Sherif Noah - US grants

This focuses on the development of procedures which integrate modern dynamical systems theory and analytical/numerical techniques to characterize the dynamical behavior of systems with strong local nonlinearities. The emphasis will be placed on nonlinearly coupled rotor/structural systems such as high speed aircraft engines. Strong local nonlinearities in rotor systems are manifested in dampers, clearances, fluid interactions, rubs, and others. The systems may be subjected to single or multi frequency excitation due to rotating imbalance in single, or multiple shaft and/or geared systems, respectively. General procedures will be developed for determining the system's multiple, periodic and quasi-periodic responses, their detailed bifurcations and routes to chaos. Low order rotor models will be constructed to study the nonlinear mechanisms by which the regular and chaotic behavior of the systems influence their performance. Of particular interest is the effect of internal resonances on that behavior. The research will yield reliable methods and procedures which will contribute to the fundamental understanding of nonlinear phenomena in systems with strong nonlinearities. The methods will be generalized to efficiently treat large order rotor systems to aid in their simulation, design, testing and monitoring; and for future developments in experimental and analytical studies.*** //

9504321 Noah Modeling, analysis and characterization of the dynamic behavior of multi-degree of freedom rotor systems with strong nonlinearities is the thrust of this research project. Analytical models of rotors and their nonlinear supports and coupling components are developed. Local nonlinearities in rotor systems are manifested in dampers, clearances and fluid interactions. Linearized analysis of industrial rotating machinery does not capture its full dynamics, and designs based upon such analyses may lead to severe malfunctions or catastrophic failures. In this project analytical/computational methods are developed for determining the nonlinear dynamic behavior of systems, including their periodic, quasi-periodic and chaotic response and bifurcation. These include the harmonic balance method, fixed point method, and their combinations. The results of this research advance the state of knowledge of nonlinear rotordynamics and leads to the development of reliable design techniques to mitigate the effects of nonlinear dynamics and chaos.***

Abstract

PIs: Sherif Noah, Alexander G. Parlos, Suhada Jayasuriya, Texas A&M University, Department of Mechanical Engineering, College Station, Texas 77843

Proposal Number: 0100238

Proposal Title: Smart Rotating Machinery

Project Abstract:

This exploratory research project addresses the development of smart rotating machinery. Unplanned machinery downtime and poor machinery performance impact negatively both industrial productivity and safety at an annual level of $1 trillion. It is therefore timely to develop smart rotating machinery that are highly adaptive to uncertain dynamic environments while maintaining high level of performance. Such machinery must incorporate new and innovative breakthroughs rooted in new information technologies that enable them to exhibit memory, learn from experience and use this learning ability to improve their adaptability while performing in an optimal manner.

The technical approach of the proposed research relies on health monitoring, condition assessment and early fault diagnosis through a combination of physics-based nonlinear rotordynamics models and empirical models developed through real-time sensor data. Closed-loop early incipient fault diagnosis is achieved through the use of computational intelligence tools, e.g. neural networks, fuzzy logic, and genetic algorithms, and other advanced signal processing methods, such as wavelet analysis. Towards making smart rotating machinery a reality, an initial framework will be explored for a methodology that will enable embedding certain elements of intelligent behavior into rotating machinery. The proposed limited effort is considered high-risk because it constitutes a pioneering study in smart systems with the perceived difficulties in developing an effective methodology. Furthermore, this research will lead to the experimental demonstrations of early diagnosis algorithms for controlled rotating machinery, a subject that has yet to be addressed in the literature. Such algorithms will control and mitigate impending failures of critical rotating machinery, reducing the probability of unplanned downtime, emergency shutdowns and catastrophic accidents.