Burst Localisation in Water Pressurised Pipelines Combining Numerical Data Generation and ANN Transient Signal Processing

Transient test-based techniques have been widely identified as one of the best non-intrusive techniques that exploit the propagation of pressure waves along pressurised pipelines, allowing the check of the status of the distribution systems. Although several studies have demonstrated the suitability of this technique for identifying anomalies in transmission pipelines, including leaks, the potential for automatically analysing transient signals through deep learning procedures has only been superficially investigated. With this aim, this study proposes how a proper synthetic generation of transient signals based on numerical simulations can support the development of neural network-based methodologies for water leak detection and localisation.