Dr. Shengnan Zhang | Engineering | Best Researcher Award
NoneĀ at School of Mechatronic Engineering and Automation, Shanghai University
Short Bio
- shengnan zhang is a Ph.D. researcher at Shanghai University specializing in electromagnetic flowmeters, signal processing, and mathematical modeling for industrial processes. With experience in engineering and automation, she integrates theoretical and applied research to enhance industrial measurement accuracy and efficiency.
Professional Profile
Educational Background
- shengnan zhang is currently pursuing a Ph.D. in the School of Mechatronic Engineering and Automation at Shanghai University (2021ā2024). She earned her masterās degree in Control Science and Engineering (Automation) from Inner Mongolia University of Science and Technology in 2020.
Professional Experience
- shengnan zhang has gained diverse experience in both industry and academia. She worked as a junior engineer in the Mechanical and Electrical Department at State Grid Xinyuan Chifeng Company, Inner Mongolia (2020ā2021). She later transitioned into roles as a Hardware R&D Engineer at JiDan Biotechnology Co., Ltd. and a High School Mathematics Teacher at Nanjing Yunjushi Education Co., Ltd. in 2021.
Research Interests
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- Her research focuses on electromagnetic flowmeters, signal processing, and mathematical modeling of complex industrial processes. She is particularly interested in developing advanced computational techniques for industrial automation and measurement systems.
Author Metrics
- Currently, shengnan zhang is actively engaged in research and has contributed to scholarly publications in her field. Her work includes studies on signal processing applications in industrial automation and measurement technologies.
Publication Top Noted
- Study on the Match-Filtering Ability of the Electromagnetic Flowmeter Signals Based on the Generalized Dual-Frequency Walsh Transform
Flow Measurement and Instrumentation, March 2025
DOI: 10.1016/j.flowmeasinst.2024.102767 - Generalized Walsh Transform Sequency-Domain-Based Match Filtering for Electromagnetic Flowmeter Signal Measurement
IEEE Sensors Journal, April 2024
DOI: 10.1109/JSEN.2024.3366238 - A Sequency Match Filtering Algorithm Based on the Generalized Walsh Transform for Processing Rectangular Wave Signals
Review of Scientific Instruments, February 2024
DOI: 10.1063/5.0175079 - Study on Match Filtering Based on Sequency Spectrum Characteristics of the Walsh Transform for Electromagnetic Flowmeter Signal Measurement
Measurement, February 2024
DOI: 10.1016/j.measurement.2023.114021
Conclusion
- Dr. shengnan zhang is a highly qualified researcher with notable contributions to signal processing and industrial measurement systems. Her innovative approaches using Generalized Walsh Transform have the potential to improve electromagnetic flowmeter accuracy significantly. With further collaboration, higher citation impact, and real-world application of her research, she would be an excellent candidate for the Best Researcher Award.