| Summary: | The primary goal of any model is to emulate, as closely as possible, the desired
behavioral phenomena of the real system but still maintain some tangible qualities
between the parameters of the model and the system response. In keeping with this
directive, models by their very nature migrate towards increasing complexity and hence
quickly become tedious to construct and evaluate. In addition, it is sometimes necessary
to employ several different analysis techniques on a particular system, which often
requires modification of the model. As a result, the concept of versatile, step-wise
automated model generation was realized as a means of transferring some of the laborious
tasks of model derivation from the analyst to a suitable program algorithm. The focus of
this research is on the construction and verification of an efficient modeling environment
that captures the dynamic properties of the system and allows many different analysis
techniques to be conveniently implemented. This is accomplished through the
implementation of Mathematica by Wolfram Research, Inc..
The presented methodology utilizes rigid body, lumped parameter systems and
Lagrange's energy formalism. The modeling environment facilitates versatility by
allowing straightforward transformations of the model being developed to different forms
and domains. The final results are symbolic expressions derived from the equations of
motion. However, this approach is predicated upon the absence of significant low
frequency flexible vibration modes in the system. This requirement can be well satisfied
in the parallel structure machine tools, the main subject of this research.
The modeling environment allows a number of techniques for validation to be
readily implemented. This includes intuitive checks at key points during model derivation
as well as applications of more traditional experimental validation. In all presented cases
the analysis can be performed in the same software package that was used for model
development.
Integration of the generation, validation, and troubleshooting methodology
delineated in this research facilitates development of accurate models that can be applied
in structure design and exploitation. Possible applications of these models include
parameter identification, visualization of vibration, automated supervision and
monitoring, and design of advanced control strategies for minimization of dynamic tool
path errors. The benefits are especially prevalent in parallel structure machine tools,
where there is still a lack of experience. Latest developments in measurement techniques
and the emergence of new sensors facilitate reliable validation and optimization of the
models. === Graduation date: 1999
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