Degradation and Fault Detection of Rotordynamic Machinery Using Real-Time Experimental Modal Analysis

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

This research study aims to develop an in-line real-time diagnostic capability for turbomachinery combining rotordynamics, fracture mechanics, and tribology to predict when equipment should be taken out of service. The concept is to use system condition metrics derived from the application of experimental modal analysis to operational response data. The research will begin with data derived from an analytical model of a rotor-shaft system having moderate sized fatigue cracks, bearing wear, and lubricant deterioration and starvation in any combination. Synthetic response measurements matching current technology for rotordynamic systems will be derived from the model, and processed by a technique for experimental modal analysis to accurately indicate the condition of the system single or multiple faults and their criticality. The signal-to-noise ratios required to implement concepts as in-line diagnostics for operational systems will be identified. Viable concepts will be subjected to a preliminary experimental validation using the onsite rotordynamics laboratory. Turbomachinery is important to many aspects of our society, especially for power generation, water supply systems, aviation and naval systems. Avoidance of catastrophic failure is presently performed primarily on a scheduled basis. Development of a technique that identifies when systems actually require maintenance, thereby avoiding unnecessary shutdowns, would have tremendous economic impact, because it would reduce the frequency with which expensive inspection procedures are performed, as well as lessen requirements for excess capacity. This study focuses on the presence of cracks in the shaft and impending bearing and lubrication failure. It would use current technology for response measurement, so it would not require major alterations to existing systems. Further development would make it implementable as an in-line diagnostic and prognostic tool, which could be employed in parallel with other in-line diagnostic techniques.