Thermal Imaging in Aviation

Aircraft leading edge is one of the most important subjects of aircraft scheduled maintenance. Leading edge as part of the slot on transport aircraft is not critical to fatigue stress in most of the cases. However, leading edge is extremely vulnerable to the accidental damage in combination with environmental damage. Maintenance is usually provided by visual inspection before every flight. Nevertheless, development of anti-icing system based on contact electrical heating opens possibility to thermographic Nondestructive Testing (NDT) methods usage. These methods could detect minor damages, which are visually undetectable especially in the case of composite materials. This paper describes possibility of thermographic methods (using anti-icing system) application as mean of leading edge minor damage detection.

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“…Infrared thermography is widely used NDT method. In aviation industry it is used for detection of structural defects [6,7].…”

Section: Thermographymentioning

confidence: 99%

Aircraft leading edges minor damages detection based on thermographic survey of electrical anti-icing system

Hlinka¹,

Koštial²,

Janhuba³

2019

13th Research and Education in Aircraft Design: Conference Proceedings

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“…At present, infrared imaging technology has been widely used in military [8][9][10], biomedical [11,12], industrial [13][14][15][16], environmental protection [10,17,18], and other fields [19,20]. Compared with visible imaging, infrared imaging is less affected by light problems due to the spontaneity of infrared radiation.…”

Section: Introductionmentioning

confidence: 99%

Mid-Infrared Sheep Segmentation in Highland Pastures Using Multi-Level Region Fusion OTSU Algorithm

et al. 2023

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In highland pastures, grazing is a common method for managing sheep due to the abundance of grassland resources. However, it is easy for sheep to encounter situations such as stray, deviation and attacks from natural enemies; therefore, the remote monitoring of sheep in the highland pastures is an urgent problem to be solved. This paper proposes a mid-infrared sheep segmentation method based on the multi-level region fusion maximum between-class variance algorithm, i.e., OTSU algorithm, for sheep surveillance. First, a mean adjustment OTSU algorithm is designed to better distinguish the interference areas in the background. Second, the Butterworth high-pass filter is combined with the mean adjustment OTSU segmentation algorithm to remove the high-brightness interference areas in the background with slow gray intensity changes. Finally, after filtering out the large area background and small stray point, the two processed results above are fused with the AND logical operation to obtain a final segmentation result. Our algorithm is evaluated using three objective evaluation indicators: the root mean square error (RMSE), structural similarity index metric (SSIM), and peak signal to noise ratio (PSNR). The RMSE, SSIM, PSNR of highland wetland image are 0.43187, 0.99526, and 29.16353. The RMSE, SSIM, PSNR of sandy land image are 0.87472, 0.98388, and 23.87430. The RMSE, SSIM, PSNR of grassland image are 0.65307, 0.99437, and 30.33159. The results show that our algorithm can meet the requirements for the mid-infrared sheep segmentation in highland pastures.

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“…The advanced computer integrated indoor inspection drone launched by Airbus in April 2018 [7], for aircraft visual inspection to reduce inspection times and enhance report quality is such a pioneer industrial robot for inspection. Unlike a visual inspection, for thermography, throughout the inspection duration, stable positioning is a requirement [8], which is difficult to achieve by controlling a drone at a fixed location. Thus, a wall-climbing robot that could firmly hold its position is more feasible for a thermography inspection process.…”

Section: Introductionmentioning

confidence: 99%

A Robotic Platform for Aircraft Composite Structure Inspection Using Thermography

et al. 2022

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Water ingression is a critical issue in honeycomb composite structures, which could result in catastrophic structural failure. In the aviation industry, they are widely used to manufacture critical aircraft structural components including fuselage, wings, and flight control surfaces. Catastrophic failure of these structures would be disastrous, thus identifying water accumulation in earlier stages of the defect is necessary. The conventional non-destructive testing method is thermography which is performed using handheld thermography cameras by manually accessing the specific areas. This method of inspection has been identified to be a risky, costly, time-consuming, and inspector-dependent technique. This paper describes using a wall-climbing robotic platform that can be controlled remotely to access and perform the inspection on a targeted structural area replacing the manual process. The designed wall-climbing inspection robot onboard a heat pump to stimulate the composite surface to an adequate temperature and, an infrared sensor to feed the real-time temperature data via Bluetooth serial communication to a remote computer system to be processed into a thermal image and evaluated to determine the presence of water. The results obtained from the thermographic sensor are validated with the comparison of the Fluke thermography camera.

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Thermal Imaging in Aviation

Cited by 9 publications

References 2 publications

Aircraft leading edges minor damages detection based on thermographic survey of electrical anti-icing system

Aircraft leading edges minor damages detection based on thermographic survey of electrical anti-icing system

Mid-Infrared Sheep Segmentation in Highland Pastures Using Multi-Level Region Fusion OTSU Algorithm

A Robotic Platform for Aircraft Composite Structure Inspection Using Thermography

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