2023 Vol. 67, No. 8

literature Metrology
Bibliometric Analysis of Disaster Chain Research in China’s Plateau Regions
HUANG Yongfang, GUO Yonggang, LI Feng, XU Jianyu, JING Xujun
2023, 67(8): 3-15, 53. doi: 10.12338/j.issn.2096-9015.2023.0424
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The study of disaster chains in China, particularly in plateau regions, is currently limited. This paper utilizes CNKI as a data source to investigate the disaster chain literature. Utilizing CiteSpace, it conducts co-occurrence, cluster, and emergence analyses, thereby providing a comprehensive review of the state of disaster chain research and methodologies in these plateau regions. The findings indicate that from 2005 to 2023, the Chinese Journal of Rock Mechanics and Engineering featured the highest number of publications on disaster chains, totaling 13 articles, predominantly within the field of geology, along with interdisciplinary studies. The research hotspots, identified through keyword analyses, include geological disasters, multi-hazard scenarios, natural disasters, risk assessment, and earthquakes. Notable disaster chain types in plateau areas encompass glacial lake and landslide disaster chains. Current research methods predominantly involve numerical simulations and monitoring technologies. Given the plateau region's unique terrain and diverse disaster chain types, there is a need for increased research efforts, particularly focusing on triggering factors. Future studies are expected to enhance monitoring techniques towards greater intelligence and integration with engineering construction.
Emerging Trends and Hot Topics in Digital Twin Research Globally: A CiteSpace Knowledge Graph Analysis
XIAO Shunan, GUO Xiaojian
2023, 67(8): 16-28, 74. doi: 10.12338/j.issn.2096-9015.2023.0215
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This study aims to comprehensively assess the status, emerging trends, and hotspots in digital twin research globally, using bibliometric analysis with data sourced from CNKI and Web of Science databases. Through CiteSpace, a knowledge graph of digital twin research both domestically and internationally was constructed to evaluate its strengths, weaknesses, and future directions. The findings indicate: 1) an increasing interest in digital twin research globally, with a consistent rise in publication numbers. 2) Currently, there is no prominent core group of authors in the digital twin domain, either in China or internationally. Collaboration rates among research institutions are higher internationally compared to domestic collaborations in China, though Chinese institutions display greater diversity. While China leads in publication quantity in this field, its global influence requires enhancement. 3) The research frontiers in digital twin studies show similarities worldwide, focusing mainly on applications in intelligent manufacturing, exploration of key technologies, and the intelligent application of digital twins across various domains.
Research Progress
Advancements and Future Perspectives in Transgenic Protein Detection Technology
NING Chengxiang, WU Liqing
2023, 67(8): 29-35. doi: 10.12338/j.issn.2096-9015.2023.0220
Abstract(189) HTML (56) PDF(26)
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Transgenic technology significantly contributes to enhancing crop yields, mitigating environmental pollution, and addressing food shortages. Central to this technology, transgenic protein assays, which directly detect expression products, facilitate rapid on-site testing and are crucial in transgenic safety regulation. This article delves into the cultivation of transgenic crops, outlines detection standards, and highlights the superiority of transgenic protein detection over nucleic acid assays. It comprehensively reviews the principles, merits, drawbacks, and applications of prevalent transgenic protein detection methods, such as enzyme-linked immunoassay, immunoblotting, test strip methods, mass spectrometry, biosensors, protein arrays, and immuno-PCR. Additionally, the article projects future trends in transgenic protein detection, exploring prospects for rapid, portable, high-throughput, multi-target detection, advanced signal amplification, ultra-sensitive single-molecule detection, and integrated, fully-automated systems. This work offers valuable insights into the current state and future directions of transgenic protein detection technology, serving as a key reference for the development of detection standards in this field.
Impact Studies in Metrology
Impact of High Altitude on Breath Alcohol Analyzer Measurements
LIU Yiling, NIMA Quzong, PAN Weijiang, HAO Jingkun
2023, 67(8): 36-42. doi: 10.12338/j.issn.2096-9015.2023.0267
Abstract(173) HTML (66) PDF(11)
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The breath alcohol analyzer, or breathalyzer, is essential for measuring breath alcohol content in law enforcement, particularly in drunk driving cases. Operating on two principal mechanisms - fuel cell and infrared absorption - these devices are deployed at various altitudes by traffic control authorities across China. Accurate readings are critical for ensuring rigorous and fair law enforcement. According to China’s National Verification Regulation JJG657-2019 for breath alcohol analyzers, these instruments are tested using first-class national certified reference materials (CRMs C2H5OH/Air) or ethanol standard gas. Appendix C indicates that the reference materials’ property values, measured in mg/L, are influenced by atmospheric pressure, necessitating corrections based on the pressure at the usage location. However, the extent to which atmospheric pressure affects the breathalyzer’s accuracy remains understudied. This study investigates the impact of altitude on measurement accuracy for both types of breathalyzers, conducting field verifications at 20 m and 3560 m altitudes. The results show that, for fuel cell type analyzers commonly used by traffic police, the deviation at critical points for determining drunk driving does not exceed 0.04 mg/L. Altitude impacts on these devices fall within a manageable error range, preserving measurement accuracy. Thus, accurate breath alcohol measurement for drunk driving law enforcement remains viable in China’s high-altitude regions.
Experimental Design for Verifying the Time-Frequency Domain Performance of Specular Single Cone Electric Field Standard Devices
ZHANG Huiru, LIN Haoyu, HE Zibin, LU Runxi, XING Hao, WANG Biyun, WANG Ziyue
2023, 67(8): 43-47, 60. doi: 10.12338/j.issn.2096-9015.2023.0234
Abstract(109) HTML (69) PDF(12)
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This study proposes a method to verify the time domain and frequency domain performance of specular single cone electric field standard devices, drawing on an analysis of relevant international and domestic standards and research. In the time domain, pulse waveform parameters (amplitude, rise time, pulse width) of the transient electromagnetic pulse electric fields generated by both the specular single cone electric field standard device and the TEM chamber are compared. In the frequency domain, the comparison is made between the continuous-wave electric field strengths generated by the specular single cone device and the μTEM chamber. The En value is employed to assess the comparison results in both time and frequency domain performance verifications. This research, focusing on the development of a time-frequency domain performance verification method for specular single cone electric field standard devices, addresses the challenges in verifying both time and frequency domain performances of these devices. It is crucial for ensuring the accuracy of pulse electric field measurements in China and for harmonizing the transient pulse electric field parameters.
Measurement Methods and Techniques
Enhancing Vehicle Terminal Positioning Accuracy Using Neural Network and Lagged Variable Regression
LI Yang, ZHANG Jian, CHENG Xu
2023, 67(8): 48-53. doi: 10.12338/j.issn.2096-9015.2023.0222
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The existing onboard positioning terminals face challenges of significant positioning errors and slow update speeds. This paper analyzes the factors influencing these errors and proposes a method for correcting vehicle terminal positioning errors using a BP neural network and lagged variable regression. Comparative analysis of three measurement data sets before and after correction shows maximum positioning error reductions of 88.2%, 85.4%, and 85.8%, respectively. Additionally, the comparison of pre- and post-correction positioning errors with measured data validates the effectiveness of the developed model utilizing BP neural networks and lagged variable regression for positioning error correction.
Predictive Analysis and Algorithmic Comparison for Faults in Laboratory Force-Measuring Equipment
ZHANG Xuemei, KONG Xiangji
2023, 67(8): 54-60. doi: 10.12338/j.issn.2096-9015.2023.0208
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This study aims to elevate digital equipment management and reduce laboratory management costs by developing a predictive model for laboratory equipment faults, thus making effective use of fault data. Operational fault data from force-measuring equipment was selected for analysis. A correlation analysis of influencing factors was conducted using statistical methods, and three regression models—RidgeCV, XGBoost, and LightGBM—were employed to fit the dataset. These models were compared to select the most appropriate algorithm for predicting the time before the first equipment fault. Model accuracy was evaluated using r2, mean squared error, explained variance, and mean absolute error. The LightGBM algorithm, optimized through grid search and cross-validation, demonstrated the best predictive accuracy and operational speed. Key features for determining the time before the first fault included the equipment's service time and its original value. By effectively managing equipment fault data and leveraging big data analysis techniques, a tailored fault prediction model for various equipment types can be established, paving the way for enhanced laboratory management efficiency and quality.
Calibration Research of Digital Recorders for Impulse Measurements
GUO Binbin, WANG Xiaofei
2023, 67(8): 61-68. doi: 10.12338/j.issn.2096-9015.2023.0203
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This study aims to ensure the accuracy and reliability of voltage and current measurement systems used in impulse testing by examining and quantifying the impact of digital recorders on impulse measurement outcomes. It focuses on the influence of range selection in digital recorders and evaluates their performance within these systems. The paper outlines calibration methods, procedures, and principles for impulse-specific digital recorders, discussing the technical specifications and calibration device feasibility. The study also proposes an experimental approach to evaluate the effect of range selection on digital recorders, using high-precision models PXI-5124, PXIe-5164, and PXIe-5172. Results reveal a consistent relationship between measurement range and error: larger ranges result in greater peak errors but reduced time parameter errors. Optimal measurement ranges for peak and time parameter accuracy are identified for each recorder. Furthermore, a methodology to calculate recorder uncertainty is presented. For the PXIe-5164 at a 10V range, under a 0.84/60 waveform, the expanded uncertainty (k=2) was determined: Ut at 0.15%, T1 at 2.1%, and T2 at 0.51%. This research thoroughly assesses digital recorder performance, their role in the uncertainty of impulse measurement systems, and contributes to enhancing both the theoretical and practical aspects of these systems.
Metrological Characteristic Research of Biosafety Cabinets
WU Xiao, LI Hao, WANG Zhidong, GAO Yunhua
2023, 67(8): 69-74. doi: 10.12338/j.issn.2096-9015.2023.0211
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This study explores the variation in performance across different models of Class II biosafety cabinets and the complexity of their metrological operations. It focuses on developing simple yet effective testing procedures for primary users of these cabinets, facilitating periodic verification during use. The research ensures that users at the basic level can confirm the equipment's performance through minimal operations during routine checks. The experimental phase involves optimizing the measurement methods for the metrological characteristics of biosafety cabinets and contrasting these optimized methods with standard testing protocols to evaluate their feasibility. Key findings include simplifications in cleanliness testing to four points, illumination intensity testing to five evenly spaced points, noise detection to two points replicating human ear noise reception, downward airflow speed to a three-point method, and inflow airflow speed to six points at a 45° angle, with the optimal smoke emission point being close to the fan. The results from the optimized methods closely match those from standard tests across various metrological characteristics of biosafety cabinets. This refined approach for testing biosafety cabinets allows frontline users to rapidly assess the current performance of these cabinets, contributing to the study of their metrological characteristics, early identification of biosafety hazards, and prevention of laboratory biological incidents.