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Rotating Equipment Defect Detection Using the Algorithm of Mode Isolation

Findings from a project involving rotating equipment defect detection using the Algorithm
of Mode Isolation (AMI) are presented. The prototypical system evaluated is a
rotating shaft, supported by hydrodynamic bearings at both ends, with one disk mounted
to the shaft. Shaft cracks and bearing wear are the two equipment defects considered.
An existing model of the prototypical system from the literature, termed the simplified
model. is modified to simulate the presence of a transverse shaft crack at mid-span. This
modified model is termed the standard model. Ritz series analysis, in conjunction with a
previously published description of the compliance related to the presence of a transverse
shaft crack, is used to describe the decrease in shaft stiffness associated with the crack.

The directional frequency response function (dFRF) is shown in the literature to provide
benefits over the standard frequency response function (FRF) in both system identification
and shaft crack detection for rotating equipment. The existing version of AMI is modified
to process dFRFs and termed Two-Sided AMI. The performance of Two-Sided AMI is
verified through system identification work using both the simplified model and a rigid
rotor model from the literature. The results confirm the benefits of using the dFRF for
system identification of isotropic systems. AMI and Two-Sided AMI are experimental modal
analysis (EMA) routines, which estimate modal properties based on a frequency domain
expression of system response. Eigenvalues and associated modal residues are the modal
properties considered in the present work.

Three defect detection studies are fully described. In the first, the simplified model is
used to investigate bearing wear detection. Various damage metrics related to the eigenvalue
and the residue are evaluated. The results show that residue-based metrics are sensitive
to bearing wear. Next, the standard model is used in an in-depth investigation of shaft
crack detection. When a shaft crack is present, the standard model is time-varying in both
the fixed and moving coordinate systems. Therefore, this analysis is also used to evaluate
performing EMA on non-modal data. In addition to continuing the evaluation of various
xiv damage metrics, the shaft crack study also investigates the effects of noise and coordinate
system choice (fixed or moving) on shaft crack detection. Crack detection through EMA
processing of noisy, non-modal data is found to be feasible. The eigenvalue-based damage
metrics show promise. Finally, the standard model is used in a dual-defect study. The
system is configured with both a shaft crack and a worn bearing. One defect is held
constant while the magnitude of the other is increased. The results suggest that AMI is
usable for defect detection of rotating machinery in the presence of multiple system defects,
even though the response data is not that of a time-invariant system. The relative merits
of both input data types, the FRF and the dFRF, are evaluated in each study.
Date03 May 2007
CreatorsWagner, Benjamin
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Detected LanguageEnglish

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