Next Article in Journal
Rapid, Affordable and Efficient Screening of Multiple Blood Abnormalities Made Possible Using an Automated Tool for MALDI-ToF Spectrometry Analysis
Next Article in Special Issue
Effect of Rotating Cylinder on Mixing Performance in a Cylindrical Double-Ribbon Mixer
Previous Article in Journal
Intelligent Monitoring of Data Center Physical Infrastructure
Previous Article in Special Issue
Fabrication of Stretchable Transparent Electrode by Utilizing Self-Induced Vacuum Force
Open AccessArticle

Flaw Classification Algorithm for Heat Exchanger Tubes Using a Bobbin-Type Magnetic Camera

1
IT-based Real-Time NDT Center, Chosun University, Gwangju 61452, Korea
2
Department of Defense Science and Technology, Gwangju University, Gwangju 61743, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(23), 5000; https://doi.org/10.3390/app9235000
Received: 4 October 2019 / Revised: 15 November 2019 / Accepted: 18 November 2019 / Published: 20 November 2019
(This article belongs to the Special Issue Selected Papers from the ICMR 2019)
This paper presents an algorithm that estimates the presence, location, shape, and depth of flaws using a bobbin-type magnetic camera consisting of bobbin probes and a bobbin-type integrated giant magnetoresistance (GMR) sensor array (BIGiS). The presence of the flaws is determined by the lobe path of the Lissajous curves obtained from bobbin coil with respect to the applied frequency. The location of the flaw, i.e., whether it is an inner diameter (ID) or outer diameter (OD) flaw, can be determined from the rotational direction of the lobe with respect to the frequency change. The shape of the flaw is then determined from the area of the lobe and the BIGiS image. At this stage, multi-site damage can be determined from the BIGiS image. The effectiveness of the flaw classification algorithm was evaluated using various types of artificial flaws introduced into small-bore tube test specimens made of austenitic stainless steel. View Full-Text
Keywords: flaw classification algorithm; bobbin-type integrated GMR sensor array (BIGiS); time-varying electromagnetic field (T-EMF); heat exchanger tube flaw classification algorithm; bobbin-type integrated GMR sensor array (BIGiS); time-varying electromagnetic field (T-EMF); heat exchanger tube
Show Figures

Figure 1

MDPI and ACS Style

Sim, S.; Lee, H.; Lee, H.; Lee, J. Flaw Classification Algorithm for Heat Exchanger Tubes Using a Bobbin-Type Magnetic Camera. Appl. Sci. 2019, 9, 5000.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop