• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.24-30
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• 2022

Distributed fiber-optic acoustic·vibration sensing technology is becoming increasingly popular in many industrial and academic areas such as in securing large edifices, exploring underground seismic activity, monitoring oil well/reservoir, etc. Long-range perimeter intrusion detection exemplifies an application that not only detects intrusion, but also pinpoints where it happens and recognizes kinds of threats made along the perimeter where a single fiber cable was installed. In this study, we developed a distributed fiber-optic sensing device that measures a distributed acoustic·vibration signature (pattern) for intrusion detection. In addition, we demontrate the proposed deep learning algorithm and how it classifies various intrusion events. We evaluated the sensing device and deep learning algorithm in a practical testbed setup. The evaluation results confirm that the developed system is a promising intrusion detection system for long-distance and seamless recognition requirements.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.2891-2898
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• 2000

The objective of this paper is to develop a fiber-optic acoustic emission(AE) sensor applicable to on-line monitoring systems which is suitable for long-distance signal transmission. An AE sensor was developed by use of a fiber-optic cantilever and an extrinsic Fabry-Perot interferometer(EEPI). The efficiency of signal processing was improved by driving the high frequency AE signals into the low frequency ones. In order to verify the developed sensor, the tensile and the pencil lead fracture(PLF) tests were performed including the experiment showing the Kaiser effect. Form tests, AE signals were successfully detected in the elastic-plastic deformation range, especially higher signals at the crack propagation. The developed sensor was expected to be used for an on-line monitoring of crack propagation in mechanical system.

• Journal of KSNVE
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• v.7 no.6
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• pp.931-936
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• 1997

Optical fiber sensor is a subject which has been attracted considerable attention in recent years. Detection of sound pressure with optical fibers positioned in the arms of a Mach-Zehnder interferometer is presented in this paper. A fiber length of the order of 150m is wounded is made by hollow cylinder type. To increase the sound signal 3${\times}3$ directional coupler is used. Fiber optic hydrophone is the underwater tank with 2kHz sound source. Finally, it is shown that the fiber optic hydeophone can stably detec 2kHz sound.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.626-633
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• 2012

In this paper, sound pressure sensitivity of the fiber optic acoustic sensor according to sensor direction and mandrel material were investigated experimentally. Three different directions were selected as stand, lay, and hole. Hollow cylinder type mandrel dimension is 30 mm in outer diameter, 45 mm in length, and 2 mm in thickness, and about 50 m optical fibers were wounded on the surface of the mandrel. Non-directional sound speaker was used as a sound source. Sagnac interferometer and single mode fiber, a laser with 1,550 nm in wavelength, $2{\times}2$ coupler were used. Based on the experimental results, lay direction's sensitivity is the highest in the frequency range of 2 kHz~4 kHz. 'PTFE+carbon' material is more sensitive than PTFE in the frequency range of 5 kHz~20 kHz. Sound pressure detection sensitivity depends on the mandrel direction and material under certain frequency.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.495-501
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• 2014

Piezoresistive-type, capacitive-type, and optical-type sensors have mainly been used for measuring a strain. However, in building a sensor network for remote monitoring using these conventional sensors there are disadvantages such as the complexity of a measuring system including wireless communication circuitry and high cost. In this paper, we demonstrates a highly-sensitive surface acoustic wave (SAW) strain sensor which is advantageous to harsh environments and wireless network. We designed and fabricated the SAW strain sensor. The SAW strain sensor attached on a specimen was tested with a tensile tester. The strain on the sensor surface was measured with a commercial strain gauge and compared with that obtained from strain analysis. The central frequency shift of the SAW sensor was measured with a network analyzer. The sensitivity of the SAW strain sensor is 134 $Hz/{\mu}{\varepsilon}$ which is high compared to previous results.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.5
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• pp.263-266
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• 2006

An optical microphone was developed using a dual-core multi-mode fiber block and a membrane type micromirror. The fiber block serves as a compact optical head, and the micromirror as a reflective diaphragm. The micromirror is designed to be suspended through a silicon bar connected t a frame, allowing for displacement induced by acoustic waves. The optical head is implemented by integrating two multi-mode fibers in a single block, and used to transfer light signals between it and the diaphragm. For the assembled microphone, its static characteristics were observed to reveal the operating point defined as the optimum distance between the optical head and the diaphragm. And its dynamic response was tested to exhibit a frequency bandwidth of 3 kHz with the variation of $\sim5dB$.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.1-7
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• 2020

In this paper, we introduce the methodology that utilizes deep learning-based front-end to enhance underwater feature matching. Both optical camera and sonar are widely applicable sensors in underwater research, however, each sensor has its own weaknesses, such as light condition and turbidity for the optic camera, and noise for sonar. To overcome the problems, we proposed the opti-acoustic transformation method. Since feature detection in sonar image is challenging, we converted the sonar image to an optic style image. Maintaining the main contents in the sonar image, CNN-based style transfer method changed the style of the image that facilitates feature detection. Finally, we verified our result using cosine similarity comparison and feature matching against the original optic image.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.163-170
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• 1997

End milling experiments are conducted to investigate characteristics of acoustic emission (AE) and cutting force singals due to tool fracture. The AE signals are obtained with a sensor attached to cutting fluid discharge nozzle. Tool states are identified with scanning electron microscopy and optical microscopy. It is demonstrated that the AE signals provide reliable informations about the cutting processes and tool states. Morever, tool fracture can be detected successfully using both the AE count rate and the standard deviation of principal cutting force.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.135-141
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• 2016

Recently, the needs for the development and application of marine robots are increasing as marine accidents occur frequently. However, it is very difficult to acquire the information by utilizing marine robots in the marine environment. Therefore, the needs for the researches of sensor networks which are composed of underwater, surface and aerial robots are increasing in order to acquire the information effectively as the information from heterogeneous robots has less limitation in terms of coverage and connectivity. Although various researches of the sensor network which is based on marine robots have been executed, all of the underwater, surface and aerial robots have not yet been considered in the sensor network. To solve this problem, a collaborative control method based on the acoustic information and image by the sonars of the underwater robot, the acoustic information by the sonar of the surface robot and the optical image by the camera of the static-floating aerial robot is proposed. To verify the performance of the proposed method, the collaborative control of a MUR(Micro Underwater Robot) with an OAS(Obstacle Avoidance Sonar) and a SSS(Side Scan Sonar), a MSR(Micro Surface Robot) with an OAS and a BMAR(Balloon-based Micro Aerial Robot) with a camera are executed. The test results show the possibility of real applications and the need for additional studies.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.75-81
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• 2023

The significance of gas sensors has been emphasized in various industries and applications, owing to the growing significance of environmental, social, and governance (ESG) management in corporate operations. In particular, the monitoring of hazardous gas leakages and detection of fugitive emissions have recently garnered significant attention across several industrial sectors. As industrial workplaces evolve to ensure the safety of their working environments and reduce greenhouse gas emissions, the demand for high-performance gas sensors in industrial sectors dealing with toxic substances is on the rise. However, conventional gas-sensing systems have limitations in monitoring fugitive gas leakages at both critical and subcritical concentrations in complex environments. To overcome these difficulties, recent studies in the field of gas sensors have employed techniques such as mobile robotic olfaction, remote optical sensing, chemical grid sensing, and remote acoustic sensing. This review highlights the significant progress made in various technologies that have enabled accurate and real-time mapping of gas distribution and localization of hazardous gas sources. These recent advancements in gas-sensing technology have shed light on the future role of gas-detection systems in industrial safety.