Zhihai Wang
Papers
1
Total Citations
12
H-Index
1
About
Zhihai Wang is a researcher whose work centers on signal processing, control systems, and industrial equipment monitoring. His key contributions address the challenge of reconstructing periodic band-limited signals from non-uniform samples at sub-Nyquist rates—a critical problem for extracting vital state parameters like torque and angle from servo control and drive systems. This work enables more reliable monitoring of equipment operating conditions despite low sampling rates in networked environments. His most-cited paper, "Reconstruction of Periodic Band Limited Signals from Non-Uniform Samples with Sub-Nyquist Sampling Rate" (2020), has garnered 12 citations, reflecting its niche but practical impact. Wang’s research bridges theoretical signal reconstruction with real-world industrial applications, offering solutions for condition-based maintenance and fault detection. By tackling data acquisition limitations in cyber-physical systems, his work supports advancements in smart manufacturing and predictive analytics. For students and researchers in signal processing or industrial automation, Wang’s studies provide foundational methods for extracting meaningful information from sparse, irregular data streams—a growing necessity in the era of the Industrial Internet of Things.
Research Focus
Key Achievements
Top Papers
- 1