• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1411-1417
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• 2015

The installation of PV system to the power distribution system is being increased as one of solutions for environmental pollution and energy crisis. However, the efficiency of PV system is getting decreased because of the aging phenomenon and several operation obstacles. Therefore, The technology development of aging diagnosis of PV modules are required in order to improve operation performance of PV modules. This paper proposes evaluation algorithm for aging state in PV modules by using the electrical characteristics of PV modules and environmental factors. And also, this paper presents a operation evaluation system of PV modules based on the proposed aging diagnosis algorithm of PV modules. From the simulation results of proposed evaluation system, it is confirmed that the proposed algorithm is a useful tool for aging diagnosis of PV systems.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.87-91
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• 2019

The diagnosis of the failure for the existing electrical facilities was based on regular preventive maintenance, but this preventive maintenance was limited in preventing a lot of cost loss and sudden system failure. To overcome these shortcomings, fault prediction and diagnostic techniques are critical to increasing system reliability by monitoring electrical installations in real time and detecting abnormal conditions in the facility early. As the performance and quality deterioration problem occurs frequently due to the increase in the number of users of the motor pump, the purpose is to build an intelligent control system that can control the motor pump to maximize the performance and to improve the quality and reliability. To this end, a vibration sensor, temperature sensor, pressure sensor, and low water level sensor are used to detect vibrations, temperatures, pressures, and low water levels that can occur in the motor pump, and to build a system that can identify and diagnose information to users in real time.

• Journal of the Korean Society of Safety
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• v.34 no.4
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• pp.59-67
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• 2019

Since it is really hard to construct process models based on prior process knowledges, various statistical approaches have been employed to build fault diagnosis models. However, the crucial drawback of these approaches is that the solutions may vary according to the fault magnitude, even if the same fault occurs. In this study, the parameter monitoring approach is suggested. When a fault occurs in a chemical process, this leads to trigger the change of a process model and the monitoring parameters of process models is able to provide the efficient fault diagnosis model. A few important variables are selected and their predictive models are constructed by partial least square (PLS) method. The Euclidean norms of parameters of PLS models are estimated and a fault diagnosis can be performed as comparing with parameters of PLS models based on normal operational conditions. To improve the monitoring performance, cumulative summation (CUSUM) control chart is employed and the changes of model parameters are recorded to identify the type of an unknown fault. To verify the efficacy of the proposed model, Tennessee Eastman (TE) process is tested and this model can be easily applied to other complex processes.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.32 no.3
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• pp.85-92
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• 2021

Attention-deficit/hyperactivity disorder (ADHD) leads to functional decline in academic performance, interpersonal relationships, and development in school-aged children. Early diagnosis and appropriate intervention can significantly reduce the functional decline caused by ADHD. Currently, there is no established biological marker for ADHD. Some studies have suggested that various indicators from the quantitative electroencephalogram (QEEG) may be useful biological markers for the diagnosis of ADHD. Until the 2010s, theta/beta ratio (TBR) was a biomarker candidate for ADHD that consistently showed high diagnostic value. However, limitations of TBR have recently been reported. Studies have demonstrated that phase-amplitude coupling, especially theta phase-gamma amplitude coupling, are related to cognitive dysfunction and may assist in the diagnosis of ADHD. As yet, the underlying mechanism is not clearly established, and the clinical efficacy of these biomarkers needs to be proven through well-controlled studies. Based on the heterogeneous characteristics of ADHD, subgrouping through QEEG plays a key role in diagnosis and treatment planning. Sophisticated, well-designed studies and meta-analyses are necessary to confirm these findings.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2134-2143
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• 2018

This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.

• Current Optics and Photonics
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• v.7 no.3
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• pp.283-296
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• 2023

An intraoral spectral domain optical coherence tomography (SD-OCT) system has been developed, using a custom-built hand-held scanner and spectrometer. The hand-held OCT probe, based on a microelectromechanical systems scanner and a self-built miniaturized drive circuit, had a field of view sufficient for dental diagnosis. The spectrometer using a fabricated f-theta lens provided the image depth required for dental diagnosis. The axial and transverse resolutions of the OCT system in air were 7.5 ㎛ and 12 ㎛ respectively. The hand-held probe could scan an area of 10 × 10 mm², and the spectrometer could image along a depth of 2.5 mm. To verify the utility of the developed OCT system, OCT images of tooth hard and soft tissues were acquired, and a user-interface program for diagnosis was developed. Early caries and microcracks that were difficult to diagnose with existing methods could be found, and the state of restoration could be observed. Measuring the depth of the gingival sulcus, distinguishing subgingival calculus, and detecting an implant under the gingiva suggested the possibility of the SD-OCT system as a diagnostic for dental soft tissues. Through the presented OCT images, the capability of the developed SD-OCT system for dental diagnosis was demonstrated.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2278-2288
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• 2017

Multilevel converter topologies are widely used in many applications. The cascaded H-bridge multilevel inverter (CHBMI), which is one of many multilevel converter topologies, has been introduced as a useful topology in high and medium power. However, it has a drawback to require a lot of switches. Therefore, the reliability of CHBMI is important factor for analyzing the performance. This paper presents a simple switch fault diagnosis method for single-phase CHBMI. There are two types of switch faults: open-fault and short-fault. In the open-fault, the body diode of faulty switch provides a freewheeling current path. However, when the short-fault occurs, the distortion of output current is different from that of the open-fault because it has an unavailable freewheeling current flow path due to a disconnection of fuse. The fault diagnosis method is based on the zero current time analysis according to zero-voltage switching states. Using the proposed method, it is possible to detect the location of faulty switch accurately. The PSIM simulation and experimental results show the effectiveness of proposed switch fault diagnosis method.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3383-3388
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• 2007

To compare the sensor performance of AE leak diagnosis system which can measure valve leak conditions, AE activities such as RMS voltage level, AE signal trend, leak rate degree according to AE database, FFT spectrum were measured on valve of the simulated test system for power plant. AE activities were recorded and analyzed from various operating conditions including different temperature, pressure difference, valve size and fluid using both piezoelectric acoustic emission sensor and Pb-Free acoustic emission sensor. The results of this study are utilized to select the type of sensors, the frequency band for filtering and thereby to improve the signal-to-noise ratio for diagnosis or monitoring of valves in operation. As the final result of application study above, portable type leak diagnosis system by AE was developed. The outcome of the study can be definitely applied as a means of the diagnosis or monitoring system for energy saving and prevention of accident for power plant valve.

• Journal of The Korea Institute of Healthcare Architecture
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• v.26 no.4
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• pp.29-38
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• 2020

Purpose: The first thing to be done in promoting community care is local diagnosis. Therefore, this study attempted to derive the physical infrastructure to be diagnosed, and to develop diagnostic items and diagnostic indicators applicable to this. Methods:: First, the physical infrastructure related to the community care is derived. And the diagnosis items are derived using the checklist of 'community support and health services' in the WHO Guide for Global age-friendly cities. Next, by analyzing previous studies, we develop diagnostic indicators for each diagnostic item and explore their applicability. Results: As a result of deriving the physical infrastructure for each area of housing, health service, and nursing care for community care, 22 facilities were derived for 9 types. Diagnosis items for the facilities are 1)regional equity, 2)proximity between facilities, 3)transportation access, 4)regional use, 5)barrier-free design, 6)diversity of facilities, and a total of 14 diagnostic indicators was derived. We reviewed and suggested the applicability of diagnostic items and indicators by each physical infrastructure. Implications: For the realization of community care, local diagnosis should not be limited to sim- ply grasping the presence or absence of facilities and the total amount. Instead it should strengthen capabilities by conducting diagnosis to understand the performance of facilities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5C
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• pp.483-489
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• 2006

Somani and Peleg proposed t/k-diagnosable system to diagonse more faults than t(dimension) by allowing upper bounded few number of units to be diagnosed incorrectly. Kranakis and Pelc showed that their adaptive diagnosis algorithm was more efficient than that of any previous ones, assuming that the number of faults does not exceed the hypercube dimension. We propose an adaptive diagnosis algorithm using the idea of t/k-diagnosable system on the basis of that of Kranakis and Pelc's. When the number of faults exceeds t, we allow a fault(k=1, 2, 3) to be diagnosed incorrectly. Based on this idea, we find that the performance of the proposed algorithm is nearly as efficient as any previously known strategies and detect above about double faults.