The moving vibration source perception using bionic lateral line system and data-driven method

Abstract

In recent years, the application scope of artificial lateral line sensor (ALLS) systems is mainly limited to the perception of water flow environment and dipole source. In order to expand the application scope, an ALLS based on a pressure sensor array is proposed in this work to recognize the shape and size parameters of moving vibration sources. First of all, the pressure sensor array is appropriately installed in the underwater vehicle with the help of sensor topology optimization. Then, a numerical simulation model of the ALLS is established and its validation is verified by experimental tests. Subsequently, the information of the moving vibration sources with different parameters is collected by the simulations and experiments to generate training data sets. Lastly, two typical data-driven methods (i.e., the random forest algorithm and support vector machine) are trained to identify the shape and size parameters of the moving vibration sources. The analysis results demonstrate that the developed ALLS is effective in vibration source perception, which enhances the function of underwater vehicles.