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Lookup NU author(s): Dr Bin Gao,
Professor Gui Yun TianORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2018.
For re-use rights please refer to the publisher's terms and conditions.
IEEEUltrasound is widely used for measuring wall-thickness and diameter of tubes. All tubes are required to conduct the full profile of inspection to guarantee the quality by using an automatic Nondestructive testing system. However, most of the current ultrasonic testing works were done under the stationary condition for both specimen and probes with limited detection area. There exist challenges for providing a precisely measurement by approaching an automatic ultrasonic testing with high-speed inspection while it suffers the influence from temperature change of the water, mechanical vibration and tube deformation. In this paper, the spectral analysis of ultrasonic resonance was applied to measure the wall-thickness and diameter of the tubes. Besides, a novel intelligent compensation ultrasonic system with embedded strategy of self-organizing feature mapping (SOFM) artificial neural network is proposed to eliminate the interference under the condition of high-speed inspection. The experimental and comparison studies have been carried out. The corresponding results illustrate that the measurement precision of diameter and wall thickness can be effectively improved by using the proposed method.
Author(s): Xiao X, Gao B, Tian GY, Zhang YC, Chen S
Publication type: Article
Publication status: Published
Journal: IEEE Sensors Journal
Print publication date: 15/08/2018
Online publication date: 13/04/2018
Acceptance date: 02/04/2018
Date deposited: 04/06/2018
ISSN (print): 1530-437X
ISSN (electronic): 1558-1748
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