Damage pattern recognition and damage evolution analysis of unidirectional CFRP tendons under tensile loading using acoustic emission technology

2020 ◽  
Vol 238 ◽  
pp. 111948 ◽  
Author(s):  
Jie Xu ◽  
Weixin Wang ◽  
Qinghua Han ◽  
Xuan Liu
Keyword(s):  
Pattern Recognition ◽  
Acoustic Emission ◽  
Damage Evolution ◽  
Tensile Loading ◽  
Damage Pattern ◽  
Evolution Analysis ◽  
Acoustic Emission Technology

scholarly journals Investigation on the Behavior of Tensile Damage Evolution in T700/6808 Composite Based on Acoustic Emission Technology

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Weihan Wang ◽  
Weifang Zhang ◽  
Shengwang Liu ◽  
Xiaoshuai Jin
Keyword(s):  
Acoustic Emission ◽  
Damage Evolution ◽  
Tensile Loading ◽  
Matrix Cracking ◽  
Composite Analysis ◽  
Fiber Breakage ◽  
Interface Damage ◽  
Initial Stage ◽  
The Matrix ◽  
Acoustic Emission Technology

T700/6808 composite has been widely used in aerospace field and the damage in composite will seriously influence the safety of aircraft. However, the behavior of damage evolution in T700/6808 composite when it suffered from tensile loading is seldom researched. In this paper, the acoustic emission (AE) technology is employed to research the process of damage evolution in T700/6808 composite under tensile loading. Results show that the damage in T700/6808 composite is small in the initial stage of tensile loading, and main damage is the matrix cracking. The composite has serious damage in the middle stage of tensile loading, which mainly includes the matrix cracking and the interface damage as well as the fiber breakage. The number of fiber breakages decreases rapidly in the later stage of tensile loading. When it comes into the stage of load holding, the composite has relatively smaller damage than that in the stage of tensile loading, and the fiber breakage rarely occurs in the composite. Analysis of damage modes shows that the criticality of the matrix cracking and the interface damage is higher than the fiber breakage, which illustrates that the reliability of T700/6808 composite could be improved by the optimization of matrix and interface.

Acoustic Emission Characterization of Damage Patterns in Composite Scarf Joints Using Unsupervised Learning

2020 ◽  
Author(s):  
D. Xu ◽  
Z. P. Chen ◽  
P. F. Liu ◽  
J. H. Wu ◽  
P. Jiao ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Acoustic Emission ◽  
Composite Structures ◽  
Tensile Loading ◽  
Matrix Cracking ◽  
Interface Debonding ◽  
Engineering Structures ◽  
Damage Pattern ◽  
Damage Initiation ◽  
Non Destructive

Abstract Interest in damage detection and damage pattern recognition of engineering structures by non-destructive techniques has been increasingly growing. As a non-destructive technique, acoustic emission (AE) has developed rapidly to detect dynamic defects and their evolution behaviors of composite structures, based on the transient elastic waves produced by rapid energy release due to the geometry change of structures. In this paper, AE technology is utilized to monitor the real-time condition of the composite scarf joint (SJ) under tensile loading. First, after AE signal acquisition, dimensionality reduction of eight AE features is realized by employing principal component analysis such that the Curse of Dimensionality can be avoided. Second, feature selection is continued by introducing two evaluation indexes, i.e., correlation coefficient and Laplacian score. Third, after the optimal cluster number is determined, damage pattern recognition is accomplished by introducing k-means++ algorithm which explores the distribution of each pattern in the space constructed by four informative AE features. Based on the clustering results, damage initiation and evolution in SJ specimens under tensile loading are subsequently explored. The shear failure of the adhesive layer which is a characteristic damage pattern for SJ specimens shows a relatively-high activity after the early stage. Matrix cracking and fiber/matrix interface debonding are two fundamental damage patterns which keep active in the whole process.

Damage Pattern Recognition of Refractory Materials Based on k-Means Clustering Analysis

2012 ◽  
Vol 602-604 ◽  
pp. 990-994
Author(s):  
Xi Li ◽  
Zhi Gang Wang ◽  
Chang Ming Liu ◽  
Bing Qiang Han
Keyword(s):  
Pattern Recognition ◽  
Acoustic Emission ◽  
Clustering Analysis ◽  
Bending Test ◽  
Refractory Materials ◽  
Damage Pattern ◽  
Three Point Bending ◽  
Centroid Frequency ◽  
Acquisition Device ◽  
Microscopic Damage

The k-means algorithm was used to divide the acoustic emission signals collected during the three-point bending test into two types. Combining with the analysis of AE parameters can we distinguish the micro-damage pattern recognition of the refractory materials. The bending test equipment is HMOR/STRAIN, and the AE acquisition device is DISP from PAC. Amplitude, counts, risetime, duration and centroid frequency were selected as the AE parameters .The microscopic damage modes of the refractory materials were recognized.

Damage Evolution Analysis of Mortar with Different w/c Ratio by Acoustic Emission Technique

2019 ◽  
Vol 55 (3) ◽  
pp. 202-209
Author(s):  
Yan Wang ◽  
Li Zhou ◽  
HongXiang Hu ◽  
Lu Ge ◽  
TingTing Zhang
Keyword(s):  
Acoustic Emission ◽  
Damage Evolution ◽  
Acoustic Emission Technique ◽  
Evolution Analysis
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