Method for Automatic Recognition of Defects in Aircraft Riveted Joints Using Wavelet Transform and Neural Network
Author:
Affiliation:
1. V.A. Trapeznikov Institute of Control Sciences of RAS,Laboratory of Intellectual Control Systems and Modelling,Moscow,Russia
2. V.A. Trapeznikov Institute of Control Sciences of RAS,Laboratory of Cyber-physical Systems,Moscow,Russia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9790074/9790739/09790755.pdf?arnumber=9790755
Reference24 articles.
1. Aging aircraft rivet site inspection using magneto-optic imaging: automation and real-time image processing;fan;Proceedings of the 9th Joint FAA/DoD/NASA Aging Aircraft Conference,2006
2. Defect detection for aircraft components: An approach using ultrasonic guided waves and neural networks;haig;51st Annual Conference of the British Institute of Non-Destructive Testing,2012
3. Defects Detection and Recognition in Aviation Riveted Joints by Using Ultrasonic Echo Signals of Non-Destructive Testing
4. An improved automated ultrasonic NDE system by wavelet and neuron networks
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