• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.571-576
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• 2002

This paper is to develop jumping ring system with three sensor arrays and to control levitated ring using dynamic neural mode. Placing an aluminum ring on the core and switching on an AC source causes the ring to jump in the air due to induced currents. The educational system is composed of 40th optical sensor array, encode circuit, 89C51 microprocessor and control board. The control board consists of power IC, and phase controller. Real time process is present to obtain a height of levitated ring for three different sensor arrays. Based on the educational system and the proposed dynamic neural mode, the height of levitation of the ring is controlled by reference signals. This paper focuses on real system controls using the dynamic neural mode with on line learning algorithm.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.403-409
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• 2016

Traditional towed line arrays using omni-directional sensor suffer from the well known port-starboard ambiguity, because the direction of arrival is determined by conic angle. The operational method and structure of the sensor arrays method have been proposed to solve this problem. Recently, a lot of research relating to the acoustic vector sensor are studied. In this paper, we study port-starboard discrimination for roll of acoustic vector sensor array. With one omni-directional sensor and three orthogonally-placed directional sensors, an acoustic vector sensor is able to measure both the acoustic pressure and the three directional velocities at the point of the sensor. The wrong axis due to the roll at directional sensors can degrade performance of beamforming. We investigate port-starboard discrimination for roll of sensor array and confirm the validity of performance of beamforming with compensated the roll.

• Journal of Sensor Science and Technology
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• v.25 no.1
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• pp.13-19
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• 2016

Nowadays, most major automobile manufacturers are very interested, and actively involved, in developing driver alcohol detection system for safety (DADSS) that serves to prevent driving under the influence. DADSS measures the blood alcohol concentration (BAC) from the driver's breath and limits the ignition of the engine of the vehicle if the BAC exceeds the reference value. In this study, to optimize the sensor array of the DADSS, we selected sensors by using three different methods, configured the sensor arrays, and then compared their performance. The Wilks' lambda, stepwise elimination and filter method (using a principal component) were used as the sensor selection methods [2,3]. We compared the performance of the arrays, by using the selectivity and sensitivity as criteria, and Sammon mapping for the analysis of the cluster type of each gas. The sensor array configured by using the stepwise elimination method exhibited the highest sensitivity and selectivity and yielded the best visual result after Sammon mapping.

• Journal of Sensor Science and Technology
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• v.23 no.2
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• pp.99-104
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• 2014

Sensor arrays based on chemical sensors produce multidimensional patterns of data that may be used discriminate between different chemicals. For the human observer, visualization of multidimensional data is difficult, since the eye and brain process visual information in two or three dimensions. To devise a simple means of data inspection from the response of sensor arrays, PCA (Principal Component Analysis) or Sammon's nonlinear mapping technique can be applied. The PCA, which is a well-known statistical method and widely used in data analysis, has disadvantages including data distortion and the axes for plotting the dimensionally reduced data have no physical meaning in terms of how different one cluster is from another. In this paper, we have investigated two techniques and proposed a combination technique of PCA and nonlinear Sammom mapping for visualization of multidimensional patterns to two dimensions using data sets from odor sensing system. We conclude the combination technique has shown more advantages comparing with the PCA and Sammon nonlinear technique individually.

• Journal of Sensor Science and Technology
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• v.20 no.4
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• pp.279-285
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• 2011

This study was carried out to apply chemical gas sensors for the identification of bad breath which is one of the important sensitive problem for the humans' daily life. Seven sensors, including five semiconductor sensors and two electrochemical sensors, were tested for the three panels three times in several conditions. The results showed that the reproducibility of sensors were generally good, and electrochemical sensors showed better reproducibility while semiconductor sensors showed better sensitivity. No rinsing before measurement showed relatively better results in terms of both sensitivity and reproducibility. Semiconductor gas sensors for hydrogen sulfide shows the highest sensitivity, and it was recommended to use the odor-free bag for the measurement of bad breath.

• Composites Research
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• v.20 no.6
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• pp.21-27
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• 2007

Low-velocity impact damage in a composite stiffened panel was detected using built-in piezoelectric active sensor arrays. Using these piezoelectric active sensors, various diagnostic signals were generated to propagate Lamb waves through the structure and the responses were picked up to detect changes in the structure's vibration signature due to the damage. Three algorithms - ADI(Active Damage Interrogation), TD RMS (Time Domain Root Mean Square) and STFT (Short Time Fourier Transform) - were examined to express the features of the signal changes as one damage index. From damage detecting tests, two impact induced delaminations were detected and the location was estimated with the algorithms and diagnostic signals.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.66-72
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• 2018

In this paper, we propose an adaptive beamforming algorithm of triplet arrays for active sonar systems. The proposed algorithm consists of three steps: matched filters, cardioid beamforming, and line array beamforming. First, we apply a matched filter of a transmitted pulse to received individual sensor signals and obtain filterd signals. Then, we perform the fast Fourier transform to the matched filter results, and make a cardioid beam for each triplet data, respectively. Finally, we apply an adaptive beamforming by assuming that the cardioid beams are input signals of a line array. Experimental results demonstrate that the proposed algorithm provides better performances than conventional algorithms.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.3985-3995
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• 2022

The emergence of new nanoscale technologies has imposed significant challenges to designing reliable electronic systems in radiation environments. A few types of radiation like Total Ionizing Dose (TID) can cause permanent damages on such nanoscale electronic devices, and current state-of-the-art technologies to tackle TID make use of expensive radiation-hardened devices. This paper focuses on a novel and different approach: using machine learning algorithms on consumer electronic level Field Programmable Gate Arrays (FPGAs) to tackle TID effects and monitor them to replace before they stop working. This condition has a research challenge to anticipate when the board results in a total failure due to TID effects. We observed internal measurements of FPGA boards under gamma radiation and used three different anomaly detection machine learning (ML) algorithms to detect anomalies in the sensor measurements in a gamma-radiated environment. The statistical results show a highly significant relationship between the gamma radiation exposure levels and the board measurements. Moreover, our anomaly detection results have shown that a One-Class SVM with Radial Basis Function Kernel has an average recall score of 0.95. Also, all anomalies can be detected before the boards are entirely inoperative, i.e. voltages drop to zero and confirmed with a sanity check.

• Smart Structures and Systems
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• v.5 no.6
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• pp.663-679
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• 2009

The use of Micro-Electro-Mechanical Systems (MEMS) accelerometers in geotechnical instrumentation is relatively new but on the rise. This paper describes a new MEMS-based system for in situ deformation and vibration monitoring. The system has been developed in an effort to combine recent advances in the miniaturization of sensors and electronics with an established wireless infrastructure for on-line geotechnical monitoring. The concept is based on triaxial MEMS accelerometer measurements of static acceleration (angles relative to gravity) and dynamic accelerations. The dynamic acceleration sensitivity range provides signals proportional to vibration during earthquakes or construction activities. This MEMS-based in-place inclinometer system utilizes the measurements to obtain three-dimensional (3D) ground acceleration and permanent deformation profiles up to a depth of one hundred meters. Each sensor array or group of arrays can be connected to a wireless earth station to enable real-time monitoring as well as remote sensor configuration. This paper provides a technical assessment of MEMS-based in-place inclinometer systems for geotechnical instrumentation applications by reviewing the sensor characteristics and providing small- and full-scale laboratory calibration tests. A description and validation of recorded field data from an instrumented unstable slope in California is also presented.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.57-61
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• 2021

A formation process of indium bump arrays on micro-pillar structures is proposed. The space to form indium bump on the narrow structures can be secured applying the benzocyclobutene (BCB) planarization and its etch-back process. We exhibit a detailed overview of the process steps involved in the fabrication of 320×256 hybrid camera sensor for short-wavelength infrared (SWIR) detection. The shear strength of the BCB, which has undergone the different processes, is extracted by quartz crystal microbalance measurement. The shear strength of the BCB is three orders of magnitude higher than that of the indium bump itself. The measured dark current distribution of the fabricated SWIR camera sensor indicates the suggested process of indium bumps can be useful for embodying highly sensitive infared camera sensors.