Vibration monitoring with artificial neural networks

Conference · Tue Jan 01 04:00:00 EST 1991

OSTI ID:6926346

Alguindigue, I. ^[1]; Uhrig, R. E. ^[2]

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1. Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering
2. Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering Oak Ridge National Lab., TN (United States)

Vibration monitoring of components in nuclear power plants has been used for a number of years. This technique involves the analysis of vibration data coming from vital components of the plant to detect features which reflect the operational state of machinery. The analysis leads to the identification of potential failures and their causes, and makes it possible to perform efficient preventive maintenance. Earlydetection is important because it can decrease the probability of catastrophic failures, reduce forced outgage, maximize utilization of available assets, increase the life of the plant, and reduce maintenance costs. This paper documents our work on the design of a vibration monitoring methodology based on neural network technology. This technology provides an attractive complement to traditional vibration analysis because of the potential of neural network to operate in real-time mode and to handle data which may be distorted or noisy. Our efforts have been concentrated on the analysis and classification of vibration signatures collected from operating machinery. Two neural networks algorithms were used in our project: the Recirculation algorithm for data compression and the Backpropagation algorithm to perform the actual classification of the patterns. Although this project is in the early stages of development it indicates that neural networks may provide a viable methodology for monitoring and diagnostics of vibrating components. Our results to date are very encouraging.

• Research Organization: Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: FG07-88ER12824; AC05-84OR21400
• OSTI ID: 6926346
• Report Number(s): CONF-910535--6; ON: DE93003543
• Country of Publication: United States
• Language: English

Related Subjects

22 GENERAL STUDIES OF NUCLEAR REACTORS
220400 -- Nuclear Reactor Technology-- Control Systems
220900* -- Nuclear Reactor Technology-- Reactor Safety
99 GENERAL AND MISCELLANEOUS
990200 -- Mathematics & Computers
ALGORITHMS
MATHEMATICAL LOGIC
MECHANICAL VIBRATIONS
NEURAL NETWORKS
NUCLEAR FACILITIES
NUCLEAR POWER PLANTS
POWER PLANTS
REACTOR MONITORING SYSTEMS
REACTOR NOISE
REACTOR SAFETY
SAFETY
SYSTEM FAILURE ANALYSIS
SYSTEMS ANALYSIS
THERMAL POWER PLANTS