&lt;title&gt;Shearography system for the testing of large-scale aircraft components taking into account noncooperative surfaces&lt;/title&gt;

Kalms, Michael; Jueptner, Werner P. O.; Tober, Gustav; Bisle, Wolfgang; Scherling, Dieter

doi:10.1117/12.498440

Cited by 12 publications

(6 citation statements)

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“…2.1 DSSPI System for Image Acquisition DSSPI is a highly precise and robust measurement technique that offers full-field, nondestructive measurement of out-of-plane deformation. This method is widely used in various fields, including the conservation of ancient artifacts, 10 mechanical manufacturing, 11 aerospace, 12 and medicine. 13 Figure 1 shows the schematic diagram of the device that utilizes DSSPI to measure out-ofplane displacement.…”

Section: Principlementioning

confidence: 99%

Looseness inspection of fasteners based on digital shearing speckle pattern interferometry and convolutional neural network

Deng,

Gao,

Chen

et al. 2024

Opt. Eng.

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The fastener plays a critical role in ensuring the stability and safety of modern engineering structures. However, factors such as vibration, shock, temperature changes, and others can cause fasteners to become loose, thereby compromising the stability and safety of the overall structure. Currently, fastener inspection is primarily done manually, and there is no widely adopted automatic method for real-time detection of fastener looseness. We proposed a fastener looseness inspection method based on digital shearing speckle pattern interferometry (DSSPI) and convolutional neural network (CNN). The key distinction between our proposed method and traditional vision-based methods is that our approach can identify loose fasteners without relying on direct visual observation of the fasteners themselves. Our approach involved setting up a DSSPI system to capture shearing speckle patterns, and the CNN model automatically extracted features from these images and classified them to detect loose fasteners. Principle-validation experiments were conducted to verify the feasibility of the methodology. The trained model achieved a classification accuracy of 92.57%, with a resolution of 0.04 mm and a completion time of only 2.03 ms for a single judgment. That is quite accurate, more sensitive, and much faster than the three-dimensional vision-based method. Furthermore, our proposed method has strong robustness to ambient light, while the incorporation of Random Erasing technology enhances robustness to part occlusion or damage of the measured surface. Most notably, our method can detect loose fasteners before deformation, a capability that conventional vision-based methods lack. These findings demonstrate the tremendous potential of our method for real-time inspection of fastener looseness.

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Section: Principlementioning

confidence: 99%

Looseness inspection of fasteners based on digital shearing speckle pattern interferometry and convolutional neural network

Deng,

Gao,

Chen

et al. 2024

Opt. Eng.

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“…In our system only thermal and mechanical loading is applied. 4 Mechanical loading is performed by changing the pressure within the test environment. To this purpose a selfadhesive vacuum chamber was developed, Fig.…”

Section: Applied Loadingmentioning

confidence: 99%

“…[3][4][5] The method is based on the digital correlation of two speckled wave fronts representing two states of the object under test such as an unloaded and a loaded one. A special quality of DSS is the so-called self-reference of each interferometrically sensitive speckle pattern.…”

Section: Introductionmentioning

confidence: 99%

Mobile shearography system for the inspection of aircraft and automotive components

Kalms

Osten

2003

Opt. Eng

Self Cite

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Shearography is an approved and powerful tool for the nondestructive investigation of technical components with respect to material faults and structural imperfections. An application field of high interest is the inspection of aircraft and automotive components. Both material and structural imperfections can be recognized as typical fringe patterns in the shearogram. However, a reliable fault detection requires a detectable fault response to the applied load at the surface and a sufficient quality of the fringe pattern as well. Therefore, the testing of large-scale technical objects having in general noncooperative surfaces needs a careful design of the following system components: the shearography sensor, the illumination unit, the loading system, and the evaluation software. We report a mobile shearography system that was especially designed for the inspection of aircraft and automotive parts under industrial boundary conditions. Several examples illustrate the efficiency of the system.

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“…These characteristics, coupled with the enhanced interferometric stability that is typical of common-path interferometers, make shearography a potentially valuable tool for industrial non-destructive testing (NDT). Shearography has demonstrated great potential in revealing defects in objects especially in detecting delamination in composite materials [9][10][11][12][13][14]. Furthermore, the technique is appropriate for the NDT analysis of artwork components [12,15].…”

Section: Introductionmentioning

confidence: 99%

Simple educational tool for digital speckle shearography

et al. 2012

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In this study, an educational tool has been prepared for obtaining short-term and more economic training on digital speckle shearography (DSS). Shearography non-destructive testing (NDT) has gained wide acceptance over the last decade, providing a number of important and exciting inspection solutions in aerospace, electronics and medical device manufacturing. For exploring these motivations, it is important to develop didactic tools to understand the potential of digital shearography through training and didactic courses in the field of NDT. In this paper we describe a simple tool for making one familiar with the potential of DSS in the area of education and training. The system is realized with a simple and economic optical setup and a virtual instrument based on the LabVIEW™ and DAQ.

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<title>Shearography system for the testing of large-scale aircraft components taking into account noncooperative surfaces</title>

Cited by 12 publications

References 0 publications

Looseness inspection of fasteners based on digital shearing speckle pattern interferometry and convolutional neural network

Looseness inspection of fasteners based on digital shearing speckle pattern interferometry and convolutional neural network

Mobile shearography system for the inspection of aircraft and automotive components

Simple educational tool for digital speckle shearography

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