Approximate and analytic flow models for leak detection and identification

The article presents a comprehensive quantitative comparison of four analytical models that, in different ways, describe the flow process in transmission pipelines necessary in the task of detecting and isolating leaks. First, the analyzed models are briefly presented. Then, a novel model comparison framework is introduced along with a methodology for generating data and assessing diagnostic effectiveness. The study presents basic assumptions, experimental conditions and scenarios considered. Finally, the quality of the model-based diagnostic estimators is assessed, focusing on their bias, standard deviation, and computational complexity. Here, several optimality criteria are used as detailed indicators of the quality and performance of the estimators in a multi-criteria Pareto optimality assessment.