Abstract An enthalpy–entropy ( h – s ) graph approach for the classification of faults in a new generation type high temperature gas-cooled reactor (HTGR) is presented. The study is performed on a 165 MW model of the main power system (MPS) of the pebble bed modular reactor (PBMR) that is based on a single closed-loop Brayton thermodynamic cycle. In general, the h – s graph is a useful tool in order to understand and characterize a thermodynamic process. It follows that it could be used to classify system malfunctions from fault patterns (signatures) based on a comparison between actual plant graphs and reference graphs. It is demonstrated that by applying the h – s graph approach, different fault signatures are derived for the examined fault conditions. The fault conditions that are considered for the MPS are categorized in three fault classes and comprise the main flow bypass of the working fluid, an increase in main flow resistance, and a decrease in component effectiveness or efficiency. The proposed approach is specifically illustrated for four single and two multiple fault conditions during normal power operation of the plant. The simulation of the faults suggests that it is possible to classify all of the examined system malfunctions correctly with the h – s graph approach, using only single reference fault signatures.
[1]
B. W. Botha,et al.
Sensitivity Analysis of the PBMR Gas Cooled Nuclear Reactor Cycle with the Aid of a Simplified Simulation Model
,
2000
.
[2]
Johannes Prock.
On-Line Detection and Diagnosis of Sensor and Process Faults in Nuclear Power Plants
,
2000
.
[3]
Jaques Reifman,et al.
Survey of Artificial Intelligence Methods for Detection and Identification of Component Faults in Nuclear Power Plants
,
1997
.
[4]
Paul M. Frank,et al.
Issues of Fault Diagnosis for Dynamic Systems
,
2010,
Springer London.
[5]
Rolf Isermann,et al.
Integration of Fault Detection and Diagnosis Methods
,
1994
.
[6]
Henry Cohen,et al.
Gas turbine theory
,
1973
.
[7]
Janos Gertler,et al.
Fault detection and diagnosis in engineering systems
,
1998
.
[8]
Irving H. Shames.
Mechanics of Fluids
,
1962
.
[9]
Du Rand,et al.
Health monitoring of a Brayton cycle-based power conversion unit
,
2007
.