|
|
|
| Study on Transfer Standard Stability of Flow Facilities Comparison Based on Principal Component Analysis |
| MENG Tao1,2, WANG Chi2, XING Chao2 |
1. School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China
2. National Institute of Metrology, Beijing 100029, China |
|
|
|
|
Abstract A transfer standard that were composed of an electromagnetic flowmeter and a turbine flowmeter connecting in serial was designed for water flow facilities comparison. The principal component analysis method was used to separate the dispersion of the comparison participating facilities and the fluctuation of transfer standard, and its principle and implementation process were presented. The applicability of the principal component analysis method was studied. According to the relationship between different principal components, a set of evaluation criteria for the transfer standard stability was proposed. Taking a water flow facilities comparison as an example, the validity of the comparison result was evaluated from the perspective of transfer standard stability, and the estimated value is 0.015%. The method improves the reliability of the evaluation standard for comparison, and can also be used to optimize the comparison route and shorten the comparison time.
|
|
Received: 03 September 2018
Published: 01 September 2019
|
|
|
|
|
|
［1］王健, 丁京鞍, 姚弘, 等. 全国分量砝码比对的研究［J］. 计量学报, 2013, 34(3):251-255.
Wang J, Ding J A, Yao H, et al. Subdivision weights comparison in China［J］. Acta Metrologica Sinica, 2013, 34(3):251-255.
［2］国家质量监督检验检疫总局. JJF1117-2010计量比对 ［S］. 2011.
［3］周宪英, 高成文, 曹建华. 主成分分析法及其在数据降噪中的应用［J］. 兵工自动化, 2014, 33(9):55-58.
Zhou X. Y, Gao C W, Cao J H. Principal component analysis method and its application in data noise reducing［J］. Ordnance Industry Automation, 2014, 33(9):55-58.
［4］何群,王红,江国乾,等. 基于相关主成分分析和极限学习机的风电机组主轴承状态监测研究［J］.计量学报, 2018,39(1): 89-93.
He Q,Wang H,Jiang G Q, et al. Research of Wind Turbine Main Bearing Condition Monitoring Based on Correlation PCA and ELM［J］. Acta Metrology Sinica, 2017,39(1):89-93.
［5］Potapov P, Longo P, Okunishi E. Enhancement of noisy EDX HRSTEM spectrum-images by combination of filtering and PCA［J］. Micron, 2017, 96:29-37.
［6］岳刚, 马义中. 利用主成分分析分离测量过程中的波动源［J］. 工业工程与管理, 2008, 13(3):37-41.
Yue G, Ma Y Z. Isolating variation of measurement process used principal component analysis［J］. Industrial Engineering and Management, 2008, 13(3):37-41.
［7］Nojiri H, Kimura T. Improvement of stability of electromagnetic flowmeter with non-wetted electrodes in low-conductivity liquid measurement［C］//SICE 2004 Conference. Sapporo, Japan, 2005:1554-1557.
［8］吕波, 徐良旺. 基于磁流体动力学的电磁流量计数值模拟［J］. 计量学报, 2012, 33(6):519-522.
Lü B, Xu L W. Numerical simulation of electromagnetic flowmeter based on magneto hydra dynamics and computational fluid dynamics［J］. Acta Metrologica Sinica, 2012, 33(6):519-522.
［9］Nesterov V N, Andreev I P. Increasing the Accuracy of Turbine Flow Transducers Using the Method of Generalized Influence Variables［J］. Measurement Techniques, 2017, 60(4): 336-342.
［10］Kadappa V, Negi A. A theoretical investigation of feature partitioning principal component analysis methods［J］. Pattern Analysis & Applications, 2016, 19(1):79-91.
［11］Marta F G, Gabriel M F, José C. Evaluation of diagnosis methods in PCA-based Multivariate Statistical Process Control［J］. Chemometrics and Intelligent Laboratory Systems, 2018, 172:194-210.
［12］吴敬华. 主成分分析与二维主成分分析之比较研究［D］. 昆明:云南财经大学, 2014.
［13］Cox M G. The evaluation of key comparison data［J］. Metrologia, 2002, 39(6):589-595.
［14］国家质量技术监督局. GB/T4091-2001常规控制图［S］. 2001. |
|
|
|
2019, Vol. 40 
