## 1 Introduction
Second, as the signal is caused by the fracture process itself, an early detection of ongoing damage processes is possible. Third, it allows the characterization of the damage process as the characteristics of the AE signal are source-dependent. Fourth, the damage source can be localized based on the arrival time observed at different sensors. AE-based detection and characterization of corrosion damage in RC have been widely studied. AE monitoring has been performed during the corrosion process as well as during mechanical testing of corroted RC components. Both parameter-based analysis as signal-based analysis have been discussed. Several researchers reported that the corrosion process can be divided in different stages based on the cumulative amount of AE events [13; 14; 15; 16] and cumulative amount of AE energy [13; 17]. These stages can be related to the onset of corrosion and nucleation of corrosion cracks. The parameters rise angle (RA), and average frequency (AF) are applied to determine the crack type (tensile and shear cracks). [PERSON] and [PERSON] [15] reported high RA values and low AF at the beginning of the test representing shear cracking. Later, RA values decreased, and AF increased meaning that tensile cracking has initiated. However, crack width measurements were not reported. [PERSON] et al. [14] on the other hand, reported an increase of the RA value and a decrease of the AF when cracking was observed. Alternative to the parameter-based RA-AF analysis described before, a difference in crack type can also be obtained by a moment tensor analysis [14; 18; 19]. Only a few studies have been performed regarding the characterization of AE sources during the corrosion process [20; 21]. A recent study by [PERSON] et al. [22] reported a decrease of the peak and center frequency at the onset of concrete macro-cracking. AE sources, such as corrosion and concrete cracking, could be distinguished after analysis of the wavelet transforms of the AE signals. Source localization of corrosion damage in RC remains challenging and is therefore less discussed in the literature. Proper localization is difficult as the P-wave velocity in steel is around 1.5 times the velocity in the concrete matrix. The wave can also be attenuated and reflected differently by both materials. Additionally, cracks have an important influence on the result [23]. The accuracy of the localization result depends on several parameters: the sensor layout, the accuracy of the arrival time picking, the velocity model, and the propagation path of the wave. Several localization algorithms are available in the literature [24; 25]. Most algorithms assume a homogeneous velocity and a straight propagation path. More complex algorithms allowing more realistic velocity models and propagation paths are still computationally very demanding. For a recent study on localization algorithms based on heterogeneous velocity models and fastest propagation paths, the reader is referred to [PERSON] et al. [26]. A drawback of these algorithms is that the gain in accuracy does not always outweigh the computational cost. The aim of this paper is to localize internal damage in RC during the corrosion process with the AE technique. The localization result was improved by the development of a post-processing protocol, allowing the performance of dedicated filtering of the AE events. The protocol is applied and validated on an extensive set of experimental data. To investigate the applicability of the developed post-processing protocol towards on-site application, the methodology is scaled up using three sample scales: small mortar samples (scale 1), RC prisms (scale 2), and RC beams (scale 3).