously adjustable in the width range of 0.1~5.0mm. This device utilizes the strong ability of partially coherent beams to resist environmental disturbances, its short-term stability is 99.5% and long-term stability is 99.1%, better than the short-term stability and long-term stability of reference laser which is 96.8% and 96.3% respectively. In addition, based on the superior beam shaping ability of SLM, the device can output the irregular beam to Gaussian beam.
2024 Vol. 45 (2): 194-198 [Abstract] ( 114 ) HTML (1 KB)  PDF (382 KB)  ( 37 )
199 Numerical Simulation Analysis and Experimental Verification of Velocity Flow Field of Large-diameter Special-Shaped Square Tube
JIA Lu,ZENG Yongzhong,LIU Xiaobing,YU Zhishun,XIAO Wenzhuo
DOI: 10.3969/j.issn.1000-1158.2024.02.09
For large-diameter irregular square pipes with a diameter exceeding 1m, where the length of the curved section is short and there are no long straight pipes before and after, and the flow field inside the pipe is complex, there is a need for accurate measurement of the pipe flow. In this regard, a numerical simulation analysis is conducted, proposing a mean velocity evaluation method based on the coefficient of variation. This method selects multiple points that best represent the average flow velocity of the pipe, determining the insertion depth of the sensors and the weight coefficients of multiple measuring points. A calculation formula is then derived, with the cross-sectional average velocity as the function and the velocity values at multiple points in the flow field as the independent variable.Flow measurement experiments are conducted on a wind tunnel test bench, and the calculated values obtained from the formula derived through numerical analysis are compared. The relative error within the full range is less than 0.54%.
2024 Vol. 45 (2): 199-206 [Abstract] ( 76 ) HTML (1 KB)  PDF (811 KB)  ( 152 )
207 Image Reconstruction of Electrical Capacitance Tomography Based on Nonconvex Entropy Minimization and Gaussian Mixture Model Clustering
ZHANG Lifeng,LU Dongchen,LIU Weiliang
DOI: 10.3969/j.issn.1000-1158.2024.02.10
Based on the principle of compressed sensing, a method of constructing nonconvex entropy (NE) function as regularization term is proposed, which can effectively alleviate the inverse problem of electrical capacitance tomography (ECT) ill-condition and ensure the sparseness of the solution. Fast iterative threshold contraction algorithm (FISTA) is used to accelerate the convergence rate. The obtained solution is optimized by Gaussian mixture model (GMM), and the model parameters are updated by expectation maximization algorithm (E-M). After that, NE-GMM algorithm is obtained. Both simulation and experimental results show that reconstructed images with the best quality can be obtained using NE-GMM algorithm compared with LBP, Landweber, iterative hard threshold (IHT), ADMM-L1 and NE algorithms, especially the fidelity of center distribution and multi-object distribution is further improved. The average relative error and correlation coefficient of the simulated reconstructed image obtained by this method are respectively 0.4611 and 0.8827, which are superior to the other five methods.
2024 Vol. 45 (2): 207-213 [Abstract] ( 74 ) HTML (1 KB)  PDF (547 KB)  ( 51 )
214 ECT Image Reconstruction Based on Parallel Adaptive Residual Network with CBAM
MA Min,WU Huan
DOI: 10.3969/j.issn.1000-1158.2024.02.11
In order to solve the problem that soft effect in capacitance tomography should lead to low accuracy of reconstructed image, a parallel adaptive residual network with convolutional attention mechanism image reconstruction algorithm is proposed. The parallel adaptive residual module is used to extract the rich feature layer information. The weight coefficients of each channel are adjusted by the squeeze and excitation networks to filter the redundant information. The convolutional attention mechanism is used to learn the channel and space information of the shallow feature. The feature fusion between the convolutional attention mechanism channel and the parallel adaptive residual network is proposed to compensate the lost shallow features and spatial information. Simulation results show that compared with LBP algorithm, Landweber iterative algorithm and 1DCNN algorithm, the improved algorithm can guarantee real-time performance and improve reconstruction quality effectively.
2024 Vol. 45 (2): 214-221 [Abstract] ( 85 ) HTML (1 KB)  PDF (633 KB)  ( 39 )
222 Sensitivity Field Optimization Method for Coplanar Array Electrodes
WEN Yingtang,WANG Kai,ZHANG Yuyan,ZONG Lewen,PAN Zhao
DOI: 10.3969/j.issn.1000-1158.2024.02.12
In order to improve the imaging quality and stability of the coplanar 3×4 array capacitive imaging system, a method of data dimensionality reduction combined with square sensitivity enhancement is proposed to optimize the sensitive field. The method is based on the principle of maximum entropy to realize the adaptive dimensionality reduction and optimization of the sensitive field, and the reconstructed feature sensitive field has higher feature matching with the actual sensitive field. In addition, the squared sensitivity enhancement method can enhance the contrast between the sensitive field feature data and the non-feature data, and can also attenuate the feature edge volatility caused by the sensitive field vector solution. Finally, the effectiveness of the proposed optimization method is verified by designing several sets of experiments with a coplanar 3×4 array capacitive imaging system, and the results show that the quality and stability of the reconstructed images are significantly improved after the sensitive field optimization.
2024 Vol. 45 (2): 222-230 [Abstract] ( 69 ) HTML (1 KB)  PDF (873 KB)  ( 27 )
231 Research on Adjustment Method of Distance Between Center of Mass and Optical Center of Falling Body in Absolute Gravimeter
FAN Feng,YANG Peixi,WANG Qiyu,FENG Jinyang,YAO Jiamin,HU Ruo,WU Shuqing
DOI: 10.3969/j.issn.1000-1158.2024.02.13
To minimize measurement error of gravity acceleration induced falling body rotation in absolute gravimeter based on laser interferometry, a method for adjusting the distance between center of mass(COM) and the optical center(OC) based on falling body suspension was proposed. Combined with the external structure of falling body, a simple and efficient falling body adjusting device was built. The device adopted photoelectric autocollimator to measure the pitch angle of the falling body in suspension state, which can adjust the position of COM of falling body, and then completed the adjustment of the distance between COM and OC. The uncertainty of the systematic measurement was also evaluated, and the synthetic standard uncertainty of the distance measurement was 18.85μm. Finally, the falling bodies adjusted by suspension method was put into the NIM-3A absolute gravimeter for experimental. The results show that the distance between COM and OC is better than 20μm, which is in line with the estimated uncertainty results. If the angular velocity of the falling body is controlled within 0.02rad/s, the measurement uncertainty of the gravitational acceleration introduced by the falling body rotation is better than 1μGal.
2024 Vol. 45 (2): 231-237 [Abstract] ( 65 ) HTML (1 KB)  PDF (523 KB)  ( 31 )
238 Influence of Anti-skid Stripes on Weighing Accuracy of Flat DynamicWeighing Instrument Based on Elastic Roller Contact Model
LAI Zhengchuang,CHI Hui,YANG Xiaoxiang,ZHANG Weihao
DOI: 10.3969/j.issn.1000-1158.2024.02.14
When dynamic weighing is carried out, the vertical undulation of the anti-skid pattern on the scale platform can cause vibrations in the vehicle, affecting weighing accuracy. To address this issue, a dynamic model of the vehicle weighing process was established, considering the compliance characteristics of the tires. An elastic roller contact model was developed, and the equivalent road surface generated by the anti-skid pattern was used as the input excitation for the dynamic model. The influence of a novel symmetrical anti-skid pattern on the accuracy of weighing in a flatbed scale under various factors was analyzed. Simulation results indicate that as the width of the anti-skid pattern increases, the vibration force on the vehicle increases, leading to an increase in weighing error. When the spacing between pit-type anti-skid patterns is 235mm, the excitation frequency generated approaches the natural frequency of the vehicle, causing resonance between the vehicle and the scale platform. The weighing error can reach a maximum of 0.21%. The vibration force and weighing error generated by triangular pit-type anti-skid patterns are lower than those of rectangular pits. Additionally, at higher speeds, the generation of anti-skid patterns results in larger weighing errors.
2024 Vol. 45 (2): 238-245 [Abstract] ( 74 ) HTML (1 KB)  PDF (730 KB)  ( 20 )
246 Homogeneity Characterization of Composite Shaped Components Based on Pixel Marking Method
ZHANG Yuyan,LI Qihang,WEN Yintang
DOI: 10.3969/j.issn.1000-1158.2024.02.15
The structural inhomogeneity caused by pore defects in fiber-reinforced ceramic matrix composites will seriously affect the macroscopic mechanical properties of the components, while the overall porosity cannot effectively characterize the homogeneity. Aiming at this problem, a spatial block division method based on pixel labeling is proposed to realize the automatic block division of CT scan volume data of special-shaped components . On the basis of calculating the porosity value of each block, the product of the mean porosity and the standard deviation is used as the index to quantitatively characterize the structural uniformity of the components. The 3D mapping of the porosity is carried out by the ray projection method, and the porosity distribution is visualized and characterized. The results show that the method can effectively quantitatively characterize the overall and local uniformity of the special-shaped component, and give the local component from a 3D perspective. The size and spatial position information of the porosity provide a strong basis for further optimizing the manufacturing process parameters and improving the reliability of component service.
2024 Vol. 45 (2): 246-252 [Abstract] ( 78 ) HTML (1 KB)  PDF (544 KB)  ( 39 )
253 Microgrid Fault Identification and Location Based on BA-MKELM
WU Zhongqiang,LU Xueqin
DOI: 10.3969/j.issn.1000-1158.2024.02.16
A microgrid fault identification and location method based on Bayesian algorithm optimizing multi-kernel extreme learning machine is proposed. Aiming at the problem of insufficient regression ability caused by the random selection of input parameters and hidden layer nodes of extreme learning machine, the kernel function is introduced, and the polynomial and the Gaussian radial basis kernel function are combined to form a multi- kernel extreme learning machine to establish a fault identification and location model. The Bayesian algorithm is used to optimize the relevant parameters of the multi-kernel extreme learning machine to further improve the approximation ability of the model. In order to verify the fault identification and location performance of the proposed model, extreme learning machine and multi-kernel extreme learning machine are selected to establish fault diagnosis models respectively for comparative analysis. Experimental results show that the proposed method can identify and locate any type of faults in the microgrid with high performance, and has higher recognition and location accuracy.
2024 Vol. 45 (2): 253-260 [Abstract] ( 105 ) HTML (1 KB)  PDF (601 KB)  ( 86 )
261 Research on the Fiber-optic Calibration Technology for the Reliability Test Power Supply of Molded Case Circuit Breakers
ZHANG Heng,LI Lingzhi,LI Chuansheng,TAN Xiangyu,ZHOU Fangrong,CAI Hui
DOI: 10.3969/j.issn.1000-1158.2024.02.17
In consideration of the characteristic properties of the reliability test current for the molded case circuit breakers (MCCB) including high value, short time and AC/DC hybrid and the high requirements of field conditions to the reference high current sensors, a field calibration method of reliability test power supply for the MCCB based on the fiber-optic current sensing technology is proposed. The dynamic model of the sensor is established according to the closed-loop signal-detecting principle of the fiber-optic current sensor. The step response and frequency response characteristics of the system are analyzed. The simulation results show that by adjusting the forward gain and sliding filter order of the system, the rise time of the sensor is better than 9.09μs, and the -3dB bandwidth can reach 39.91kHz, and prove the tracking response capability of the sensor to the reliability test current of the MCCB. The fiber-optic current sensor is calibrated based on the equal ampere-turn method. The uncertainty of the calibration result is evaluated, and the results show that within the range of 2.5kA to 60kA, the measurement accuracy of the sensors DC and power frequency currents is better than 0.2%. The field test of the reliability test current of the MCCB is performed. The mentioned research provides a technical route for the field calibration of the reliability test power supply of the molded case circuit breaker.
2024 Vol. 45 (2): 261-268 [Abstract] ( 82 ) HTML (1 KB)  PDF (658 KB)  ( 38 )
269 Research on Bayesian Network Structure Learning Based on Hybrid Simplified Particle Swarm Algorithm
LIU Haoran,LI Sheng,CUI Shaopeng,WANG Niantai,CAI Yanbin,SHI Qianrui,ZHANG Liyue
DOI: 10.3969/j.issn.1000-1158.2024.02.18
In order to improve the problems that the current Bayesian network structure learning algorithm tends to fall into local optimization, premature convergence and low optimization efficiency, a hybrid simplified particle swarm algorithm is proposed to optimize Bayesian network structure learning(BNs-HsPSO). The algorithm uses the maximum support tree to constrain the search space, and proposes an initial orientation strategy combining V-structure and conditional relative average entropy(CRAE), and then uses the mountain-climbing strategy to establish the initial particle swarm, uses the improved particle swarm optimization algorithm and genetic algorithm to iteratively optimize the initial population, proposes a conditional crossing and mutation strategy in the iterative process to avoid random divergence update of particles, and updates the unoptimized particles in combination with the sub-particle slowing strategy to avoid the algorithm falling into local optimum. The algorithm is compared with other algorithms in simulation experiments under four standard networks.The experimental results show that the proposed algorithm has an average higher BIC score of 5.775%, 5.8%, 0.475%, and 2.75% compared to MMHC, GS, BNC-PSO, and PC-PSO algorithms in ASIA, CAR, CHILD, and ARM networks, respectively; the Hamming distance HD is lower and the accuracy ACC is higher.
2024 Vol. 45 (2): 269-278 [Abstract] ( 118 ) HTML (1 KB)  PDF (858 KB)  ( 137 )
279 Unified Calibration and Low-Level Concentration Comparison of Standard Radon Monitors in China
SUN Changhao,YANG Zhijie,LIU Meiling,LIU Haoran,ZHANG Jian,LIANG Juncheng
DOI: 10.3969/j.issn.1000-1158.2024.02.19
To improve the capacity of radon metrology in China, the standard radon monitors from 11 standard laboratories were calibrated uniformly. The low-level concentration comparison was conducted base on the unified calibration. The unified calibration was carried out at 700~3000Bq/m3 radon concentration, and the reference value of radon concentration can be traced to the primary standard of radon activity, Urel=1.6% (k=2). The range of response to reference radon atmosphere for standard radon monitors are 0.93~1.02, and the uncertainties range are 2.2%~3.6% (k=2). The low-level concentration comparison was carried out at 100~400Bq/m3, the most standard radon monitors En<1. By optimizing the strategy, it is feasible for standard radon moniters to transfer above 100Bq/m3. However, it is necessary to improve the ability of measurement and concentration control for each laboratory to carry out transfer at concentration of 100Bq/m3 or below.
2024 Vol. 45 (2): 279-284 [Abstract] ( 92 ) HTML (1 KB)  PDF (509 KB)  ( 25 )
285 NOx Concentration Prediction Model Based on Feature Optimization and BSO-RBF Neural Network
ZHANG Guoxing,WANG Shipeng
DOI: 10.3969/j.issn.1000-1158.2024.02.20
In the process of thermal power generation, the operation condition of combustion system is complicated and the delay is large, which makes it difficult to accurately measure the inlet NOx mass concentration in the selective catalytic reduction (SCR) flue gas denitration system. To solve this problem, a prediction model based on feature optimization and radial basis (RBF) neural network is proposed. Firstly, the variable after feature optimization is taken as the final input variable of the model. Secondly, the beetle swarm optimization (BSO) is used to optimize the neural network hyperparameters. Finally, a prediction model of inlet NOx concentration is established. The results show that the predictive results of the optimized variables are better than those of the original variables. After feature optimization and timely delay, the SRMSE of the model decreased by 44.5%, and the R2 increased by 2.3%. The neural network hyperparameters determined by BSO also improved the accuracy of the model.
2024 Vol. 45 (2): 285-293 [Abstract] ( 100 ) HTML (1 KB)  PDF (744 KB)  ( 47 )
294 Research of a Reference Material of Inactivated Influenza A (H1N1) Virus
XU Li,YUE Lihuan,YANG Xue,WANG Zhaokun,LI Lanying,WEN Yanli,TAO Qing,HU Yihong,LIU Gang
DOI: 10.3969/j.issn.1000-1158.2024.02.21
A reference material (RM) of inactivated influenza A (H1N1) virus was developed. The RM was made of artificially cultured natural virus as raw materials. After chemical inactivation and verification of the inactivation effect, the copy number concentration was determined by digital PCR (dPCR) in different laboratories. The homogeneity, stability and uncertainty of the RM were evaluated in detail. As the results demonstrated, the RM can be stably stored for more than 5 months under -80~-70℃. The final certified value of reference materials was (1384.5±249.3) copies/μL (k=2). The RM can be used for the metrological traceability and quality control in the whole process of influenza A virus H1N1 detection and help to improve the accuracy and reliability of related nucleic acid test results.
2024 Vol. 45 (2): 294-299 [Abstract] ( 85 ) HTML (1 KB)  PDF (529 KB)  ( 48 )
300 The Research on Target Hit Probability Estimation and Judging Method Using Bayesian Filtering Theory
JING Peiliang,DUAN Yu,JIANG Shuangshuang,GAO Hong
DOI: 10.3969/j.issn.1000-1158.2024.02.22
In order to depress the wrong judging rate of the target hit probability during the ordnance test,a target hit probability estimation and judging method using Bayesian filtering theory is proposed.Through this method, the statistical mathematical model of target hit probability and experimental observation data is constructed. Then, based on Bayesian filtering theory, analytical expressions of posterior probability density function, posterior mean estimation and mean square error of hit probability are derived. We generate observation data based on different real target hit probabilities, and carry out estimation and decision experiments using traditional methods and the proposed methods respectively.The results show that the decision error rate of the proposed method is only 1/3 of that of the traditional method, which proves that the proposed method is feasible.
2024 Vol. 45 (2): 300-304 [Abstract] ( 103 ) HTML (1 KB)  PDF (486 KB)  ( 40 )
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