Non-Destructive Evaluation of the Quality of Adhesive Joints Using Ultrasound, X-ray, and Feature-Based Data Fusion

被引:9
作者
Jasiuniene, Elena [1 ,2 ]
Yilmaz, Bengisu [1 ,3 ]
Smagulova, Damira [1 ,2 ]
Bhat, Gawher Ahmad [1 ]
Cicenas, Vaidotas [1 ]
Zukauskas, Egidijus [1 ]
Mazeika, Liudas [1 ,2 ]
机构
[1] Kaunas Univ Technol, Ultrasound Res Inst, K Barsausko Str 59, LT-51423 Kaunas, Lithuania
[2] Kaunas Univ Technol, Dept Elect Engn, Studentu St 50, LT-51368 Kaunas, Lithuania
[3] Bundesanstalt Materialforschung und prufung BAM, Acoust & Electromagnet Methods Div, D-12205 Berlin, Germany
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 24期
关键词
data fusion; ultrasonics; radiography; adhesive joints; adhesive bond; non-destructive evaluation; interface defects; multiple reflections; signal modeling; IMAGE FUSION; COMPOSITES; DEFECTS;
D O I
10.3390/app122412930
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages and limitations. The integration of data obtained from pulse echo immersion ultrasound testing and radiography holds immense potential to help improve the reliability of non-destructive evaluation. In this study, distinctive features obtained from single techniques, traditional ultrasonic pulse echo testing, and radiography, as well as fused images, were investigated and the suitability of these distinctive features and fusion techniques for improving the probability of defect detection was evaluated. For this purpose, aluminum single lap joints with brass inclusions were analyzed using ultrasound pulse echo and radiography techniques. The distinctive features were extracted from the data obtained, and images of features obtained by both techniques were fused together. Different combinations of features and fusion algorithms were investigated, considering the desire to automate data evaluation in the future.
引用
收藏
页数:20
相关论文
共 44 条
  • [21] Maev R.G., 2006, P ECNDT 2006 9 EUR C, P1
  • [22] Advances, limitations and prospects of nondestructive testing and evaluation of thick composites and sandwich structures: A state-of-the-art review
    Nsengiyumva, Walter
    Zhong, Shuncong
    Lin, Jiewen
    Zhang, Qiukun
    Zhong, Jianfeng
    Huang, Yuexin
    [J]. COMPOSITE STRUCTURES, 2021, 256 (256)
  • [23] Ultrasonic analysis and lock-in thermography for debonding evaluation of composite adhesive joints
    Palumbo, D.
    Tamborrino, R.
    Galietti, U.
    Aversa, P.
    Tati, A.
    Luprano, V. A. M.
    [J]. NDT & E INTERNATIONAL, 2016, 78 : 1 - 9
  • [24] Poularikas A., 2017, HDB MULTISENSOR DATA
  • [25] Investigation of influence of printing parameters on the quality of 3D printed composite structures
    Rimasauskas, Marius
    Jasiuniene, Elena
    Kuncius, Tomas
    Rimasauskiene, Ruta
    Cicenas, Vaidotas
    [J]. COMPOSITE STRUCTURES, 2022, 281
  • [26] Structural health monitoring of adhesive joints under pure mode I loading using the electrical impedance measurement
    Sam-Daliri, Omid
    Faller, Lisa-Marie
    Farahani, Mohammadreza
    Zangl, Hubert
    [J]. ENGINEERING FRACTURE MECHANICS, 2021, 245
  • [27] Adhesive bond quality classification using machine learning algorithms based on ultrasonic pulse-echo immersion data
    Samaitis, Vykintas
    Yilmaz, Bengisu
    Jasiuniene, Elena
    [J]. JOURNAL OF SOUND AND VIBRATION, 2023, 546
  • [28] Shafer G., 2020, MATH THEORY EVIDENCE
  • [29] Nonlinear ultrasonic evaluation of the fatigue damage of adhesive joints
    Shui, Guoshuang
    Wang, Yue-sheng
    Huang, Peng
    Qu, Jianmin
    [J]. NDT & E INTERNATIONAL, 2015, 70 : 9 - 15
  • [30] Novel Processing Algorithm to Improve Detectability of Disbonds in Adhesive Dissimilar Material Joints
    Smagulova, Damira
    Mazeika, Liudas
    Jasiuniene, Elena
    [J]. SENSORS, 2021, 21 (09)