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    Smart Diagnostics: Hierarchical Deep Learning of Acoustic Emission Signals for Early Crack Detection in Zirconia Dental Structures
    (2026-05-01)
    Tuntiwong, Kuson
    ;
    Wangman, Rangsinee
    ;
    Kanchanatawewat, Kanchana
    ;
    Anucul, Boonjira
    ;
    Sritart, Hiranya
    Monolithic zirconia restorations are frequently affected by the unnoticed growth of subcritical cracks, a failure process that is not captured by traditional imaging methods like radiographs and ultrasounds in sophisticated dental architectures. To address this evaluative inadequacy, this research introduces a hierarchical deep learning framework for microcrack detection and spatial localization. We promote a hierarchical deep learning system that integrates Acoustic Emission (AE) detection alongside signal processing. Raw AE signals utilized during dynamic loading are enhanced via Kalman filtering and Continuous Wavelet Transform (CWT) to construct high-fidelity time–frequency scalograms. The diagnostic pipeline operates in two stages: first, a hybrid CNN–BiGRU network with temporal attention fulfills zirconia component-level classification; second, a ResNet-18 backbone integrated with Bidirectional LSTM and Multi-Head Attention precisely localizes defects across five anatomical crown regions. This hierarchical design effectively captures the non-stationary, transient nature of fracture-induced stress waves. The framework achieved an F1-score of 99.00% and an AUC of 0.994, significantly outperforming conventional convolutional networks. By enabling predictive maintenance through early, non-invasive damage localization, this study demonstrates a promising laboratory framework for AE-based crack detection in zirconia dental structures and prosthetics and toward enhanced clinical reliability in digital dentistry.
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    Dielectric material determination using the radar equation in RFID sensor applications
    (2016-03-07)
    Suwalak, Rattapong
    ;
    Phongcharoenpanich, Chuwong
    ;
    Torrungrueng, Danai
    ;
    Akkaraekthalin, Prayoot
    A radar-cross section (RCS) of passive printed tags in a radio frequency identification (RFID) is presented to determine a dielectric constant of a material under test (MUT). In this paper, a printed loop tag with a meander-line is employed as an RFID sensor. The optimum parameters of the proposed RFID sensor are obtained using the CST Microwave Studio program. This paper employs two RFID sensors with different RCS to improve the accuracy of dielectric material determination. The relation between the read range (Rmax) and the real part of dielectric constant (?r) can be used to determine the dielectric constant of MUT.
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    A radar-cross section of a passive tag on dielectric material in an RFID sensor application
    (2015-08-17)
    Suwalak, Rattapong
    ;
    Phongcharoenpanich, Chuwong
    ;
    Torrungrueng, Danai
    ;
    Akkaraekthalin, Prayoot
    This paper is mainly present to a radar-cross section (RCS) of a passive tag in a radio frequency identification (RFID) sensor application. To determine qualities of a dielectric material under test (MUT) with a non-destructive testing (NDT) technique, a proposed meander-line dipole tag antenna is employed as a RFID sensor. The design and optimum parameters of the proposed RFID sensor are obtained using the CST Microwave Studio program. In this paper, instead of focusing on the scalar backscattered power based on the Friis transmission equation, we are also studying the RCS range equation to utilize for improve the accuracy of determination a qualities of MUT in a RFID sensor system. Simulated results show that the characteristics of the proposed RFID sensor such as the input impedance, antenna gain, power transmission coefficient and RCS.
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    Characteristics of an RFID sensor for a different number of reinforced metal bars in lossy light weight concrete
    (2015-04-22)
    Suwalak, Rattapong
    ;
    Phongcharoenpanich, Chuwong
    ;
    Torrungrueng, Danai
    The radio frequency identification (RFID) sensor technique applied to detect a different number of reinforced metal bars in a lossy light weight concrete (LWC) is presented. The proposed dipole antenna with inductive loop is employed as an RFID sensor. A different number of reinforced metal bars are studied through the characteristics of the RFID sensor placed on LWC. Simulations are performed using the CST Microwave Studio simulation program. It is found that the reinforced metal bars in LWC have important effects to the antenna gain of the RFID sensor.
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    Characteristics of specifically designed tags placed on a dielectric material
    (2014-01-01)
    Suwalak, Rattapong
    ;
    Phongcharoenpanich, Chuwong
    ;
    Torrungrueng, Danai
    A proposed folded dipole tag antenna for a radio frequency identification (RFID) sensor system is employed to determine qualities of a material under test (MUT). In this paper, a study on the characteristics of specifically designed tags (SDTs) placed on a dielectric material with a gap is presented. The CST Microwave Studio is used to study characteristics of these SDTs in the presence of an MUT near or contact with SDTs. Simulated results show that different SDTs provide different characteristics depending on MUTs. © 2014 IEEE.