Multi-parameter demodulation for temperature, salinity and pressure sensor in seawater based on the semi-encapsulated microfiber Mach-Zehnder interferometer

被引：38

作者：

Liu, Jichao ^{[1
]}

Hou, Yunfei ^{[1
]}

Wang, Jing ^{[1
]}

Zhong, Guoqiang ^{[2
]}

Zhang, Lihui ^{[1
]}

Zhuang, Funa ^{[1
]}

Yu, Lijun ^{[1
]}

Wang, Shanshan ^{[1
]}

机构：

[1] Ocean Univ China, Sch Phys & Optoelect Engn, Opt & Optoelect Lab, Qingdao 266100, Peoples R China

[2] Ocean Univ China, Sch Comp Sci & Technol, Qingdao 266100, Peoples R China

来源：

MEASUREMENT | 2022年 / 196卷

关键词：

Multi-parameter sensing; Temperature; salinity and pressure in seawater; Support vector regression; PSO-SVR; FIBER; PREDICTION;

D O I：

10.1016/j.measurement.2022.111213

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Semi-encapsulated microfiber Mach-Zehnder interferometer is designed and developed for temperature, salinity and pressure (TSP) sensing in seawater. Based on the theoretical analysis, sensing experiment is performed with typical sensitivities of-2312 pm/celcius, 631 pm/parts per thousand, and 3775 pm/MPa, respectively. To demodulate the signal with cross-sensitivity, sensitivity matrix method (SMM) and machine learning method (MLM) are used, respectively. By 25 tests under arbitrary TSP, relatively low errors of about 19.14 %, 4.01 % and 15.75 % are obtained based on the support vector regression (SVR) model. In addition, non-linear dependence of sensitivity on surrounding, SMM accuracy on sensing dips, stability of prediction and influence of the dataset used in training are also investigated. Finally, combination of SMM and MLM is realized, which shows relatively good performance for TSP measurement with errors of 10.67 %, 5.25 % and 16.76 %, respectively.

引用

页数：11

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