Practical applications of singular value decomposition in rotordynamics

Abstract

Singular value decomposition (SVD) is used extensively in the controls community to examine the dynamic behavior of systems. SVD is one component of linear systems theory that has developed into a very mature mathematical tool for assessing systems. One objective of this paper is to illustrate the manner in which that large base of analysis can be brought to bear on both classical and emerging rotordynamics problems. This paper reviews the mathematical fundamentals of SVD and addresses its physical implications with respect to rotordynamics. To illustrate these physical concepts, simple rotor systems are examined in terms of forced response and stability margin characteristics. Additional examples are presented in which SVD is applied to more complex rotor systems for balancing, model reconciliation, and model reduction objectives.

Keywords:

• Rotordynamics
• singular value decomposition
• blancing
• model reduction
• model reconciliation
• stability margin

Additional information

Notes on contributors

C H Cloud

Hunter Cloud is Lab Engineer at the University of Virginia’s Rotating Machinery and Controls (ROMAC) Laboratories. After receiving a BSME from UVA, Mr Cloud worked 11 years with Mobil Research and Development Corporation in Princeton, NJ, as a turbomachinery specialist responsible for machinery application engineering, commissioning, start up and troubleshooting for Mobil’s worldwide production, refining and chemical facilities.

Currently, he is pursuing his doctorate where his research focuses on the measurement of turbomachinery stability characteristics.

G Li

Eric Maslen received his BSME from Cornell University in 1980 and his Doctorate in Mechanical and Aerospace Engineering from the University of Virginia in 1990. In between, he was a Research and Development engineer for Koppers Company, Inc. He joined the faculty of the University of Virginia in 1990 and was promoted to full professor in 2003. His research interests include magnetic bearings, rotordynamics, and identification.