Michael A. Minnicino
Papers
1
Total Citations
5
H-Index
1
About
Michael A. Minnicino is a researcher whose work lies at the intersection of structural dynamics, nonlinear system identification, and condition-based maintenance. His most-cited paper, "Detecting and quantifying friction nonlinearity using the Hilbert transform" (2004, 5 citations), introduces a straightforward methodology for identifying and quantifying nonlinear effects such as Coulomb friction and backlash—critical for advancing predictive maintenance in both structural and machine-based applications. By leveraging the Hilbert transform, Minnicino provides engineers with a practical tool to detect subtle nonlinearities that often precede system failure, enhancing the reliability of passive structural systems and rotating machinery alike. Though his citation count is modest, his contributions are notable for their clarity and direct applicability to real-world diagnostics. Minnicino’s work underscores the importance of bridging theoretical signal processing with tangible engineering challenges, offering a foundation for researchers and practitioners aiming to improve the longevity and safety of mechanical and structural systems. His focus on friction nonlinearity remains a key reference for those exploring early fault detection and nonlinear vibration analysis.
Research Focus
Key Achievements
Top Papers
- 1