Characterizing Depth of Defects with Low Size/Depth Aspect Ratio and Low Thermal Reflection by Using Pulsed IR Thermography

Moskovchenko, Alexey; Švantner, Michal; Вавилов, В. П.; Чулков, А. О.

doi:10.3390/ma14081886

Cited by 12 publications

(5 citation statements)

References 30 publications

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“…where ρ is the density, c is the specific heat capacity, k is the thermal conductivity, α is the thermal diffusivity of the material, and t represents the time. The coefficient γ describes the contrast of the thermal effusivities at the interface of the sound material to defect, which is very close to 1 only in the theoretical case of perfect reflection and a large discontinuity [7], [26]- [27]. During the last years in which the pulsed thermography technique has been used for several applications, several post-processing algorithms were considered and adopted to improve the quality of the raw thermal data and then the signal-to-noise ratio such as Pulsed Phase Thermography (PPT) [1], [6]- [7], [15], Thermographic Signal Reconstruction (TSR) [16]- [17], Principal Component Thermography (PCT) [18], Slope and R 2 [24].…”

Section: Theoretical Background: Pulsed Thermography and Post-process...mentioning

confidence: 95%

Analysing the probability of detection of shallow spherical defects by means of Active Thermography

D’Accardi

Palumbo

Errico

et al. 2022

Preprint

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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 Active 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 (IR) 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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Section: Theoretical Background: Pulsed Thermography and Post-process...mentioning

confidence: 95%

Analysing the probability of detection of shallow spherical defects by means of Active Thermography

D’Accardi

Palumbo

Errico

et al. 2022

Preprint

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“…The depth d and diameter D of the defect and thickness L of the block varied from 1 to 3 mm, 1 to 10 mm and 1.2 to 10 mm respectively. The numerical model was described in detail in the work [7]. Thermal properties of the solid block were: density ρ=7800kg/m 3 , thermal conductivity k=54 W/(m•K) and heat capacity Cp=465 J/(kg•K).…”

Section: Numerical Model and Experimental Setupmentioning

confidence: 99%

“…3D heat diffusion processes should be taken into account in this case. The new defect depth estimation technique, which takes into account the defect size and shape, was presented by the authors in previous study [7]. This method is based on modified analytical model obtained by Almond et al [8] and nonlinear fitting procedures [9].…”

Section: Introductionmentioning

confidence: 99%

Infrared Thermographic Method for Depth Characterization of Low size/Depth Aspect Ratio defects in Metal Parts

Moskovchenko

ŠVANTNER

Muzika

2022

METAL 2022 Conference Proeedings

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Infrared thermography is a fast and illustrative nondestructive testing method, which is widely used for an inspection of metallic and non-metallic materials. Previously it was used mostly for defects indication. However, modern devices and software allow an application of a quantitative estimation of parameters of the defects. This contribution presents a novel infrared thermographic method for quantitative defect depth estimation. The majority of known thermographic techniques is based on a 1D heat transfer model and does not take into account 3D heat transfer. These methods are applicable only for large defects, which lateral size can be assumed as infinite. In contrast, the presented technique takes into account lateral dimension of defects and a finite thickness of a tested material. The method is based on a modification of the 1D analytical solution obtained by Almond et al. and a nonlinear optimization procedure. The algorithm was verified by numerical modelling and flash-pulse thermographic inspection experiments. Applicability of the method for the defect depth evaluation in the duraluminum parts was demonstrated.

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“…Various testing techniques, like acoustic emission testing [12], magnetic testing [13], infrared thermographic testing [14] and so on, could be adopted for NDT of additive manufactured products by gathering testing information of target products after the manufacturing process or simultaneously. The NDT of AM can be roughly categorized into two types: in-situ and ex-situ.…”

Section: Introductionmentioning

confidence: 99%

Thermal deformation prediction for additive manufacturing of thin-walled components based on multi-layer transfer learning

WANG,

XU,

ZHANG

et al. 2024

Preprint

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This paper presents a thermal deformation prediction method for additive manufacturing of thin-walled components based on multi-layer transfer learning (MTL). The printability is forwardly designed via multi-objective optimization (MOO) by evaluating scanning length, spot amount and segment amount, accompanied by support material. To avoid the burdened and time-consuming simulation of FEM for various geometric characteristics of thin-walled components, the feed-forward multi-layer perceptron was constructed as the main structure of MTL to rapidly obtain temperature and deformation distributions of manufactured parts. The proposed method is verified by the SLM of mechanical unshrouded turbine. The metallographic diagrams of manufactured components were generated to observe the fabricating quality and verify the effectiveness of the MTL-based method. The metallographic experiment of the fabricated piece proves that the main microstructure of the cross-section of molten pool is spindly columnar crystals. The cross-section morphology and size of the molten pool is different due to different process parameters, making the width of grain is about 1µm. The proposed method is especially useful for metal 3D printing under uncertainty.

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Characterizing Depth of Defects with Low Size/Depth Aspect Ratio and Low Thermal Reflection by Using Pulsed IR Thermography

Cited by 12 publications

References 30 publications

Analysing the probability of detection of shallow spherical defects by means of Active Thermography

Analysing the probability of detection of shallow spherical defects by means of Active Thermography

Infrared Thermographic Method for Depth Characterization of Low size/Depth Aspect Ratio defects in Metal Parts

Thermal deformation prediction for additive manufacturing of thin-walled components based on multi-layer transfer learning

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