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RISS 인기검색어
- 검색키워드
- 저자 : Rahim Gorgin (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Baseline-free damage imaging technique for Lamb wave based structural health monitoring systems
Rahim Gorgin,Ziping Wang 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.28 No.5
In Lamb wave based structural health monitoring (SHM) systems, damage scatter signals are usually used for damage identification. Such scatters are obtained by subtracting the current signal from a baseline. However, changes in the environmental condition, particularly temperature, make false scatters in the damage scatter signal. This affects the overall efficiently of the system. To overcome this obstacle, this study proposes a baseline-free damage identification technique. A dual-PZT actuation scheme is applied to generate a comparatively pure A0 mode. A wave velocity determination procedure is then developed to actively determine the velocity of the generated A0 mode in the presence of unmeasured temperature changes. Using a damage scatter separation process, the damage scatter wave is separated from other waves appear in the current signal. Finally, a damage diagnostic image is constructed to illustrate the most probable location of damage. The experimental validation of the developed technique is conducted on two aluminum plates one carrying an L shape crack and the other carrying a hole, subjected to temperatures changes. The experimental results demonstrate the effectiveness of the developed technique for damage identification in the presence of unmeasured temperature. During the proposed procedure no baseline data is used. This bright advantage, qualify the presented technique for practical SHM systems.
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Impact localization method for composite structures subjected to temperature fluctuations
Rahim Gorgin,Ziping Wang 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.4
A novel impact localization method is presented based on impact induced elastic waves in sensorized composite structure subjected to temperature fluctuations. In real practices, environmental and operational conditions influence the acquired signals and consequently make the feature (particularly Time of Arrival (TOA)) extraction process, complicated and troublesome. To overcome this complication, a robust TOA estimation method is proposed based on the times in which the absolute amplitude of the signal reaches to a specific amplitude value. The presented method requires prior knowledge about the normalized wave velocity in different directions of propagation. To this aim, a finite element model of the plate was built in ABAQUS/CAE. The impact location is then highlighted by calculating an error value at different points of the structure. The efficiency of the developed impact localization technique is experimentally evaluated by dropping steel balls with different energies on a carbon fiber composite plate with different temperatures. It is demonstrated that the developed technique is able to localize impacts with different energies even in the presence of noise and temperature fluctuations.
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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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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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