On-Line Monitoring of Accuracy and Reliability of Instrumentation and Health of Nuclear Power Plants

Period of Performance: 01/01/2006 - 12/31/2006


Phase 1 SBIR

Recipient Firm

Analysis And Measurement Services Corporation
9119 Cross Park Drive
Knoxville, TN 37923
Principal Investigator
Firm POC


The nuclear power industry continues to depend largely on antiquated methods and hands-on maintenance for its instrumentation, for plant-aging management, and health monitoring. This project will develop on-line monitoring technology that will help establish the accuracy and reliability of nuclear power plant instrumentation and also will help in the management of aging critical plant equipment. Advanced data acquisition and data analysis techniques, which can readily meet the needs of the nuclear industry for automated maintenance and plant health management, will be identified, evaluated, and tested in Phase I. These techniques will include data qualification algorithms; steady-state data-analysis techniques, involving both physical and empirical modeling; and dynamic signal analysis, such as Fast Fourier Transfer (FFT) and Autoregressive Modeling (AR). The feasibility of an on-line monitoring system for nuclear power plants will be established. The analytical techniques will be integrated into a prototype system in Phase II. Commercial Applications and Other Benefits as described by the awardee: The technology should find use in conventional, advanced, and Gen IV reactors as well as in such non-nuclear industries as fossil fuel generation, chemical plants, and aerospace. The system would: (1) ensure the accuracy and reliability of process instrumentation; (2) characterize the overall health of a plant; (3) provide a means to guard against aging degradation that can impair safety; (4) provide timely information and data to plant operators, allowing accurate decision making for control and safety monitoring; and (5) establish the condition of critical plant equipment, needed to prioritize maintenance resources and optimize maintenance tasks.