Damage Pattern Recognition and Crack Propagation Prediction for Crumb Rubber Concrete Based on Acoustic Emission Techniques

Applied Sciences

Zhengwu Fu¹  Giuseppe Lacidogna²  Xi Chen³  Jianjie Sun³ 

[1] Department of Civil Engineering, Tsinghua University, Beijing 100084, China;Department of Structural, Geotechnical and Building Construction, Politecnico di Torino, 10129 Turin, Italy;School of Civil Engineering, Tianjin University, Tianjin 300350, China;

关键词: acoustic emission;    crumb rubber concrete;    damage pattern recognition;    clustering methods;    artificial neural network;   

DOI  :  10.3390/app112311476

来源: DOAJ

【 摘 要 】

In this study, the clustering method of the concrete matrix rupture and rubber fracture damages as well as the prediction of the ultimate load of crumb rubber concrete using the acoustic emission (AE) technique were investigated. The loading environment of the specimens was a four-point bending load. Six clustering methods including k-means, fuzzy c-means (FCM), self-organizing mapping (SOM), Gaussian mixture model (GMM), hierarchical model, and density peak clustering method were analyzed; the results illustrated that the density peak clustering has the best performance. Next, the optimal clustering algorithm was used to cluster AE signals so as to study the evolution behavior of different damage modes, and the ultimate load of crumb rubber concrete was predicted by an artificial neural network. The results indicated that the combination of AE techniques and appropriate clustering methods such as the density peak clustering method and the artificial neural network could be used as a practical tool for structural health monitoring of crumb rubber concrete.

【 授权许可】

Unknown