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Wednesday, May 15 • 8:30am - 9:00am
Selection of Thermal Isolator for a Propylene Transfer Pump – A Case Study

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The diagnosis of rotating and reciprocating machinery has been an area of active research_x000D_
for several decades, for both commercial and military equipment. Most researchers are_x000D_
knowledgeable concerning instrumentation and signal analysis algorithms, but not as_x000D_
experienced with the 'physiology' of various machinery, the details and dynamical behavior of _x000D_
which can be quite complex. Therefore, the tendency has been to use either simple rule-based_x000D_
look-up tables, or in the other extreme ti apply adaptive learning, neural nets, or other_x000D_
data-driven statistics-based approaches that look for anomalies in a manner that attempts_x000D_
to be machine-agnostic. These approaches can be useful in some applications. However, the_x000D_
authors suggest that a superior approach is the use of physics-based set of algorithms that_x000D_
are based on the mechanical and fluid-dynamic (or electrical for motors/generators) details_x000D_
of the machinery in question. Some examples are provided of such algorithms that have_x000D_
application over broad classes of machinery. It is demonstrated how such as approach can_x000D_
be blended with ISO standards based constraints and guidelines to provide software_x000D_
that can mimic much of what an experienced machinery engineer or technician would_x000D_
conclude from a given data set. Examples of machinery successfully diagnosed by the_x000D_
approach will be given.



Manager Mechanical - Rotating Equipment, PETROFAC INTL. LTD

Wednesday May 15, 2019 8:30am - 9:00am EDT
Freedom Ballroom II