An Improved Signal Peak Extraction Algorithm for RFID Pipeline Surface Defect Detection

The reliable inspection of aging oil and gas pipelines is essential for preventing accidents and ensuring operational safety, yet the accuracy of RFID-based detection systems is often limited by noise-sensitive peak detection algorithms, motivating the need for more robust signal processing approaches. In this study, an improved Discrete Wavelet Transform (DWT)-based method is proposed, employing db6/db8 wavelets for signal denoising and reconstruction, followed by peak localization using derivative zero-crossing to enhance detection precision. Experimental validation was conducted through both simulations and physical tests, where the proposed method achieved zero false and missed detections in simulation environments and reduced relative error by 30–50% compared to conventional algorithms in practical scenarios. These results demonstrate that the proposed approach significantly improves detection reliability and accuracy. Overall, the method provides an effective and cost-efficient solution for pipeline surface defect inspection, offering strong potential for application in real-world industrial monitoring systems.