Corrosion detection and severity level prediction using acoustic emission and machine learning based approach-Reference-Cited by-同舟云学术

Corrosion detection and severity level prediction using acoustic emission and machine learning based approach

Published:2021-12 Issue:4 Volume:12 Page:3891-3903
ISSN:2090-4479
Container-title:Ain Shams Engineering Journal
language:en
Short-container-title:Ain Shams Engineering Journal

Author:

Sheikh Muhammad Fahad,Kamal Khurram,Rafique Faheem,Sabir Salman,Zaheer Hassan,Khan Kashif

Funder

Sichuan University

National Natural Science Foundation of China

Airbus

Publisher

Elsevier BV

Subject

General Engineering

Reference32 articles.

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2. Brief review on corrosion & its prevention;Mali;J Environ Eng Stud,2017

3. NACE – National Association of Corrosion Engineers. NACE SP0294-2006: Standard practice – Design, fabrication, and inspection of storage tank systems for concentrated fresh and process sulfuric acid and oleum at ambient temperatures. Houston; 2006. 42p.

4. Agarwala, Vinod S., Perry L. Reed, and Siraj Ahmad. Corrosion detection and monitoring-A review. CORROSION 2000. NACE International; 2000.

5. Global needs for knowledge dissemination, research, and development in materials deterioration and corrosion control;Schmitt,2009

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