Acoustic Emission Localization in Steel Pipes Through Entropy-information Analysis

The present study aims to introduce an innovative entropy-based denoising technique to enhance the accuracy of TDoA (Time Difference of Arrival) in source localization techniques based on acoustic emissions (AE). The approach focuses on the challenging scenario of industrial pipelines in energy and transportation systems characterized by high level of noise. Conventional methods for estimating the TDoA of AE sources, are generally hindered by external interferences in near-industrial scenarios, leading to distorted AE signals. The proposed approach encompasses a comprehensive analysis of signal waveforms, integrating local entropy to effectively compensate for the presents of noise, and employing the Akaike Information Criterion (AIC) to estimate the TDoA. To evaluate the performance of the proposed method, a two-stage experimental campaign was conducted on a pressurized hydraulic circuit. The first stage involved verifying the statistical reliability of the proposed algorithm by employing the Hsu-Nielsen test (pencil lead break) at multiple points along a series of pipes. In the second stage, an ad-hoc system was devised to induce accelerated corrosion on the same piping while capturing raw acoustic emission waveforms. Various levels of Gaussian noise, reflecting distinct signal-to-noise ratios, were added to the recorded raw waveforms to simulate diverse industrial interference scenarios. The findings illustrate significant enhancement in the accuracy and repeatability of AE source localization. The proposed entropy-based denoising technique showcases substantial potential for advancing damage detection and localization within the Process & Power Industry.