Automated Aircraft Dent Inspection via a Modified Fourier Transform Profilometry Algorithm

Lafiosca, Pasquale; Fan, Ip‐Shing; Avdelidis, Nicolas P.

doi:10.3390/s22020433

Cited by 5 publications

(2 citation statements)

References 39 publications

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“…The signals are obtained scanning flat a white board several times and in different positions with the 3D scanner. In this case a system based on Fourier transform profilometry [19,20] was chosen. An example of its noise distribution over a flat board about 40 cm wide is shown in Fig.…”

Section: Noise Signalsmentioning

confidence: 99%

Automatic Segmentation of Aircraft Dents in Point Clouds (SAE Paper 2022-01-0022)

Lafiosca¹,

Fan²,

Avdelidis³

2022

SAE Technical Paper Series

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Dents on the aircraft skin are frequent and may easily go undetected during airworthiness checks, as their inspection process is tedious and extremely subject to human factors and environmental conditions. Nowadays, 3D scanning technologies are being proposed for more reliable, human-independent measurements, yet the process of inspection and reporting remains laborious and time consuming because data acquisition and validation are still carried out by the engineer. For full automation of dent inspection, the acquired point cloud data must be analysed via a reliable segmentation algorithm, releasing humans from the search and evaluation of damage. This paper reports on two developments towards automated dent inspection. The first is a method to generate a synthetic dataset of dented surfaces to train a fully convolutional neural network.The training of machine learning algorithms needs a substantial volume of dent data, which is not readily available. Dents are thus simulated in random positions and shapes, within criteria and definitions of a Boeing 737 structural repair manual. The noise distribution from the scanning apparatus is then added to reflect the complete process of 3D point acquisition on the training. The second proposition is a surface fitting strategy to convert 3D point clouds to 2.5D. This allows higher resolution point clouds to be processed with a small amount of memory compared with state-of-the-art methods involving 3D sampling approaches. Simulations with available ground truth data show that the proposed technique reaches an intersection-over-union of over 80%. Experiments over dent samples prove an effective detection of dents with a speed of over 500 000 points per second.

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Section: Noise Signalsmentioning

confidence: 99%

Automatic Segmentation of Aircraft Dents in Point Clouds (SAE Paper 2022-01-0022)

Lafiosca¹,

Fan²,

Avdelidis³

2022

SAE Technical Paper Series

Self Cite

View full text Add to dashboard Cite

show abstract

“…Conversely, the transform-based methods, 12 – 14 requiring only a single fringe for phase calculation, boast high efficiency 15 – 18 The Fourier transform (FT) algorithm, 19 – 21 a typical transform-based technique, transforms the fringe pattern into the frequency domain for phase extraction. Despite its high computation efficiency, the band-pass filtering process in the FT algorithm may compromise accuracy in edge regions.…”

Section: Introductionmentioning

confidence: 99%

Dynamic three-dimensional measurement by spatial-domain phase-shifting method based on fringe projection profilometry

Zhu,

Deng,

Zhang

et al. 2024

Opt. Eng.

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The Fourier transform (FT) method is one of the foremost single-fringe techniques for high-speed three-dimensional (3D) surface reconstruction within the fringe projection profilometry (FPP). Despite its widespread use, the intrinsic issue of spectrum leakage in the FT method leads to diminished precision in regions of image edge. We introduce a spatial-domain phase-shifting (SDPS) method, employing pixel spatial translation to extract the phase-shifting subfringe sequence, followed by the least-square fitting technique to accurately determine surface phase information. Simulation analyses for continuous and discontinuous structures are conducted to affirm that the SDPS method could mitigate the edge error in comparison to the FT method. Meanwhile, the factors that may influence the performance of the proposed method are also analyzed, including the background, modulation, and spatial translation distance. Experiments of static and dynamic scenarios are carried out to further demonstrate that the SDPS method could achieve improved measurement precision in edge areas when compared with the FT method and has the potential to be applied in dynamic 3D surface reconstruction with high precision and efficiency in FPP.

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3D reconstruction from structured-light profilometry with dual-path hybrid network

Wang

Qiu

et al. 2022

EURASIP J. Adv. Signal Process.

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With the rapid development of high-speed image sensors and optical imaging technology, these have effectively promoted the improvement of non-contact 3D shape measurement. Among them, striped structured-light technology has been widely used because of its high measurement accuracy. Compared with classical methods such as Fourier transform profilometry, many deep neural networks are utilized to restore 3D shape from single-shot structured light. In actual engineering deployments, the number of learnable parameters of convolution neural network (CNN) is huge, especially for high-resolution structured-light patterns. To this end, we proposed a dual-path hybrid network based on UNet, which eliminates the deepest convolution layers to reduce the number of learnable parameters, and a swin transformer path is additionally built on the decoder to improve the global perception of this network. The experimental results show that the learnable parameters of the model are reduced by 60% compared with the UNet, and the measurement accuracy is not degraded at the same time. The proposed dual-path hybrid network provides an effective solution for structured-light 3D reconstruction and its practice in engineering.

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Automated Aircraft Dent Inspection via a Modified Fourier Transform Profilometry Algorithm

Cited by 5 publications

References 39 publications

Automatic Segmentation of Aircraft Dents in Point Clouds (SAE Paper 2022-01-0022)

Automatic Segmentation of Aircraft Dents in Point Clouds (SAE Paper 2022-01-0022)

Dynamic three-dimensional measurement by spatial-domain phase-shifting method based on fringe projection profilometry

3D reconstruction from structured-light profilometry with dual-path hybrid network

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