Pacific Northwest National Laboratory (PNNL) scientists are performing research under the Department of Energy Nuclear Energy Research Initiative (NERI) program, to develop a methodology for accurate identification and prediction of equipment faults in critical machinery. The 3-year project, on-line intelligent self-diagnostic monitoring system (SDMS) for next generation nuclear power plants is scheduled for completion at the end of FY 2002. The research involves running machinery to failure in the Laboratory by the introduction of intentional faults. During testing, advanced diagnostic/prognostic sensors and analysis systems monitor the equipment stressor levels, correlate them with expected degradation rates, and predict the resulting machinery performance levels and residual lifetime. Application of a first principles physics-based approach is expected to produce prognostic methodologies of significantly higher accuracies than are currently available. This paper reviews the evolution and current state of the maintenance art. It presents a key measurement philosophy that results from the use of condition based maintenance (CBM) as a fundamental investigative precept, and explains how this approach impacts degradation and failure measurement and prediction accuracy. It then examines how this measurement approach is applied in sensing and correlating pump stressors with regard to degradation rate and time to equipment failure. The specifics are examined on how this approach is being applied at PNNL to cavitation and vibration phenomena in a centrifugal pump. Preliminary vibration analysis results show an excellent correspondence between the (laser) motor position indication, the vibration response, and the dynamic force loading on the bearings. Orbital harmonic vibratory motion of the pump and motor appear to be readily correlated through the FFTs of all three sensing systems.

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