Application of improved multi-strategy MPA-VMD in pipeline leakage detection

Abstract

This paper is concerned with the development of improved multi-strategy MPA-VMD method and its application in pipeline leakage detection. Aiming at the shortcomings of the marine predator algorithm (MPA) itself, which has a slow convergence speed and is easy to fall into local optimum, an improved MPA is proposed and used to find two important parameters in variational mode decomposition (VMD), and then dynamic entropy is used to select effective modes. In the initial stage of the population, a good point set strategy is adopted to enhance the search accuracy by increasing the diversity of the initial population; in the search process, a nonlinear convergence factor and the Cauchy distribution are introduced to optimize the predator step size to enhance the global search ability of the algorithm. The ability of the algorithm is enhanced to jump out of the local optimum, and the convergence speed of the algorithm is further improved; the effective mode after VMD is selected by the method of symbolic dynamic entropy. The experimental results show that compared with MPA-VMD, grey wolf optimization-VMD and particle swarm optimization-VMD methods, the devised method has improved signal-to-noise ratio, reduced mean square error and mean absolute error, and has better denoising effect.

Keywords

• Denoising
• variational modal decomposition algorithm
• marine predator algorithm
• Cauchy distribution
• good point set strategy