scholarly journals Infrared Thermal Imaging-Based Crack Detection Using Deep Learning

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 182060-182077 ◽  
Author(s):  
Jun Yang ◽  
Wei Wang ◽  
Guang Lin ◽  
Qing Li ◽  
Yeqing Sun ◽  
...  
Keyword(s):  
Deep Learning ◽  
Thermal Imaging ◽  
Crack Detection ◽  
Infrared Thermal Imaging

scholarly journals Detection of Sick Laying Hens by Infrared Thermal Imaging and Deep Learning

2021 ◽  
Vol 2025 (1) ◽  
pp. 012008
Author(s):  
Pei Li ◽  
Huishan Lu ◽  
Fujie Wang ◽  
Shouyao Zhao ◽  
Ning Wang
Keyword(s):  
Deep Learning ◽  
Thermal Imaging ◽  
Laying Hens ◽  
Infrared Thermal Imaging

scholarly journals A Defect Detection Method for the Surface of Metal Materials Based on an Adaptive Ultrasound Pulse Excitation Device and Infrared Thermal Imaging Technology

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yibo Ai ◽  
Yingjie Zhang ◽  
Xingzhao Cao ◽  
Weidong Zhang
Keyword(s):  
Thermal Imaging ◽  
Crack Detection ◽  
Control Method ◽  
Three Dimensional ◽  
Resonance State ◽  
Ultrasonic Pulse ◽  
Operating Conditions ◽  
Pulse Excitation ◽  
Infrared Thermal Imaging ◽  
Imaging Technology

Ultrasonic excitation has been widely used in the detection of microcracks on metal surfaces, but there are problems such as poor excitation effect of ultrasonic pulse, long time to reach the best excitation, and difficult to find microcracks. In this paper, an adaptive ultrasonic pulse excitation device and infrared thermal imaging technology have been combined, as well as their control method, to solve the problem. The adaptive ultrasonic pulse excitation device adds intelligent modules to realize automatic adjustment of detection parameters, which can quickly obtain reliable excitation; the multidegree-of-freedom base realizes the three-dimensional direction change of the ultrasonic gun to adapt to different excitation occasions. When the appropriate ultrasonic excitation makes microcracks in the resonance state, the microcracks can be frictionated, which produce heat rise with the temperature. Then, the microcrack defect can be detected by the infrared thermal instrument through the different surface temperatures with imaging recognition method. Our detection experiments of the titanium alloy plates and the aluminum alloy profiles of marine engineering show that the method can get reliable detection parameters in a short time and measure the crack length effectively. It can be used in many aspects such as crack detection in mechanical structures or complex equipment operating conditions and industrial production processes.

Infrared thermal imaging denoising method based on second-order channel attention mechanism

2021 ◽  
pp. 103789
Author(s):  
Zhuo Li ◽  
Shaojuan Luo ◽  
Meiyun Chen ◽  
Heng Wu ◽  
Tao Wang ◽  
...  
Keyword(s):  
Thermal Imaging ◽  
Second Order ◽  
Attention Mechanism ◽  
Denoising Method ◽  
Infrared Thermal Imaging

Deep Learning based Thermal Crack Detection on Structural Concrete Exposed to Elevated Temperature

2021 ◽  
pp. 136943322098663
Author(s):  
Diana Andrushia A ◽  
Anand N ◽  
Eva Lubloy ◽  
Prince Arulraj G
Keyword(s):  
Deep Learning ◽  
Crack Detection ◽  
Detection Method ◽  
Concrete Structures ◽  
Vital Role ◽  
Subjective Knowledge ◽  
Thermal Cracks ◽  
Reinforced Cement ◽  
Novel Method ◽  
Human Inspection

Health monitoring of concrete including, detecting defects such as cracking, spalling on fire affected concrete structures plays a vital role in the maintenance of reinforced cement concrete structures. However, this process mostly uses human inspection and relies on subjective knowledge of the inspectors. To overcome this limitation, a deep learning based automatic crack detection method is proposed. Deep learning is a vibrant strategy under computer vision field. The proposed method consists of U-Net architecture with an encoder and decoder framework. It performs pixel wise classification to detect the thermal cracks accurately. Binary Cross Entropy (BCA) based loss function is selected as the evaluation function. Trained U-Net is capable of detecting major thermal cracks and minor thermal cracks under various heating durations. The proposed, U-Net crack detection is a novel method which can be used to detect the thermal cracks developed on fire exposed concrete structures. The proposed method is compared with the other state-of-the-art methods and found to be accurate with 78.12% Intersection over Union (IoU).

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