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Visual inspection and assessment of the condition of metal structures are essential for safety. Pulse thermography produces visible infrared images, which have been widely applied to detect and characterize defects in structures and materials. When active thermography, a non-destructive testing tool, is applied, the necessity of considerable manual checking can be avoided. However, detecting an internal crack with active thermography remains difficult, since it is usually invisible in the collected sequence of infrared images, which makes the automatic detection of internal cracks even harder. In addition, the detection of an internal crack can be hindered by a complicated inspection environment. With the purpose of putting forward a robust and automatic visual inspection method, a computer vision-based thresholding method is proposed. In this paper, the image signals are a sequence of infrared images collected from the experimental setup with a thermal camera and two flash lamps as stimulus. The contrast of pixels in each frame is enhanced by the Canny operator and then reconstructed by a triple-threshold system. Two features, mean value in the time domain and maximal amplitude in the frequency domain, are extracted from the reconstructed signal to help distinguish the crack pixels from others. Finally, a binary image indicating the location of the internal crack is generated by a K-means clustering method. The proposed procedure has been applied to an iron pipe, which contains two internal cracks and surface abrasion. Some improvements have been made for the computer vision-based automatic crack detection methods. In the future, the proposed method can be applied to realize the automatic detection of internal cracks from many infrared images for the industry.

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The interfacial debonding detection of multi-layered strengthened structures (i.e. carbon fiber reinforced polymer (CFRP) strengthened steel/concrete beams) has always been an important problem urgent to be solved. Fiber Bragg grating (FBG) sensor is limited to directly perceive the shear strain. How to monitor the interfacial bonding state based on optical fiber sensing technology thus attracts high attention. A smart CFRP-FBG composite has then been developed in this paper. The structural integrity of the composites has been non-destructively checked by ultrasonic testing technique. Theoretical study on the strengthened steel beam has been conducted to establish a relationship between the interfacial shear stress and the normal stress of the CFRP-FBG composites. Loading tests have been performed to check the measurement accuracy of the FBGs in series and the effectiveness of the composites to perceive the interfacial debonding failure. Results indicate that the proposed smart CFRP-FBG composites can accurately identify the interfacial debonding of the multi-layered structures. The degradation process of the interfacial bonding state can be favorably reflected by the variations of strain profiles measured by the FBGs in series in the composites. The proposed method can be used to instruct the concept design of damage detection. The developed CFRP-FBG composites can be adopted to identify the damage and make in-time maintenance in practical engineering.