• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.7-12
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• 2019

Significant progress has been made recently in detection of highly sensitive volatile organic compounds (VOCs) using chemical sensors. Combined with the progress in design of micro sensors array and electronic nose systems, these advances enable new applications for detection of extremely low concentrations of breath-related VOCs. State of the art detection technology in turn enables commercial sensor systems for health care applications, with high detection sensitivity and small size, weight and power consumption characteristics. We have been developing an intelligent electronic nose system for detection of VOCs for healthcare breath analysis applications. This paper reviews our contribution to monitoring of respiratory diseases and to diabetic monitoring using an intelligent electronic nose system for detection of low concentration VOCs using breath analysis techniques.

• Journal of Power Electronics
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• v.16 no.2
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• pp.760-768
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• 2016

Three-phase grid-connected inverters are widely applied in the fields of new energy power generation, electric vehicles and so on. Islanding detection is necessary to ensure the stability and safety of such systems. In this paper, feature recognition technology is applied and a novel islanding detection method is proposed. It can identify the features of inverter systems. The theoretical values of these features are defined as codebooks. The difference between the actual value of a feature and the codebook is defined as the quantizing distortion. When islanding happens, the sum of the quantizing distortions exceeds the threshold value. Thus, islanding can be detected. The non-detection zone can be avoided by choosing reasonable features. To accelerate the speed of detection and to avoid miscalculation, an active islanding detection method based on feature recognition technology is given. Compared to the active frequency or phase drift methods, the proposed active method can reduce the distortion of grid-current when the inverter works normally. The principles of the islanding detection method based on the feature recognition technology and the improved active method are both analyzed in detail. An 18 kVA DSP-based three-phase inverter with the SVPWM control strategy has been established and tested. Simulation and experimental results verify the theoretical analysis.

• Journal of Power System Engineering
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• v.19 no.2
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• pp.33-39
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• 2015

In conducting indoor positioning by code division multiple access using spread spectrum ultrasonic waves, it is required to detect signals under the influence of near-far problem occurred by difference on signal power, caused by distance between transmitter and receiver. For discussing robustness to the problem, we verified measuring accuracy on distance from an experiment on a real space with a hardware device where our proposed method is mounted. The proposed method performs automatic signal detection by setting threshold level dynamically. As an experimental result, measurable distance were improved by the proposed method, and measurement errors were up to 50mm in distances from 1000mm to 6000mm; therefore, enough accuracy to realize self-localization or navigation for autonomous mobile robot or human was obtained.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1655-1657
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• 2002

Ultra-wide bandwidth (UWB), narrow bandwidth (single frequency), and a combination of both technologies have been studied for the ultra-high frequency (UHF) partial discharge (PD) monitoring system as a detection scheme. We have experimentally compared those detection methods using a mock-up of 362 kV class single phase gas-insulated switchgear (GIS) and a stable PD source. A rolling-ball type PD cell that produces PDs of about 10 pC, is placed at one end of the GIS. An internal UHF PD sensor was attached several meters away from the PD source. The PD spectrum was measured up to 3 GHz. A useable bandwidth of more than 1 GHz was used to measure UWB signals from the PD. To simulate the narrow bandwidth scheme a bandwidth of 100 kHz centered at several different frequencies was used.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.3
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• pp.296-301
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• 2005

This paper proposing the use of the Instantaneous reactive power method as a harmonic detection method for a single phase active filter system. This method is to detect harmonic components through d-q frame approach. The conventional use of d-q frame approach for a 3-phase system Is extended to the single phase system. The proposed system uses a multi-level inverter for harmonic compensation and the inverter is connected to the input side without using transformers. The proposed algorithm is verified by simulation and experiment.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.461-462
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• 2007

DC Arc is an electric discharge which is occurred in two oppolsite electrode when system operating with DC current appliance. In this paper, DC arc detection system is designed for the display of DC arc fault current which is occurred in the local electric network with DC Power. This DC arc is one of the main causes of electric fire of dc system. Arc fault in electrical network has the characteristics of low current, high impedance and low frequency. DC Arc current detection device is designed for the display of arc fault current which has the modified arc characteristics.

• Journal of Power Electronics
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• v.10 no.6
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• pp.686-693
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• 2010

In this paper, a fault diagnosis method based on fuzzy logic for the three-parallel power converter in a wind turbine system is presented. The method can not only detect both open and short faults but can also identify faulty switching devices without additional voltage sensors or an analysis modeling of the system. The location of a faulty switch can be indicated by six-patterns of a stator current vector and the fault switching device detection is achieved by analyzing the current vector. A fault tolerant algorithm is also presented to maintain proper performance under faulty conditions. The reliability of the proposed fault detection technique has been proven by simulations and experiments with a 10kW simulator.

• Journal of Power Electronics
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• v.10 no.3
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• pp.300-305
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• 2010

This paper presents a two Hall sensor method for rotor angle detection in permanent magnet synchronous motors (PMSM). To minimize the implementation complexity, the system is designed to measure the edge field of permanent magnet pieces. However, there are nonlinearities in the measured values of the edge field. In this work, an angle correction algorithm is proposed, and the improvements in accuracy are verified through experiments. Finally, a field orientation controller is constructed with the proposed angle detection algorithm.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.107-109
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• 2003

This paper studies islanding detection distributed of distributed generation(DG). The study of islanding detection has been disconnected DG when power islanding was detected but fault type wasn't distingish. Nearby feeder fault the fault of feeder that not interconnected DG, is a little affect DG and distribution system. Therefore DG not need to disconnect distribution system. We studied islanding detection algorithm considering fault location.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.2
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• pp.63-66
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• 2005

This paper describes analysis and pattern recognition techniques for Partial Discharge(PD) signals in Gas Insulated Switchgears (GIS). Detection of PD signals is one of the most important factors in the predictive maintenance of GIS. One of the methods of detection is electro magnetic wave detection within the Ultra High Frequency (UHF) band (300MHz $\~$ 3GHz). In this paper, PD activity simulation is generated using three types of artificial defects, which were detected by a UHF PD sensor installed in the GIS. The detected PD signals were performed on three-dimensional phi-q-n analysis. Finally, parameters were calculated and an Artificial Neural Network (ANN) was applied for PD pattern recognition. As a result, it was possible to discriminate and classify the defects.