Monitoring and fault diagnosis of the steam generator system of a nuclear power plant using data-driven modeling and residual space analysis

Support vector regression model based predictive control of water level of U-tube steam generators

“…Han (2000) developed a steam generator model as part of the overall plant. Lu and Upadhyaya (2005) used a residual space analysis based model primarily intended for fault detection. Marseguerra and Avogadri (2004) along with Rusinowski and Stanek (2007) implemented neuro-fuzzy and neural techniques, respectively.…”

Importance of auxiliary systems for process fault detection and diagnosis

“…Traditionally, FDD in plant utilities is focused on the condition of the equipments responsible for the utility generation and distribution, without studying the effects of the faults plant-wide [26][27]. Recently though, [28] acknowledged a malfunctioning utility as a cause for plantwide disturbances and estimated its economical effects.…”

Nuclear power plant components condition monitoring by probabilistic support vector machine

“…Artificial Neural Network (ANN), Support Vector Machine (SVM), Genetic Algorithm (GA) and Auto-Associative Kernel Regression (AAKR) are among some of the most studied and applied (Chevalier et al, 2009;Baraldi et al, 2010;Baradi et al, 2011;Santosh et al, 2009;Li et al, 2012;Yazikov et al, 2012;Rand et al, 2012a;Rand et al, 2012b;Muralidharan and Sugumaran, 2012;Ekici, 2012;Zio and Gola, 2006;Lu and Upadhyaya, 2005;Jeong et al, 2003;Zio et al, 2009). These approaches are already mature, especially for detection and diagnostics.…”