Ning Li

Mr. Ning Li


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 August 2023 in Sensors
Verified
Journal Article
Open access
PDF file
NLNing Li
Ning Li
YCYuren Chen
Yuren Chen
CZChaofan Zhang
Chaofan Zhang
JNJie Nong
Jie Nong
WXWenjie Xu
Wenjie Xu
Zhenrong ZhangZhenrong Zhang
Zhenrong Zhang
Fiber-optic magnetic field sensors have garnered considerable attention in the field of marine monitoring due to their compact size, robust anti-electromagnetic interference capabilities, corrosion resistance, high sensitivity, ease of multiplexing and integration, and potential for large-scale sensing networks. To enable the detection of marine magnetic field vector information, we propose an optical fiber vector magnetic field sensor that integrates three single-axis sensors in an orthogonal configuration. Theoretical analysis and experimental verification are conducted to investigate its magnetic field and temperature sensing characteristics, and a sensitivity matrix is established to address the cross-sensitivity between the magnetic field and temperature; experimental tests were conducted to assess the vector response of the three-dimensional (3D) vector sensor across the three orthogonal axes; the obtained experimental results illustrate the commendable magnetic field vector response exhibited by the sensor in the orthogonal axes, enabling precise demodulation of vector magnetic field information. This sensor presents several advantages, including cost-effectiveness, easy integration, and reliability vectorially. Consequently, it holds immense potential for critical applications in marine magnetic field network detection.

23 March 2023 in Sensors
Verified
Journal Article
Open access
PDF file
LWLinyi Wei
Linyi Wei
Yang YuYang Yu
Yang Yu
DWDongying Wang
Dongying Wang
SYSiyu Yao
Siyu Yao
NLNing Li
Ning Li
Zhenrong ZhangZhenrong Zhang
Zhenrong Zhang
The magnetic field is a vital physical quantity in nature that is closely related to human production life. Magnetic field sensors (namely magnetometers) have significant application value in scientific research, engineering applications, industrial productions, and so forth. Accompanied by the continuous development of magnetic materials and fiber-sensing technology, fiber sensors based on the Magneto-Refractive Effect (MRE) not only take advantage in compact structure, superior performance, and strong environmental adaptability but also further meet the requirement of the quasi-distributed/distributed magnetic field sensing; they manifest potential and great application value in space detection, marine environmental monitoring, etc. Consequently, the present and prevalent Magneto-Refractive Magnetic Field Fiber Sensors (MR-MFSs) are briefly summarized by this paper, proceeding from the perspective of physicochemical properties; design methods, basic performance and properties are introduced systematically as well. Furthermore, this paper also summarizes key fabrication techniques and future development trends of MR-MFSs, expecting to provide ideas and technical references for staff engaging in relevant research.

11 May 2023 in Sensors
Verified
Journal Article
Open access
PDF file
SZShumao Zhang
Shumao Zhang
Yang YuYang Yu
Yang Yu
Xiaoyang HuXiaoyang Hu
Xiaoyang Hu
QBQiang Bian
Qiang Bian
DWDongying Wang
Dongying Wang
Zhenrong ZhangZhenrong Zhang
Zhenrong Zhang
In the process of ocean exploration, highly accurate and sensitive measurements of seawater temperature and pressure significantly impact the study of seawater’s physical, chemical, and biological processes. In this paper, three different package structures, V-shape, square-shape, and semicircle-shape, are designed and fabricated, and an optical microfiber coupler combined Sagnac loop (OMCSL) is encapsulated in these structures with polydimethylsiloxane (PDMS). Then, the temperature and pressure response characteristics of the OMCSL, under different package structures, are analyzed by simulation and experiment. The experimental results show that structural change hardly affects temperature sensitivity, and square-shape has the highest pressure sensitivity. In addition, with an input error of 1% F.S., temperature and pressure errors were calculated, which shows that a semicircle-shape structure can increase the angle between lines in the sensitivity matrix method (SMM), and reduce the effect of the input error, thus optimizing the ill-conditioned matrix. Finally, this paper shows that using the machine learning method (MLM) effectively improves demodulation accuracy. In conclusion, this paper proposes to optimize the ill-conditioned matrix problem in SMM demodulation by improving sensitivity with structural optimization, which essentially explains the cause of the large errors for multiparameter cross-sensitivity. In addition, this paper proposes to use the MLM to solve the problem of large errors in the SMM, which provides a new method to solve the problem of the ill-conditioned matrix in SMM demodulation. These have practical implications for engineering an all-optical sensor that can be used for detection in the ocean environment.