Abstract
AbstractCondition assessment of water pipelines using fluid transient waves is a noninvasive technique that has been investigated for the past 25 years. Approaches to identify different anomalies a...
Highlights
Water is a vital resource to society and its continuous distribution for all types of use is becoming a challenge, including time and spatial inequality in its availability, and the lack of responsible management and poorly maintained infrastructure
Transient-based methods have received special attention in the past two decades given that they allow the inspection of large sections of a pipe with a relatively simple set up (Gong et al 2013b), and results can be obtained quickly (Lee et al 2006; Shi et al 2017). These methods are based on the interpretation of the effect that any feature in a pipeline has on the transient head trace, when a small controlled artificial transient pressure event is generated
The present paper provides a background in transient-based methods for identifying topological elements and for locating leaks based on transient pressure traces, highlighting certain limitations of each method that can potentially be overcome with the use of artificial neural networks (ANNs)
Summary
Water is a vital resource to society and its continuous distribution for all types of use is becoming a challenge, including time and spatial inequality in its availability, and the lack of responsible management and poorly maintained infrastructure. Transient-based methods have received special attention in the past two decades given that they allow the inspection of large sections of a pipe with a relatively simple set up (Gong et al 2013b), and results can be obtained quickly (Lee et al 2006; Shi et al 2017) These methods are based on the interpretation of the effect that any feature in a pipeline has on the transient head trace, when a small controlled artificial transient pressure event is generated. The computational effort of the proposed technique is concentrated in the ANN training stage, but once this stage is complete, the technique can process and find leaks and/or topological features from different transient head traces almost immediately, without the need of retrain the ANN Considering that this is the first reported joint application of fluid transients and ANNs, the examples and the functioning of the technique are demonstrated only with numerically derived data. The proposed method is shown to be accurate and general for the considered systems; in addition to some concluding remarks, some challenges of the future application of this technique are briefly discussed
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