• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.388-394
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• 2021

The conventional microelectromechanical system (MEMS) process has been used to fabricate sensors with high costs and high-volume productions. Emerging 3D printing can utilize various materials and quickly fabricate a product using low-cost equipment rather than traditional manufacturing processes. 3D printing also can produce the sensor using various materials and design its sensing structure with freely optimized shapes. Hence, 3D printing is expected to be a new technology that can produce sensors on-site and respond to on-demand demand by combining it with open platform technology. Therefore, this paper reviews three standard 3D printing technologies, such as Fused Deposition Modeling (FDM), Direct Ink Writing (DIW), and Digital Light Processing (DLP), which can apply to the sensor fabrication process. The review focuses on strain/load sensors having both sensing material features and structural features as well. NCPC (Nano Carbon Piezoresistive Composite) is also introduced as a promising 3D material due to its favorable sensing characteristics.

• Composites Research
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• v.22 no.6
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• pp.1-6
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• 2009

This paper presents an experimental study on the piezoresistive behavior of nanocomposite strain sensors subjected to various loading modes and their capability to detect structural deformations and damages. The electrically conductive nanocomposites were fabricated in the form of a film using various types of thermoplastic polymers and multi-walled carbon nanotubes (MWNTs) at various loadings. In this study, the nanocomposite strain sensors were bonded to a substrate and subjected to tension, flexure, or compression. In tension and flexure, the resistivity change showed dependence on measurement direction, indicating that the sensors can be used for multi-directional strain sensing. In addition, the sensors exhibited a decreasing behavior in resistivity as the compressive load was applied, suggesting that they can be used for pressure sensing. This study demonstrates that the nanocomposite strain sensors can provide a pathway to affordable, effective, and versatile structural health monitoring.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.215-226
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• 2015

Normally, aero photography using UAV uses about 430 MHz bandwidth radio frequency (RF) modem and navigates and remotely controls through the connection between UAV and ground control system. When using the exhausting method, it has communication range of 1-2 km with frequent cross line and since wireless communication sends information using radio wave as a carrier, it has 10 mW of signal strength limitation which gave restraints on life my distance communication. The purpose of research is to use communication technologies such as long-term evolution (LTE) of smart camera, Bluetooth, Wi-Fi and other communication modules and cameras that can transfer data to design and develop automatic shooting system that acquires images to UAV at the necessary locations. We conclude that the android based UAV filming and communication module system can not only film images with just one smart camera but also connects UAV system and ground control system together and also able to obtain real-time 3D location information and 3D position information using UAV system, GPS, a gyroscope, an accelerometer, and magnetic measuring sensor which will allow us to use real-time position of the UAV and correction work through aerial triangulation.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.275-285
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• 2016

This study analyzes the accuracy of ortho imagery based on whether camera calibration performed or not, using an unmanned aerial vehicle which equipped smart camera. Photgrammetric UAV system application was developed and smart camera performed image triangulation, and then created image as ortho imagery. Image triangulation was performed depending on whether interior orientation (IO) parameters were considered or not, which determined at the camera calibration phase. As a result of the camera calibration, RMS error appeared 0.57 pixel, which is more accurate compared to the result of the previous study using non-metric camera. When IO parameters were considered in static experiment, the triangulation resulted in 2 pixel or less (RMSE), which is at least 200 % higher than when IO parameters were not considered. After generate ortho imagery, the accuracy is 89% higher when camera calibration are considered than when they are not considered. Therefore, smart camera has high potential to use as a payload for UAV system and is expected to be equipped on the current UAV system to function directly or indirectly.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.695-706
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• 2022

Medium and high-resolution optical satellites have proven their effectiveness in detecting wildfire areas. However, smoke plumes generated by wildfire scatter visible light incidents on the surface, thereby interrupting accurate monitoring of the area where wildfire occurs. Therefore, a technology to extract smoke in advance is required. Deep learning technology is expected to improve the accuracy of smoke extraction, but the lack of training datasets limits the application. However, for clouds, which have a similar property of scattering visible light, a large amount of training datasets has been accumulated. The purpose of this study is to develop a smoke extraction technique using deep learning, and the limits due to the lack of datasets were overcome by using a cloud dataset on transfer learning. To check the effectiveness of transfer learning, a small-scale smoke extraction training set was made, and the smoke extraction performance was compared before and after applying transfer learning using a public cloud dataset. As a result, not only the performance in the visible light wavelength band was enhanced but also in the near infrared (NIR) and short-wave infrared (SWIR). Through the results of this study, it is expected that the lack of datasets, which is a critical limit for using deep learning on smoke extraction, can be solved, and therefore, through the advancement of smoke extraction technology, it will be possible to present an advantage in monitoring wildfires.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.05a
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• pp.250-253
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• 2001

Recently, based on the smart structure concept, optical fiber sensors have been increasingly applied to monitor the various engineering and civil structural components. Repairs based on adhesively bonded fiber reinforce composite patches are more structurally efficient and much less damaging to the parent structure than standard repairs based on mechanically fastened metallic patches. As a result of the high reinforcing efficiency of bonded patches fatigue cracks can be successfully repaired. However, when such repairs are applied to primary structures, it is needed to demonstrate that its loss can be immediately detected. This approach is based on the "smart patch" concept in which the patch system monitors its own health. The objective of this study is to evaluate the potentiality of application of transmission-type extrinsic Fabry-Perot optical fiber sensor (TEFPI) to the monitoring of crack growth behavior of composite patch repaired structures. The sensing system of TEFPI and the data reduction principle for the detection of crack detection are presented. Finally, experimental results from the tests of center-cracked-tension aluminum specimens repaired with bonded composite patch is presented and discussed.

• Journal of KSNVE
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• v.8 no.6
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• pp.1093-1102
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• 1998

The success of controllability of smart structures depends on the quality of the bonding along the interface between the main structure and the attached sensing and acuating elements. Generally, the analysis procedures neglect the effect of the interfacial bond layer or assume that this bond layer behaves like viscoelastic material. Three different bond layers. two modified epoxy adhesives, and one isocyanate adhesive were prepared for their toughness and moduli. Bond layer of the chosen adhesive provides an almost perfect bonding condition between the composite structure and the PZT while bended significantly like arrow-shape. The perfect bonding condition is tested by considering various material properties of the bond layers. and based on this perfect bonding condition, the effects of the interfacial bond layer on the dynamic behavior and controllability of the test structure is experimentally studied. Once the perfect bonding condition is achieved. dynamic effects of the bond layer itself on the dynamic characteristics of the main structure is negligible. but the contribution of the attached PZT elements on the stiffness of the multi-layered structure becomes significant when the thickness of the bond layer increased.

• Advances in nano research
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• v.9 no.2
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• pp.123-131
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• 2020

Conventional fabrics that have modified in to conductive fabrics using conductive nanomaterials have novel applications in different fields. These of fabrics can be used as heat generators with the help of the Joule heating mechanism, which is applicable in thermal therapy and to maintain the warmth in cold weather conditions in a wearable manner. A modified fabric can also be used as a sensor for body temperature measurements using the variation of resistance with respect to the body temperature deviations. In this study, polyol synthesized silver nanowires (Ag NWs) are incorporated to commercially available cotton fabrics by using drop casting method to modify the fabric as a thermogenic temperature sensor. The variation of sheet resistance of the fabrics with respect to the incorporated mass of Ag NWs was measured by four probe technique while the bulk resistance variation with respect to the temperature was measured using a standard ohm meter. Heat generation profiles of the fabrics were investigated using thermo graphic camera. Electrically conductive fabrics, fabricated by incorporating 30 mg of Ag NWs in 25 ㎠ area of cotton fabric can be heated up to a maximum steady state temperature of 45℃, using a commercially available 9 V battery.

• Smart Structures and Systems
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• v.13 no.4
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• pp.501-515
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• 2014

This paper presents a linear computational homogenization framework to evaluate the effective (or generalized) electromechanical coupling coefficient (EMCC) of adaptive structures with piezoelectric structural fiber (PSF) composite elements. The PSF consists of a silicon carbide (SiC) or carbon core fiber as reinforcement to a fragile piezo-ceramic shell. For the micro-scale analysis, a micromechanics model based on the variational asymptotic method for unit cell homogenization (VAMUCH) is used to evaluate the overall electromechanical properties of the PSF composites. At the macro-scale, a finite element (FE) analysis with the commercial FE code ABAQUS is performed to evaluate the effective EMCC for structures with the PSF composite patches. The EMCC is postprocessed from free-vibrations analysis under short-circuit (SC) and open-circuit (OC) electrodes of the patches. This linear two-scale computational framework may be useful for the optimal design of active structure multi-functional composites which can be used for multi-functional applications such as structural health monitoring, power harvest, vibration sensing and control, damping, and shape control through anisotropic actuation.