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RISS 인기검색어
- 검색키워드
- 저자 : Dongyue Wu (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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The Development and Experimental Test of a New Pore-forming Grouted Precast Shear Wall Connector
Dongyue Wu,Shuting Liang,Zhenxing Guo,Xiaojun Zhu,Qian Fu 대한토목학회 2016 KSCE JOURNAL OF CIVIL ENGINEERING Vol.20 No.4
Pore-forming grouted connection characterized with great economic superiorities and application potentials has weaker mechanical properties comparing to the steel sleeve grouted connector. To improve the mechanical properties of pore-forming grouted connector, the NPGCS was generated using welded closure confinement steels in buckle configuration. Experimental tests and finial element analysis of two NPGCS precast shear wall specimens and one cast-in-situ shear wall specimen was carried out to test mechanical performances. Results indicated that the mechanical properties of NPGCS can match the connection requirements even under the adverse effects from grouted interface gap opening and slip. Contributing to the excessive confinement steels, the mechanical properties of NPGCS specimens are better than that of the cast-in-situ specimen. So, according to the suggestions given out in this paper, the NPGCS can be widely applied into precast buildings in certain areas and conditions.
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Optimizations of Canny Edge Detection in Ghost Imaging
Guohua Wu,Dongyue Yang,Chen Chang,Longfei Yin,Bin Luo,Hong Guo 한국물리학회 2019 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.75 No.3
An optimization of the Canny edge detector’s application in ghost imaging is presented. Based on the pseudo-thermal light ghost imaging scheme with a binary object, a thin and accurate edge map can be extracted by using a Gaussian-filtering-optimized Canny edge detector. The scale of the Gaussian filter in Canny edge detection algorithm is the dominate factor in the performance of the edge detector, and can be evaluated by the bit error rate of reconstructed binary image based on the edge map. Simulation results indicate the optimal window size of Gaussian filter for ghost imaging is proportional to the full width at half maximum of the self-correlation function in the idler arm samples without any priori knowledge of the object. Experimental results show that, with an appropriate Gaussian filter, the reconstructed binary image can approach the original binary object with the minimum bit error rate, which means the edge detection result is optimal.
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Probabilistic-based damage identification based on error functions with an autofocusing feature
Gorgin, Rahim,Ma, Yunlong,Wu, Zhanjun,Gao, Dongyue,Wang, Yishou Techno-Press 2015 Smart Structures and Systems, An International Jou Vol.15 No.4
This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.
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Probabilistic-based damage identification based on error functions with an autofocusing feature
Rahim Gorgin,Yunlong Ma,Zhanjun Wu,Dongyue Gao,Yishou Wang 국제구조공학회 2015 Smart Structures and Systems, An International Jou Vol.15 No.4
This study presents probabilistic-based damage identification technique for highlightingdamage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate andmonitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define thescatter signals of different paths. The energy of scatter signals till different times were calculated by takingroot mean square of the scatter signals. For each pair of parallel paths an error function based on the energyof scatter signals is introduced. The resultant error function then is used to estimate the probability of thepresence of damage in the monitoring area. The presented method with an autofocusing feature is applied toaluminum plates for method verification. The results identified using both simulation and experimentalLamb wave signals at different central frequencies agreed well with the actual situations, demonstrating thepotential of the presented algorithm for identification of damage in metallic structures. An obvious merit ofthe presented technique is that in addition to damages located inside the region between transducers; thosewho are outside this region can also be monitored without any interpretation of signals. This noveltyqualifies this method for online structural health monitoring.
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