Can Cavitation Be Anticipated? [electronic resource].
- Washington, D.C. : United States. Dept. of Energy. Office of Energy Research, 1999.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- 12 pages : digital, PDF file
- Additional Creators:
- Oak Ridge National Laboratory
United States. Department of Energy. Office of Energy Research
United States. Department of Energy. Office of Scientific and Technical Information
- The major problem with cavitation in pumps and hydraulic systems is that there is no effective (conventional) method for detecting or predicting its inception. The traditional method of recognizing cavitation in a pump is to declare the event occurring when the total head drops by some arbitrary value (typically 3%) in response to a pressure reduction at the pump inlet. However, the device is already seriously cavitating when this happens. What is actually needed is a practical method to detect impending rather than incipient cavitation. Whereas the detection of incipient cavitation requires the detection of features just after cavitation starts, the anticipation of cavitation requires the detection and identification of precursor features just before it begins. Two recent advances that make this detection possible. The first is acoustic sensors with a bandwidth of 1 MHz and a dynamic range of 80 dB that preserve the fine details of the features when subjected to coarse vibrations. The second is the application of Bayesian parameter estimation which makes it possible to separate weak signals, such as those present in cavitation precursors, from strong signals, such as pump vibration. Bayesian parameter estimation derives a model based on cavitation hydrodynamics and produces a figure of merit of how well it fits the acquired data. Applying this model to an anticipatory engine should lead to a reliable method of anticipating cavitation before it occurs. This paper reports the findings of precursor features using high-performance sensors and Bayesian analysis of weak acoustic emissions in the 100-1000kHz band from an experimental flow loop.
- Published through SciTech Connect.
8th American Nuclear Society Topical Meeting on Robotics and Remote Systems, Pittsburgh, PA (US), 04/25/1999--04/29/1999.
Hylton, J.O.; Allgood, G.O.; Dress, W.B.; Kercel, S.W.
- Funding Information:
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