Evaluation of an ancient cast-iron Buddha head by step-heating infrared thermography

Li, Xiaoli; Tao, Ning; Sun, Jie; Lei, Yong; Qu, Liang; Gao, Fei; He, Yi; Wang, Guan; Feng, Lichun

doi:10.1016/j.infrared.2019.03.017

Cited by 7 publications

(2 citation statements)

References 28 publications

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“…Contrary to some other areas of investigation, the examination of historical items demands extra care with regard to safety. For example, the investigation of the cast-iron Buddha head created in China during the Song Dynasty (AD 960-1279) is a very delicate and important process that was carried out by IRT [ 20 ].…”

Section: Background On Irt In Cultural Heritage and Irt Using Aimentioning

confidence: 99%

A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography

Moradi

Ghorbani

Сфарра

et al. 2022

Sensors

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Assessment of cultural heritage assets is now extremely important all around the world. Non-destructive inspection is essential for preserving the integrity of artworks while avoiding the loss of any precious materials that make them up. The use of Infrared Thermography is an interesting concept since surface and subsurface faults can be discovered by utilizing the 3D diffusion inside the object caused by external heat. The primary goal of this research is to detect defects in artworks, which is one of the most important tasks in the restoration of mural paintings. To this end, machine learning and deep learning techniques are effective tools that should be employed properly in accordance with the experiment’s nature and the collected data. Considering both the temporal and spatial perspectives of step-heating thermography, a spatiotemporal deep neural network is developed for defect identification in a mock-up reproducing an artwork. The results are then compared with those of other conventional algorithms, demonstrating that the proposed approach outperforms the others.

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Section: Background On Irt In Cultural Heritage and Irt Using Aimentioning

confidence: 99%

A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography

Moradi

Ghorbani

Сфарра

et al. 2022

Sensors

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“…The samples in this experiment were seriously rusted, and the scientific analysis and the detection of components and rusty decay products were able to identify the cause of iron anchor corrosion and the degree of rust, to provide a scientific basis for subsequent protection and restoration [17][18][19]. First, the digital image collection of cultural relics samples was conducted and the disease map was drawn.…”

Section: Samplingmentioning

confidence: 99%

Analysis of Iron Anchor Diseases Unearthed from Gudu Ruins in Xianyang City, Shaanxi Province, China

Mai

Chen²,

Zhang

et al. 2022

Coatings

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Iron cultural relics are easily affected by environmental factors and can completely rust away. As early as the Qin Dynasty in ancient China, Xianyang Gudu was part of the most important transportation route to the West from ancient Chang’an; research into Xianyang Gudu has provided important information for understanding the historical changes in ancient China, East–West trade, and ancient boating technology. In this research, we use the iron anchors unearthed from the Gudu ruins in Xianyang City, Shaanxi Province, China as the research object; then, we used a scanning electron microscope–energy dispersive spectrometer (SEM-EDS), a high-resolution X-ray diffractometer (XRD), ion chromatography, and other methods to detect the corroded products of the iron anchors, and analyzed the iron anchor diseases in different preservation environments to explore the relationship between iron anchor disease and the preservation environment. This research found that the corroded products of the iron anchors contained the harmful tetragonal lepidocrocite (β-FeOOH) and that a high concentration of salt ions in the river channel accelerated the corrosion of the anchors; this analysis, based on the disease results, can provide a basis for the subsequent scientific restoration of iron anchors.

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Prediction of defect depth in GFRP composite by square-heating thermography

Tao

Zhang

et al. 2023

Infrared Physics & Technology

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Evaluation of an ancient cast-iron Buddha head by step-heating infrared thermography

Cited by 7 publications

References 28 publications

A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography

A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography

Analysis of Iron Anchor Diseases Unearthed from Gudu Ruins in Xianyang City, Shaanxi Province, China

Prediction of defect depth in GFRP composite by square-heating thermography

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