Leak Detection and Calibration Using Transients and Genetic Algorithms

TLDR

Leak detection and calibration of pipe roughness in water distribution networks is critical, and computer simulation using the inverse transient technique is emerging as a key tool despite uncertainties about pipe interiors. The study applies a genetic algorithm combined with the inverse transient method to detect leaks and estimate friction factors in water distribution systems. The authors developed a continuous‑variable GA coding scheme and introduced novel crossover and mutation operators. The GA‑based inverse transient method accurately identifies leak locations and sizes while simultaneously estimating friction factors across varying transient data record lengths.

Abstract

Leak detection and calibration of pipe internal roughnesses in a water distribution network are significant issues for water authorities around the world. Computer simulation of water distribution systems to determine the location and size of leaks is emerging as an important tool. A major uncertainty in developing computer models is the condition of the interior of the pipes in the network, especially if they are old. An innovative technique for leak detection and calibration called the inverse transient technique has been recently developed. This paper uses the genetic algorithm (GA) technique in conjunction with the inverse transient method to detect leaks and friction factors in water distribution systems. A continuous variable representation has been developed for the GA coding scheme in this paper. Two new GA operators for crossover and mutation are also introduced. The inverse transient method using the GA technique is effective at finding leakage locations and magnitudes while simultaneously finding the friction factors for different transient data record lengths.