Abstract Identifying the spatial positions of acoustic emission (AE) sources in piping networks is essential for narrowing down degradation sites across pipe segments and weld joints. Traditional localization techniques often face limitations due to geometric complexity, wave dispersion, and signal detection issues resulting from incorrect time of arrival determination, sensor response differences, and variations in wave velocity. A regression-based mapping framework, in addition to conventional source localization, was introduced that leverages the geometric connectivity of the piping system to relate AE signal features to source-to-sensor distances and enable additional localization across multiple pipe segments and welds. The quadratic relationship between source-to-sensor distance and the amplitude-to-time-of-arrival ratio is demonstrated from the combined effects of geometric spreading and exponential material attenuation, which produce a nonlinear dependence well approximated by a second-order polynomial. The developed method is particularly effective when conventional linear localization or triangulation fails, such as when the AE source lies outside the sensor array. The approach was tested using the scaled advanced reactor vessel at the Mechanisms Engineering Test Loop (METL) facility at Argonne National Laboratory. Wave propagation behavior and acoustic connectivity were investigated experimentally and through numerical modeling. A finite element model was developed to simulate signal attenuation and time-of-arrival variations across different sensor configurations and was validated using pencil lead break tests. Across three representative pipe segments, the quadratic regression achieved with R^2 R 2 values of 0. 73–0. 78, corresponding to localization errors less than 20% if the geometric mapping covers the source position in the regression model.
Xu et al. (Sun,) studied this question.