Masters Theses

Date of Award

12-1997

Degree Type

Thesis

Degree Name

Master of Science

Major

Nuclear Engineering

Major Professor

Belle R. Upadhyaya

Committee Members

J. W. Hines, L. F. Miller

Abstract

Nonintrusive diagnostic methods provide the identification of malfunctions in plant components during normal plant operations allowing the avoidance of catastrophic failures and the associated costs. The operability of a plant component driven by an electrical motor can be determined by analysis of measured electrical variables from the motor. The result of the current research is an expert system for the diagnosis of motor- operated valves (MOVs) in nuclear power plants through analysis of the motor power signature and an automated marking of the power signature for different valve types.

The PC-based fuzzy-expert system, PowerMOV, identifies events in the motor current, motor voltage, switch current and total real power (TRP) signatures from MOVS and uses these events to diagnose degradations identified by Nuclear Regulatory Commission (NRC) Generic Letter 89-10. The enhanced system, PowerMOV, was interfaced with Motor Power Monitor (MPM) which provides the data acquisition and power calculations. Field data used in this research were acquired from operating nuclear power stations. PowerMOV successfully detects events and identifies degradations for gate, globe and butterfly valves. A Microsoft Access 2.0 database was used to store all marked events and calculated input parameters for PowerMOV for all previous tests of each MOV including the baseline data. Data storage for a large number of MOVs was provided in the database. The information stored in the database include MOV operability parameters for use in the trending of MOV degradation.

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