# A Crack Characterization Method for Reinforced Concrete Beams Using an Acoustic Emission Technique
## 2 Related Works  
A numerical model and an onsite monitoring mechanism of retro-filled concrete beams with nonrectangular cross-sections was presented by [PERSON] et al. [17]. Using nondestructive techniques, like impact tests and pull-out tests, they estimated the mechanical parameters of the concrete specimen. Simultaneously, AE was used to investigate the micro-cracking and creep effects. [PERSON] et al. [8] used AE to monitor slow dynamics in polymer concrete samples. AE was used for the characterization of the micro-damage mechanism in real time by putting concrete specimens under a three-point bending test. Finally, k-means clustering accompanied by principal component analysis was used to classify AE data. [PERSON] et al. [9] designed a framework to automate the probabilistic classification of the cracksusing AE. The average frequency and rising angle (RA) values were clustered using an unsupervised learning algorithm for classification. The clustered data was further classified using a support vector machine to identify the damage condition. [PERSON] et al. [10] evaluated and monitored the mechanical performance of lightweight carbon fiber and concrete beams using AE and digital image correlation. They found that AE signals with high-frequency components represent the beams suffering from matrix cracking. [PERSON] [11] conducted a study using several types of concrete by means of AE during bending tests. The signals collected at different stages of fractures displayed distinguishable signatures. The proposed method could successfully distinguish between tensile micro-cracks and brittle macro-cracks. Additionally, it could detect fiber pullout, enabling a warning when the final failure occurs. [PERSON] et al. [12] presented a study that focused on developing an effective AE technique to monitor the initiation and propagation of cracks considering various types of concrete. Additionally, they identified acoustic parameters that can determine both shear and tensile cracks. [PERSON] et al. [13] proposed that it is quite difficult and, to some extent, impossible to characterize macro-cracks occurring in concrete beams by observing the changes in mechanical properties. Therefore, they suggested the use of the AE technique to comprehend the damage process. Cumulative AE hits under increasing loads in their proposed method could successfully detect the damage initiation process. The assessment of the severity was conducted by parameterizing load/calm ratios. [PERSON] et al. [15] conducted a study on how the loading rate impacts the behavior of the fracture. AE was used for real-time monitoring. The results showed that the toughness of concrete has rate effect points in the curve representing the cumulative AE hits and cumulative ringing count. As time passes by, one of these can represent the commencing point of the concrete boundary effect. Further, they found that, as the loading rate was increased, the width of the crack increased and the ductility of concrete decreased. On the other hand, the quantity of shear cracks increased. For the first time in the field of concrete crack characterization and detection, [PERSON] et al. [7] considered using the MD to show the time history of the increasing severity of cracks in concrete beams. They used the Mahalanobis-Taguchi system to build a degradation indicator. The Chebyshev inequality was used to suppress the noise in the degradation indicator. The main issue with the work is that it did not consider the full-length signal and perform classification that can distinguish between normal and crack modes. However, it is necessary to build the degradation indicator considering the full-length signal and, also, perform the classification in such a way that the system can precisely distinguish between micro-cracks and fractures, along with the normal mode. [PERSON] et al. [34] detected impulses occurring in the AE signals using the constant-false-alarm-rate algorithm. They considered AE features like counts, duration, amplitude, risetime, energy, etc.