Application of PCA in Concrete Infrared Thermography Detection

An, Ning; Xie, Jun; Zheng, Xiaoyan; Gao, Xiaoni

doi:10.2991/iwmecs-15.2015.160

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…Specifically, the cumulative variance achieved by the four "PCs" in 2020 is 92.35%, while in 2021 and 2022, these figures change to 91.89% and 92.59%, respectively (see Table 4). Although the cumulative contribution rate surpassing 85% typically indicates a sufficient representation of the original variable information [80], this study sets a higher standard, choosing to select "PCs" that account for more than 90% of the variance to ensure a more robust representation. Meanwhile, the loading matrix produced by PCA reveals the correlation relationships among the "PCs" and their original input indicators.…”

Section: Pca Executionmentioning

confidence: 99%

A Comprehensive Study on Static and Dynamic Operational Efficiency in Major Korean Container Terminals Amid the Smart Port Development Context

Zhou,

Suh

2024

Sustainability

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Today, the concept of “smart ports”, which are designed to enhance operational efficiency and competitiveness, has emerged as a key paradigm in the port and maritime industry. As an integral component of maritime transportation networks, container terminals in ports play a crucial role in facilitating international trade and stimulating economic growth. Accordingly, the Korean government has steadily pursued policies and investments to improve the technological capabilities of ports, focusing on container terminals. However, there is still a lack of comprehensive research that thoroughly analyzes the operational efficiency of container terminals in domestic ports undergoing smart port technology implementation. Therefore, this study analyzes the operational efficiency of 20 container terminals across five major domestic ports, which are forerunners in smart port transformation, as declared by the Korean government. This study employs a Principal Component Analysis (PCA)–Data Envelopment Analysis (DEA) approach to increase the effectiveness of the analysis and addresses efficiency in two aspects: static and dynamic. The findings indicate that container terminals under Ulsan Port and Busan Port (New) have the best operational efficiency. In particular, Ulsan Port demonstrates significant improvement in terms of efficiency changes. The conclusion emphasizes the pivotal role of technological progress in achieving higher efficiency among container terminals. In addition to providing policymakers and port managers with useful insights into smart port transformation, this study is expected to make theoretical contributions to expanding the perspectives of port efficiency research by simultaneously encompassing static and dynamic analyses.

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Section: Pca Executionmentioning

confidence: 99%

A Comprehensive Study on Static and Dynamic Operational Efficiency in Major Korean Container Terminals Amid the Smart Port Development Context

Zhou,

Suh

2024

Sustainability

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“…Those images generated by employing PCA do keep the spatial pattern of the thermal flows. Recently, PCA is applied to analyze the thermography to detect the defects illustrated on the outside layers of reinforced concrete (RC) structures [6] [7]. For an RC structure, the surface temperatures of the building are slowly increased during the heating procedure; similarly, the surface temperatures are slowly decreased during the cooling procedure.…”

Section: Introductionmentioning

confidence: 99%

Analysing a Time Series of Thermographs to Identify the Defects of Building Exterior Layers

Huang¹,

Peng²,

Chen³

et al. 2017

Proceedings of the 2017 Asia International Conference on Quantitative InfraRed Thermography

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Thermography is designed to record the surface temperature information of the photographed objects. It is difficult to efficiently extract the useful information related the defects presented in the building outside walls because it is hard to analyze many thermographs at a time. Principal component analysis (PCA) has been widely used to analyze the hyperspectral satellite images by generating the new image that is composed of major characteristics extracted from hundreds of bands contained in the hyperspectral images. In this study, a scheme is proposed by applying PCA on the collected thermographs such that large data can be limited into the few enhanced thermographs, and then object-based image segmentation is introduced to analyze those enhanced thermographs such that the boundaries of the segmented regions can be described and lied on those enhanced thermographs. The image segmentation presented in the paper can efficiently group those pixels with collecting similar surface temperatures into the same regions such that each thermography can be composed by few groups. In each segmented group, the average surface temperature of each segmented region can be used to replace the surface temperature recorded in each pixel. Furthermore, the environmental effects acting on the given thermal image can be estimated by the proposed model. In doing so, those regions with the highest surface temperature information can be considered as defects located on the exterior building layer. Different nondestructive testing methods are, then, applied to those identified locations to verify the processed results. From the experimental results, the proposed approach does offer a reliable way to locate the defects presented on the building exterior layers because the results obtained by applying impact echo method are almost the same with the processed results of the proposed approach.

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