Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study...

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Several factors must be considered in model evaluation, including accuracy, training data requirements, calibration effort, generality, and computational requirements. All modeling...