Modified particle swarm algorithm for locating leakage source on natural gas pipeline in obstructed space

In order to guide the search robots to locate quickly and accurately the leakage source on natural gas pipeline in the complex obstructed space, a Modified Guaranteed Convergence Particle Swarm Optimization (MGCPSO) algorithm integrating the guaranteed convergence particle swarm optimization and the artificial potential field was proposed based on their respective advantages in collaborative search and obstacle avoidance. Specifically, a leakage diffusion field was created to simulate the two-dimensional leakage concentration field considering obstacles, the locating capability of MGCPSO was tested, and the influence of measuring error and robot number on the locating capability was analyzed. The results indicate that the MGCPSO algorithm can locate the single leakage source in the space with circular obstacle, and the increase of measuring error can lead to the increasing in location deviation of the leakage source predicted by the algorithm. The locating result of the algorithm is accurate when the standard deviation of measuring error is less than 0.1. In addition, increasing the robot number can improve the prediction accuracy of the algorithm. Generally, the MGCPSO algorithm could guide the robots to avoid the obstacles during the searching of leakage source and provide data support for the field emergency rescue. The locating accuracy of the algorithm under small population conditions should be further studied in the future.