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Boheng Yang,Hui Qian,Yonglin Ren,Rende Wang 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.2
Structural health monitoring and structural vibration control are multidisciplinary and frontier research directions of civil engineering. As intelligent materials that integrate sensing and actuation capabilities, shape memory alloys (SMAs) exhibit multiple excellent characteristics, such as shape memory effect, superelasticity, corrosion resistance, fatigue resistance, and high energy density. Moreover, SMAs possess excellent resistance sensing properties and large deformation ability. Superfine NiTi SMA wires have potential applications in structural health monitoring and micro-drive system. In this study, the mechanical properties and electrical resistance sensing characteristics of superfine NiTi SMA wires were experimentally investigated. The mechanical parameters such as residual strain, hysteretic energy, secant stiffness, and equivalent damping ratio were analyzed at different training strain amplitudes and numbers of loading.unloading cycles. The results demonstrate that the detwinning process shortened with increasing training amplitude, while austenitic mechanical properties were not affected. In addition, superfine SMA wires showed good strain.resistance linear correlation, and the loading rate had little effect on their mechanical properties and electrical resistance sensing characteristics. This study aims to provide an experimental basis for the application of superfine SMA wires in engineering.
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A Sobel Operator Combined with Patch Statistics Algorithm for Fabric Defect Detection
( Jiein Jiang ),( Zilong Jin ),( Boheng Wang ),( Li Ma ),( Yan Cui ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.2
In the production of industrial fabric, it needs automatic real-time system to detect defects on the fabric for assuring the defect-free products flow to the market. At present, many visual-based methods are designed for detecting the fabric defects, but they usually lead to high false alarm. Base on this reason, we propose a Sobel operator combined with patch statistics (SOPS) algorithm for defects detection. First, we describe the defect detection model. mean filter is applied to preprocess the acquired image. Then, Sobel operator (SO) is applied to deal with the defect image, and we can get a coarse binary image. Finally, the binary image can be divided into many patches. For a given patch, a threshold is used to decide whether the patch is defect-free or not. Finally, a new image will be reconstructed, and we did a loop for the reconstructed image to suppress defects noise. Experiments show that the proposed SOPS algorithm is effective.
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