Sound Signal Potential for Visualization of Corrosion in Pipelines

Abstract

This study explores the potential of using sound signals to visualize corrosion within pipes. Early detection of pipe damage is crucial in preventing leaks and larger losses, especially in industries that rely on pipes for fluid distribution. Sound-based methods have advantages in detecting damage in hard-to-reach areas without direct contact with the pipe's surface. This study demonstrates that microphones mounted on the pipe surface can capture variations in sound signal characteristics related to corrosion conditions. To simulate corrosion in pipes, a layer of plasticine was applied to a specific area of the pipe's inner surface, creating a model of corrosion damage. The test results show that microphone positions aligned with the corroded area produce higher signal coefficients compared to non-corroded areas. With further processing, these signal data have the potential to be visualized as 3D images, providing a more detailed representation of the internal conditions of the pipe.