Autocorrelation-based Thickness Measurement for Enhancing Online Monitoring of Pipeline Health

The remaining thickness of pipes is one of the most critical factors in the operation of pipe systems. Recent advancements in wireless communication technology and the development of lightweight systems capable of measuring and processing ultrasonic signals have shifted pipe thickness measurement from periodic inspections to on-line monitoring. Operating pipeline systems generate considerable noise that does not need to be considered during preventive maintenance, so a noise -robust thickness estimation method is required. In particular, signal weakening due to corrosion progression further emphasizes the need for such a method. In this study, we investigated the possibility of thickness estimation in noisy situations using an autocorrelation function (ACF). We examined the signal characteristics of the ACF and compared the proposed method with existing methods in various signal-to-noise ratio (SNR) cases. To this end, we used pipe specimens corroded through an accelerated corrosion test. As a result of detecting the reflected signal for thickness estimation by applying Gaussian white noise, it was confirmed that a meaningful time delay of the reflected signal can be observed even when the SNR is -6 dB.