Monitoring, diagnosis and prediction of failures play key roles in automatic
supervision of machine tools. They have received much attention because of the
potential for reduced maintenance expenses, down time, and an increase in the
equipment utilization level. At present, signal analysis techniques are predominantly
used. But methods involving system analysis are capable of providing more reliable
information, especially for predictive applications of supervision. System analysis
involves comprehensive analytical models combined with techniques developed in
control theory, and experimental modal analysis.
The primary objective of this research is to develop a methodology to monitor
critical physical parameters of mechanical systems, which are difficult to measure
directly. These parameters are inherent features of constitutive rigid body models. A
method for computer aided model generation developed in this thesis leads to a gray
box model structure by which physical parameters can be estimated from experimental
data. Lagrange's energy formalism, linear algebra and homogenous transformations
are used to promote parsimonious three-dimensional model building. A software
environment allowing symbolic and arbitrary precision computations facilitates
efficient mapping of physical properties of the actual system into specific quantities of
the analytical model.
Six different methods are postulated and analyzed in this thesis to estimate
physical parameters such as masses, stiffnesses and damping coefficients.
Implementation of this methodology is a prerequisite for the design of an on-line
monitoring and diagnosis system, which can detect and predict process faults. Two
mechanical systems are used to validate the proposed methods: (1) A simple multi
degree-of-freedom (MDOF) system and (2) a machine tool spindle assembly.
A practical application of physical parameter estimation is proposed for
preload monitoring in high-speed spindles. Preload variations in the bearing can lead
to thermal instability and bearing seizure. The feasibility of using accelerometers
located on the spindle housing to estimate bearing preload is evaluated.
The optimal environment for continuation of this research is collaboration with
machine tool companies to incorporate the proposed methodology (or parts of it) into
current design practices. / Graduation date: 1999
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/33479 |
| Date | 28 April 1999 |
| Creators | Nickel, Thomas |
| Contributors | Spiewak, Swavik A. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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