• Advances in aircraft and spacecraft science
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• v.9 no.6
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• pp.525-536
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• 2022

The current state of telecommunications infrastructure in the Arctic does not allow providing a wide range of required services for people, businesses and other categories, which necessitates the use of non-traditional approaches to its organization. The paper proposes an innovative approach to building a combined communication network based on tethered high-altitude platform station (HAPS) located at an altitude of 1-7 km and connected via radio channels with terrestrial and satellite communication networks. Network configuration and composition of telecommunication equipment placed on HAPS and located on the terrestrial and satellite segment of the network was justified. The availability of modern equipment and the distributed structure of such an integrated network will allow, unlike existing networks (Iridium, Gonets, etc.), to organize personal mobile communications, data transmission and broadband Internet up to 100 Mbps access for mobile and fixed subscribers, rapid transmission of information from Internet of Things (IoT) sensors and unmanned aerial vehicles (UAV). A substantiation of the possibility of achieving high network capacity in various paths is presented: inter-platform radio links, subscriber radio links, HAPS feeder lines - terrestrial network gateway, HAPS radio links - satellite retransmitter (SR), etc. The economic efficiency of the proposed solution is assessed.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.118-123
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• 2023

This study presents sensor system for autonomous mobile robot capable of floor-to-floor self-navigation. The robot was modified using the Turtlebot3 hardware platform and ROS2 (robot operating system 2). The robot utilized the Navigation2 package to estimate and calibrate the moving path acquiring a map with SLAM (simultaneous localization and mapping). For elevator boarding, ultrasonic sensor data and threshold distance are compared to determine whether the elevator door is open. The current floor information of the elevator is determined using image processing results of the ceiling-fixed camera capturing the elevator LCD (liquid crystal display)/LED (light emitting diode). To realize seamless communication at any spot in the building, the LoRa (long-range) communication module was installed on the self-navigating autonomous mobile robot to support the robot in deciding if the elevator door is open, when to get off the elevator, and how to reach at the destination.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.8
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• pp.112-119
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• 1996

Among the various type of accelerometer, the servo rebalancing type accelermoter can be suitable for Inertial Navigation System, because of its high sensitivity and good response in low frequency. In this paper, we proposed a new technology to control inductive tuype accelerometer utilizing digital PWM method. The new developed digital PWM control has special design scheme for transmitting measurement value to outer device in its servo ollp. So it has no quantized error of transforming outputs of sensors to digital domain. The quantized error may make serious problem in INS system, because outputs of sensor are integrated once or twice by digital computer and it happens every sensor reading times. Therefore, in order to get the accurate information such as displacement, it is necessary to measure accurately the input current. In addition, Digital Signal Processing needs digital data transmission, digital PWM method is adaptive for this purpose. We realized a practical circuit for digital PWM control, analyzed the stability of the circuit, and designed the controller etc. In this study, we solved many practical problem for this application, and got out good results.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.183-183
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• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.205-207
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• 2021

The way to develop an IoT device is to mount the sensor required by the application on a platform such as Arduino or Raspberry Pi, and write the sensor driver and application. At this time, if the driving driver for the sensor has already been written and the application can access the driver as a standardized API, then Plug&Play of the sensor will be possible. The old way to do this is because the sensor interface is too complicated to use on the current platform. In this paper, when a standardized sensor and driver with a USB terminal are plugged into the Raspberry Pi, we propose a method for automatically installing the driver. Application developers can get sensor values through Linux's file access API without worrying about sensor drivers. The proposed technique is currently being implemented on Raspberry-Pi.

• Journal of Sensor Science and Technology
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• v.31 no.3
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• pp.151-155
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• 2022

In this paper, we present a highly-sensitive gate/body-tied (GBT) metal-oxide semiconductor field-effect transistor (MOSFET)-type photodetector using multi-finger structure whose photocurrent increases in proportion to the number of fingers. The drain current that flows through a MOSFET using multi-finger structure is proportional to the number of fingers. This study intends to confirm that the photocurrent of a GBT MOSFET-type photodetector that uses the proposed multi-finger structure is larger than the photocurrent per unit area of the existing GBT MOSFET-type photodetectors. Analysis and measurement of a GBT MOSFET-type photodetector that utilizes a multi-finger structure confirmed that photocurrent increases in ratio to the number of fingers. In addition, the characteristics of the photocurrent in relation to the optical power were measured. In order to determine the influence of the incident the wavelength of light, the photocurrent was recorded as the incident the wavelength of light varied over a range of 405 to 980 nm. A highly-sensitive GBT MOSFET-type photodetector with multi-finger structure was designed and fabricated by using the Taiwan semiconductor manufacturing company (TSMC) complementary metal-oxide-semiconductor (CMOS) 0.18 um 1-poly 6-metal process and its characteristics have been measured.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.412-417
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• 2023

There is increasing interest in the rapid and highly sensitive monitoring of cell viability in biological and toxicological research. Conventional methods depend on optical assays using Water Soluble Tetrazolium-8 (WST-8) or 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) assay, which requires a large volume of samples and special instruments, necessitating shipment of clinical samples to laboratories. This paper reports on the development of a rapid and sensitive electrochemical (EC) sensor using screen printed electrode (SPE) and surface modification using 4'-mercapto-N-phenylquinone diamine (4'-NPQD), as double electron mediators, for monitoring cell viability via the measurement of nicotinamide adenine dinucleotide (NADH). We used the sensor to observe the viability of MCF-7 and doxorubicin (Dox)-treated cells. The oxidation current of NADH was measured via chronoamperometry (CA), and the EC results showed a good linear relationship when compared with NADH quantification using WST-8 assay. The analysis time was only 10 s and limit of detection (LOD) of NADH was 1.78 µM. Our EC method has the potential to replace conventional WST assays for cell viability and cytotoxicity experiments.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.455-461
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• 2023

We investigated the electrical characteristics of ZnO nanoparticles (NPs) with air exposure that is a widely used electron transport layer for quantum dot light-emitting diodes (QLEDs). Upon air exposure, we observed changes in the density of states (DOS) of the trap levels of ZnO NPs. In particular, with air exposure, the concentration of deep trap energy levels in ZnO NPs decreased and electron mobility significantly improved. Consequently, the air-exposed ZnO reduced leakage current by approximately one order of magnitude and enhanced the external quantum efficiency at the low driving voltage region of the QLED. In addition, based on the excellent conductivity properties, high-brightness QLEDs could be achieved.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.21-27
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• 2023

This paper discusses a deep learning-based road surface analysis system that collects data by installing vibration sensors on the 4-axis wheel bearings of a vehicle, analyzes the data, and appropriately classifies the characteristics of the current driving road surface for use in the vehicle's control system. The data used for road surface analysis is real-time large-capacity data, with 48K samples per second, and the A2B protocol, which is used for large-capacity real-time data communication in modern vehicles, was used to collect the data. CAN and CAN-FD commonly used in vehicle communication, are unable to perform real-time road surface analysis due to bandwidth limitations. By using A2B communication, data was collected at a maximum bandwidth for real-time analysis, requiring a minimum of 24K samples/sec for evaluation. Based on the data collected for real-time analysis, performance was assessed using deep learning models such as LSTM, GRU, and RNN. The results showed similar road surface classification performance across all models. It was also observed that the quality of data used during the training process had an impact on the performance of each model.