## 3 Verification of the Clustering Algorithm on RC Prisms  
### Experimental Setup of the RC Prisms  
An experimental test program was executed to gather AE data during the corrosion process of RC prisms. The experimental setup with 1D AE monitoring has been presented in [PERSON] et al. [5]. Most important specifications are summarized here for completeness.  
Three corrosion levels (CL) were targeted (1%, 5%, and 10% mass loss) and two rebar types were investigated (ribbed and smooth). Of each type, one sample was made, resulting in six samples. The sample name is based on the corrosion level and rebar type, e.g., CL2-R refers to a sample of the second corrosion level (5% mass loss) having a ribbed rebar. The six RC prisms with dimensions 150 \(\times\) 150 \(\times\) 250 mm\({}^{3}\) were monitored with a 1D AE sensor setup, using 2 AE sensors per RC sample. The rebars were placed in the center of the sample. A length of 100 mm was bonded to the concrete and was able to corrode. Corrosion was induced with a direct current having a current density of 100 \(\upmu\)A/cm\({}^{2}\). The rebar functioned as the anode, whereas a stainless steel plate functioned as the cathode. The samples were partially immersed in a 5% sodium chloride solution. Surface crack measurements were performed once a week with a crack meter having an accuracy of 0.05 mm, using nine measurement points with a spacing of 25 mm. AE monitoring was performed continuously, and only interrupted briefly during the crack measurements.  
An AMSY-6 Vallen acquisition system (ASIP-2, advanced version) with six channels was used, allowing monitoring up to three samples at the same time. Broadband piezoelectric sensors with a flat frequency response between 100 and 400 kHz (type AE104A, Fuji Ceramics Corporation) were attached on the specimen surface with hot melt glue (Pattex PTK1). AE sensors with a flat frequency response were preferred as the frequency of interest of the damage sources was unknown and a signal-based analysis was desired. This type of sensor is used as an alternative to the 150 kHz resonance sensor (operating range between 100 and 450 kHz) which is frequently used for damage detection in small-to-medium sized RC samples [12; 16; 30]. The amplitude threshold, the pre-trigger time, duration discrimination time, and rearm time were set to 40 dB, 20 \(\upmu\)s, 400 \(\upmu\)s, and 0.4 ms, respectively. The sampling rate was set to 10 MHz. With 2048 samples being stored, the length of the stored signal was 204.8 \(\upmu\)s. The digital frequency filter was set between 95 and 850 kHz. This filter was chosen based on the operating frequency range of the sensors which is between 100 and 400 kHz. The accelerated corrosion setup and position of the AE sensors are shown in Figure 2.  
As the clustering algorithm is computationally demanding, it will be applied on filtered AE signals. The AE signals are filtered according to a developed filtering protocol as presented in Van Steen and Verstrynge [28]. The threshold-based arrival time is improved by applying the Akaike Information Criterion (AIC). Two criteria were applied to filter the most reliable AE signals. The first criterion is based on the signal-to-noise ratio (SNR), which should be higher than 10. The second criterion evaluates whether the time of arrival (TOA) was accurately picked by AIC, based on the shape of the AIC-value graph. If the slope between the first low point and the global minimum of the AIC graph was higher than \(-25\ \frac{1}{\upmu\mathrm{s}}\), the estimation with the AIC picker was not found to be accurate. Afterwards,  
Figure 1: Working principle of the hierarchical clustering algorithm.  
the AE signals were localized in 1D and only the first arriving hit of located events are used for the clustering.