Ph.D. Proposal Presentation by Benjamin B. Wagner
Tuesday, April 13, 2004
( Dr. J. H. Ginsberg, Chair)
"Rotating Equipment Defect Detection Using the Algorithm of Mode Isolation "
The proposed work will apply the Algorithm of Mode Isolation (AMI) to the task of defect detection in rotating equipment. AMI has been shown to provide accurate determination of modal parameters in low signal-to-noise applications. The prototypical system evaluated in this work will be a rotating shaft, supported by hydrodynamic bearings at both ends, with one disk mounted to the shaft at an arbitrary axial location. During the analytical evaluation, the mathematical model of the prototypical system will be modified to include bearing wear, shaft cracks, and lubricant viscosity changes. The output of the prototypical system mathematical model will be a time domain response signal analogous to a displacement, velocity, or acceleration signal taken from instrumentation on an actual machine. The Fast Fourier Transform (FFT) will be used to convert this time domain signal to the frequency domain so that it can be processed by AMI. The output of AMI will be system eigenvalues, which are related to natural frequencies and associated modal damping ratios. For constant-speed operation, the threshold of detectability of each type of defect acting alone will be determined by repeatedly decreasing the defect severity in the system model until AMI can no longer detect changes in natural frequencies or damping ratios. The process will be repeated with multiple defects present, and the effects of noise on the thresholds of detectability will be quantified in the same manner. Existing experimental data for a cracked, overhung rotating shaft will be evaluated in the same manner. Finally, the method will be extended to variable-speed operation. Many modal parameter identification techniques for rotating equipment currently exist. Most require either change in operating speed, low-noise vibration signals, or many more sensors than typically installed in operating equipment. The proposed work would be a significant advance because it would determine changes in system modal parameters, and thereby identify defects, using signals ordinarily taken in a high-noise environment by industry-standard instrumentation with the rotating equipment operating normally.