A method based on VMD improved by SSA for leak location of water distribution

Leak location using cross-correlation of acoustic signals collected by acceleration sensors is easily disturbed by the environmental noises resulting in inaccurate identification of its location, especially at low SNR. Aiming at this problem, an adaptive signal denoising algorithm based on squirrel search algorithm referred to as improved variational mode decomposition (SSA-VMD) is proposed to improve the accuracy of leak location. First, a fitness function based on the ratio of the envelope entropy to the kurtosis of the power spectrum of intrinsic mode functions (IMF) is established. Second, the leak signal is decomposed into IMFs using VMD with optimized parameters searched using the squirrel search algorithm. Then, a new method combining kurtosis analysis with crest factor and impulse factor is applied to select effective IMF components to reconstruct the leak signal at low SNR effectively. Finally, location search based on cross-correlation is performed using the reconstructed signal. Simulation and experiments results show that the proposed method can effectively suppress noise and reduce the error of leak location. The average relative leak location error of this method is within 2%, which proves the feasibility and effectiveness of the proposed adaptive signal noise reduction method.