Analysing the Probability of Detection of Shallow Spherical Defects by Means of Pulsed Thermography

被引:13
作者
D'Accardi, E. [1 ]
Palumbo, D. [1 ]
Errico, V [1 ]
Fusco, A. [1 ]
Angelastro, A. [1 ]
Galietti, U. [1 ]
机构
[1] Politecn Bari, Via Edoardo Orabona 4, I-70125 Bari, Italy
关键词
Pulsed thermography (PT); Non-destructive techniques (NDT); Probability of detection (PoD); Laser-powder bed fusion (L-PBF); Additive Manufacturing (AM); INFRARED THERMOGRAPHY;
D O I
10.1007/s10921-023-00936-y
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
The capability of Active Thermography (AT) techniques in detecting shallow defects has been proved by many works in the last years, both on metals and composites. However, there are few works in which these techniques have been used adopting simulated defects more representative of the real ones. The aim of this work is to investigate the capability of Pulsed Thermography of detecting shallow spherical defects in metal specimens produced with laser powder bed fusion (L-PBF) process and characterized by a thermal behaviour very far from the flat bottom hole and so near to the real one. In particular, the quantitative characterization of defects has been carried out to obtain the Probability of Detection (PoD) curves. In fact, it is very common in non-destructive controls to define the limits of defect detectability by referring to PoD curves based on the analysis of flat bottom holes with a more generous estimation and therefore not true to real defect conditions. For this purpose, a series of specimens, made by means of Laser-Powder Bed Fusion technology (L-PBF) in AISI 316L, were inspected using Pulsed Thermography (PT), adopting two flash lamps and a cooled infrared sensor. To improve the quality of the raw thermal data, different post-processing algorithms were adopted. The results provide indications about the advantages and limitations of Active Thermography (AT) for the non-destructive offline controls of the structural integrity of metallic components.
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页数:16
相关论文
共 33 条
  • [1] Probability of Detecting the Deep Defects in Steel Sample Using Frequency Modulated Independent Component Thermography
    Ahmad, Javed
    Akula, Aparna
    Mulaveesala, Ravibabu
    Sardana, H. K.
    [J]. IEEE SENSORS JOURNAL, 2021, 21 (10) : 11244 - 11252
  • [2] An integrated analytical model for the forecasting of the molten pool dimensions in Selective Laser Melting
    Angelastro, Andrea
    Campanelli, Sabina Luisa
    [J]. LASER PHYSICS, 2022, 32 (02)
  • [3] An Analytical Model for Defect Depth Estimation Using Pulsed Thermography
    Angioni, S. L.
    Ciampa, F.
    Pinto, F.
    Scarselli, G.
    Almond, D. P.
    Meo, M.
    [J]. EXPERIMENTAL MECHANICS, 2016, 56 (06) : 1111 - 1122
  • [4] [Anonymous], 2005, GESTS INT T COMPUTER
  • [5] [Anonymous], 2013, E146113 ASTM INT STD
  • [6] Study of the aging treatment on selective laser melted maraging 300 steel
    Campanelli, S. L.
    Contuzzi, N.
    Posa, P.
    Angelastro, A.
    [J]. MATERIALS RESEARCH EXPRESS, 2019, 6 (06)
  • [7] The Detection and Characterization of Defects in Metal/Non-metal Sandwich Structures by Thermal NDT, and a Comparison of Areal Heating and Scanned Linear Heating by Optical and Inductive Methods
    Chulkov, A. O.
    Tuschl, C.
    Nesteruk, D. A.
    Oswald-Tranta, B.
    Vavilov, V. P.
    Kuimova, M. V.
    [J]. JOURNAL OF NONDESTRUCTIVE EVALUATION, 2021, 40 (02)
  • [8] Limits and advantages in using low-cost microbolometric IR-Camera in lock-in thermography for CFRP applications
    D'Accardi, E.
    Dell'Avvocato, G.
    Palumbo, D.
    Galietti, U.
    [J]. THERMOSENSE: THERMAL INFRARED APPLICATIONS XLIII, 2021, 11743
  • [9] Capability to detect and localize typical defects of laser powder bed fusion (L-PBF) process: an experimental investigation with different non-destructive techniques
    D'Accardi, Ester
    Krankenhagen, Rainer
    Ulbricht, Alexander
    Pelkner, Matthias
    Pohl, Rainer
    Palumbo, Davide
    Galietti, Umberto
    [J]. PROGRESS IN ADDITIVE MANUFACTURING, 2022, 7 (06) : 1239 - 1256
  • [10] A Quantitative Comparison among Different Algorithms for Defects Detection on Aluminum with the Pulsed Thermography Technique
    D'Accardi, Ester
    Palumbo, Davide
    Tamborrino, Rosanna
    Galietti, Umberto
    [J]. METALS, 2018, 8 (10):