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- Title
Evaluation of Cracks in Metallic Material Using a Self-Organized Data-Driven Model of Acoustic Echo-Signal.
- Authors
Teng, Xudong; Zhang, Xin; Fan, Yuantao; Zhang, Dong
- Abstract
Non-linear acoustic technique is an attractive approach in evaluating early fatigue as well as cracks in material. However, its accuracy is greatly restricted by external non-linearities of ultra-sonic measurement systems. In this work, an acoustical data-driven deviation detection method, called the consensus self-organizing models (COSMO) based on statistical probability models, was introduced to study the evolution of localized crack growth. By using pitch-catch technique, frequency spectra of acoustic echoes collected from different locations of a specimen were compared, resulting in a Hellinger distance matrix to construct statistical parameters such as z-score, p-value and T-value. It is shown that statistical significance p-value of COSMO method has a strong relationship with the crack growth. Particularly, T-values, logarithm transformed p-value, increases proportionally with the growth of cracks, which thus can be applied to locate the position of cracks and monitor the deterioration of materials.
- Subjects
FRACTURE mechanics; ECHO; NONLINEAR acoustics
- Publication
Applied Sciences (2076-3417), 2019, Vol 9, Issue 1, p95
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app9010095