Support vector machine procedure and Gaussian mixture modelling of acoustic emission signals to study crack classification in reinforced concrete structures

R. Vidya Sagar (2019). "Support vector machine procedure and Gaussian mixture modelling of acoustic emission signals to study crack classification in reinforced concrete structures." In Proceedings of FraMCoS 10, Bayonne, France.

R. Vidya Sagar. "Support vector machine procedure and Gaussian mixture modelling of acoustic emission signals to study crack classification in reinforced concrete structures." Paper presented at FraMCoS 10, Bayonne, France, 2019.

R. Vidya Sagar, "Support vector machine procedure and Gaussian mixture modelling of acoustic emission signals to study crack classification in reinforced concrete structures," in Proc. FraMCoS 10, Bayonne, France, 2019.

@inproceedings{r-vidya-sagar2019,
  title     = {Support vector machine procedure and Gaussian mixture modelling of acoustic emission signals to study crack classification in reinforced concrete structures},
  author    = {R. Vidya Sagar},
  year      = {2019},
  booktitle = {Proceedings of FraMCoS 10},
  address   = {Bayonne, France},
}

TY  - CPAPER
TI  - Support vector machine procedure and Gaussian mixture modelling of acoustic emission signals to study crack classification in reinforced concrete structures
AU  - R. Vidya Sagar
PY  - 2019
T2  - Proceedings of FraMCoS 10
CY  - Bayonne, France
UR  - https://framcos.org/wp-content/uploads/framcos-papers/Support_vector_machine_procedure_and_Gaussian_mixture_modelling_of_acoustic_emis.pdf
AB  - Four point bending tests on reinforced concrete (RC) beam specimens were carried out and simultaneously released Acoustic Emissions (AE) were recorded in laboratory. This study reports on the AE characteristics of RC beams under monotonically increased loading. By using load-displacement curves and the AE signal parameters data, the fracture process of RC beams was studied. As the occurrence of AE events is random, a probabilistic approach named Gaussian Mixture Model (GMM) is implemented for AE data clustering related to tensile cracking and shear cracking considering different AE parameters. A supervised learning model named Support Vector Machine (SVM) procedure has been…
ER  -