Abstract
This research introduces an inverse transient-based optimization approach to automatically detect potential faults, such as leaks, partial blockages, and distributed deteriorations, within pipelines or a water distribution network (WDN). The optimization approach is named the Pipeline Examination Ordinal Symbiotic Organism Search (PEOS). A modified steady hydraulic model considering the effects of pipe aging within a system is used to determine the steady nodal heads and piping flow rates. After applying a transient excitation, the transient behaviors in the system are analyzed using the method of characteristics (MOC). A preliminary screening mechanism is adopted to sift the initial organisms (solutions) to perform better to reduce most of the unnecessary calculations caused by incorrect solutions within the PEOS framework. Further, a symbiotic organism search (SOS) imitates symbiotic relationship strategies to move organisms toward the current optimal organism and eliminate the worst ones. Two experiments on leak and blockage detection in a single pipeline that have been presented in the literature were used to verify the applicability of the proposed approach. Two hypothetical WDNs, including a small-scale and large-scale system, were considered to validate the efficiency, accuracy, and robustness of the proposed approach. The simulation results indicated that the proposed approach obtained more reliable and efficient optimal results than other algorithms did. We believe the proposed fault detection approach is a promising technique in detecting faults in field applications.
Highlights
The steady-state hydraulics of pipe network B were predicted by pipe network symbiotic organism search (PNSOS) in 309 s, and the transient event was generated by closing the valve at N17
It is noteworthy that leak L2 at node N22 was isolated by the proposed approach, indicating that Pipeline Examination Ordinal Symbiotic Organism Search (PEOS) was capable of handling the case of pipe junction leakage
The application of PEOS was verified by two experimental reservoir pipe valve (RPV) systems in the literature, and PEOS was further applied to identify fault information in synthetic pipe networks
Summary
Water distribution networks (WDNs) in modern cities are usually large-scale, with complex systems and limited instrumentation. The faults in a pipeline or a WDN may be divided into three types: Leak, blockage, and deterioration, which may induce various problems. Water supply networks leak an average of 20% of their water supply and lose an estimated U.S $9.6 billion each year [3]. This may affect environmental health and safety [4,5,6] and create water quality problems, such as equipment failure, problematic operations management, and errors in pipeline design [4,7,8,9]. Fault detection in WDNs is an important task in the community of water supply engineers
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