Gene

Algorithm

Control (management)

Engineering

Materials science

Leak

Robustness (evolution)

Biochemistry

Particle swarm optimization

Computer science

Mathematical optimization

Mechanical engineering

Environmental engineering

Mathematics

Pipeline (software)

Leak detection

Artificial intelligence

Pipeline transport

Chemistry

Programming language

Control theory (sociology)

IEEE Transactions on Industrial Informatics

Based on inverse hydraulic-thermodynamic transient analyses and on an improved particle swarm optimization (PSO), a leak detection and localization method is proposed for liquid pipelines. The finite volume method is employed to numerically model the continuity, momentum, and energy equations. To determine the optimum-improved PSO algorithm and corresponding parameters, four types of algorithms were used for the analyses of a virtual pipeline. Accuracy, stability, robustness, and false alarm rate tests were conducted. The SIPSO algorithm has been shown to outperform the other algorithms. Two oil pipelines were utilized as example cases in conjunction with the use of the SIPSO algorithm. One of these pipelines was involved in a field opening experiment, while the other was involved in a real leak accident. The results demonstrated that smaller relative errors were achieved with the proposed method for the estimations of the location, coefficient, and starting time of the leak.

Improved PSO-based Method for Leak Detection and Localization in Liquid Pipelines