Almost all engineered systems are nonlinear and show nonlinear phenomena that can only be predicted by nonlinear models. However, the application of model-based approaches for diagnostics has been constrained mostly to linearized or simplified models. This paper introduces a fundamental approach for characterization of nonlinear response of systems based on the topology of the phase space trajectory. The method uses the density distribution of the system states to quantify this topology and extracts features that can be used for system diagnostics. The proposed method has been employed to diagnose a multi degree of freedom system with various simultaneous defects.
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Fekrmandi, H. (2015). Development of new structural health monitoring techniques.
Kappaganthu, K., & Nataraj, C. (2011). Nonlinear modeling and analysis of a rolling element bearing with a clearance. Communications in Nonlinear Science and Numerical Simulation, 16(10), 4134-4145.
Letellier, C., Le Sceller, L., Dutertre, P., Gouesbet, G., Fei, Z., & Hudson, J. (1995). Topological characterization and global vector field reconstruction of an experimental electrochemical system. The Journal of Physical Chemistry, 99(18), 7016–7027.
Mevel, B., & Guyader, J. L. (1993). Routes to chaos in ball bearings. Journal of Sound and Vibration, 162(3), 471- 487.
Rezvanizaniani, S. M., Dempsey, J., & Lee, J. (2014). An effective predictive maintenance approach based on historical maintenance data using a probabilistic risk assessment: PHM14 data challenge. International Journal of Prognostics and Health Management.
Samadani,M., Kwuimy, C. K., & Nataraj, C. (2015). Modelbased fault diagnostics of nonlinear systems using the features of the phase space response. Communications in Nonlinear Science and Numerical Simulation, 20(2), 583–593.
Sankaravelu, A., Noah, S. T., & Burger, C. P. (1994). Bifurcation and chaos in ball bearings. ASME Applied Mechanics Division-publications, 192, 313-313.
Tufillaro, N., Holzner, R., Flepp, L., Brun, E., Finardi, M., & Badii, R. (1991). Template analysis for a chaotic NMR laser. Physical Review A, 44(8), R4786.
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