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Evaluation of Cracks in Metallic Material Using a Self-Organized Data-Driven Model of Acoustic Echo-Signal
Key Laboratory of Modern Acoustics, Ministry of Education, Institute of Acoustics, Nanjing University, Nanjing, China & School of Electronic and Electric Engineering, Shanghai University of Engineering Science, Shanghai, China.
Nanjing Manse Acoustics Technology Co. Ltd., Nanjing, China.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-3034-6630
Key Laboratory of Modern Acoustics, Ministry of Education, Institute of Acoustics, Nanjing University, Nanjing, China.
2019 (English)In: Applied Sciences: APPS, ISSN 1454-5101, E-ISSN 1454-5101, Vol. 9, no 1, article id 95Article in journal (Refereed) Published
Abstract [en]

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. © 2018 by the authors. 

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI, 2019. Vol. 9, no 1, article id 95
Keywords [en]
crack growth, acoustic echo, COSMO, p-value
National Category
Applied Mechanics
Identifiers
URN: urn:nbn:se:hh:diva-39445DOI: 10.3390/app9010095ISI: 000456579300095Scopus ID: 2-s2.0-85059353615OAI: oai:DiVA.org:hh-39445DiVA, id: diva2:1317222
Note

Financiers: National Natural Science Foundation of China, QingLan Project & The Fundamental Research Funds for the Central Universities.

Available from: 2019-05-22 Created: 2019-05-22 Last updated: 2019-06-10Bibliographically approved

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Fan, Yuantao

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