# Acoustic Emission-Based Method for IFSS Characterization in Single-Fiber Fragmentation Tests
This generates a series of breaks in the fiber until all fragment lengths are within a critical length, thus reaching the so-called saturation status. Conventionally, the number of fragments and the length of the breaks are measured using polarized optical microscopes. For IFSS quantification, a classical approach is to use the Kelly and Tyson equation [22], the main input parameter being the average fragment length. These are measured directly by optical microscopy [16; 23; 24] being the usual technique or indirectly through acoustic emissions (AE) [25]. The optical method for measuring fragment length requires neat surface treatment and is time-consuming, making it impractical for non-transparent matrices or high adhesion interfaces where the fiber fragments hundreds of times. To address this, acoustic emission techniques have been integrated into SFFT to detect breaks and indirectly calculate the average fragment length [26]. [PERSON] et al. [27] used a pair of AE sensors to detect and locate breaks within the SFFT of carbon fibers under different sizing conditions. In their investigation, the AE method generally presented a lower number of ruptures compared to the optical method. They attributed this loss of events to the energy dissipation caused by the damping of the epoxy matrix. Furthermore, they conclude that the AE method, considering the wave velocity and according to the level of matrix defects, performs well for the location of flaws within the specimen. On the other hand, the average fragment length is a key factor for the determination of IFSS. [PERSON] et al. [28] suggested that since fiber strength varies during testing, Weibull distributions should be used for fragment lengths. In acoustic emission techniques, burst detection is critical for accurate fracture identification. In burst detection methods, the threshold and its parameters are generally determined by trial and error, with the fixed threshold method being the most widely used due to its simplicity and low computational cost. However, this method has problems when the signal contains multiple high-amplitude bursts in a short period of time. This causes the signal's noise level to increase above the detection threshold, resulting in multiple bursts being interpreted as a single event, leading to a loss of information and possible interpretation errors [29; 30]. Therefore, in this work, the conventional fixed threshold method is not used. Instead, a burst detection method is developed based on the approach proposed by [PERSON] in [31], which describes a methodology to improve the detectability of AE bursts. In this study, burst detection is performed by simplifying the raw AE signal through a series of smoothing operations until a triangular envelope is obtained, where the appearance of the bursts is represented by a triangle in the envelope. From these triangles, the bursts present in the raw AE signal are identified and extracted separately. In AE applications, the fragment length cannot be measured directly, so the critical length used is the arithmetic mean estimated from the calibrated length and the number of AE events. In this research, the AE technique is used to obtain the IFSS in SFFTs. For this purpose, single fiber fragmentation specimens are fabricated, and the IFSS is determined using AE and optical microscopy for comparison. Burst detection is performed using the methodology presented by [PERSON] to improve accuracy. In addition, the mean length correction for the IFSS determination in AE is performed using statistical analysis based on the calibration of a gamma distribution fitted to the reference data, which improves the accuracy of the estimation and reduces the discrepancy with the optical measurement.