An integrated approach to sensor FDI and signal reconstruction in HTGRs. Part I. Theoretical framework

Abstract Sensor fault detection and isolation (FDI) is an important element in modern nuclear power plant (NPP) diagnostic systems. In this respect, sensor FDI of generation II and III water-cooled nuclear energy systems has become an active research topic to continually improve levels of reliability, safety, and operation. However, evolutionary advances in reactor and component technology together with different energy conversion methodologies support the investigation of alternative approaches to sensor FDI. Within this context, the basic aim of this two part series is to propose, implement and evaluate an integrated approach for sensor FDI and signal reconstruction in generation IV nuclear high temperature gas-cooled reactors (HTGRs). In part I of this two part series, the methodology and theoretical background of the integrated sensor FDI and signal reconstruction approach are given. This approach combines techniques such as non-temporal parity space analysis (PSA), principal component analysis (PCA), sensor fusion and fuzzy decision systems to form a more powerful sensor FDI methodology that exploits the strengths of the individual techniques. An illustrative example of the PCA algorithm is given making use of actual data retrieved from a pilot plant called the pebble bed micro model (PBMM). This is a prototype gas turbine power plant based on the first design configuration of the pebble bed modular reactor (PBMR). In part II, the described integrated sensor fault detection approach will be evaluated by means of two case studies. In the first case study the approach will be evaluated on real PBMM data and in the second case study the approach will be evaluated on a highly detailed Flownex® model of the new generation PBMR.