• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.7
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• pp.508-516
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• 2008

Fault detection and diagnosis(FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. An experimental study has been performed on fault detection and diagnosis method for a water chiller. Bayes classifier, which is one of classical pattern classifiers, is adopted in deciding whether fault occurred or not. Failure modes in this study include refrigerant leakage, decrease in mass flow rate of the chilled water and cooling water, and sensor error of the cooling water inlet temperature. It is possible to detect and diagnose faults in this study by adopting FDD algorithm using only four parameters(compressor outlet temperature, chilled water inlet temperature, cooling water outlet temperature and compressor power consumption). Refrigerant leakage failure is detected at 20% of refrigerant leakage. When mass flow rate of the chilled and cooling water decrease more than 8% or 12%, FDD algorithm can detect the faults. The deviation of temperature sensor over $0.6^{\circ}C$ can be detected as fault.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.89-96
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• 2018

When a fault occurs in a power system, the existing analytic models for the power system fault diagnosis could generate multiple solutions under the condition of one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or an alarm or alarms of these PRs and/or CBs failing. Therefore, this paper presents an improved analytic model addressing the above problem. It takes into account the interaction between the uncertainty involved with PR operation and CB tripping and the uncertainty of the alarm reception, which makes the analytic model more reasonable. In addition, the existing analytic models apply the penalty function method to deal with constraints, which is influenced by the artificial setting of the penalty factor. In order to avoid the penalty factor's effects, this paper transforms constraints into an objective function, and then puts forward an improved immune clonal multi-objective optimization algorithm to solve the optimal solution. Finally, the cases of the power system fault diagnosis are served for demonstrating the feasibility and efficiency of the proposed model and method.

• Proceedings of the KIEE Conference
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• 2004.05b
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• pp.132-135
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• 2004

In generally, compared with VHF band, electromagnetic waves of UHF band have a low influence for external noise. We can detect the real abnormality with several pC in GIS using UHF method. Recently, it has applied to use the external UHF sensor attached on spacer to GIS of existing substation. In this paper, we firstly described the technique of the partial discharge measurement using frequency analysis and phase analysis in UHF band. Secondly, we presented the results of sensitivity, the relationship of dBm-pC and diagnosis of the reason of PD source by phase analysis. And then, we report the diagnosis result of partial discharge on 800kV GIS in domestic substation. rge diagnosis of GIS.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.473-473
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• 2010

Plasma is widely used in various commercial etchers and chemical vapor deposition. Unfortunately, real-time plasma process monitoring is still difficult. Some methods of plasma diagnosis is improved, however, it is possible for real-time plasma diagnosis to use non-intrusive probe only. In this research, the object is to investigate the suitability of using impedance analysis and optical emission spectroscopy (OES) for real-time plasma process monitoring. It is assumed that plasma system is a equivalent circuit. Therefore, V-I probe is used for measuring impedance, which can be a new non-intrusive probe for plasma diagnosis. From impedance data, we tried to analyse physical properties of plasma. And OES, the other method of plasma diagnosis, is a typical non-intrusive probe for analyzing chemical properties. The amount of the OES data is typically large, so this poses a difficulty in extracting relevant information. To solve this problem, principal component analysis (PCA) can be used. For fundamental information, Ar plasma and $O_2$ plasma are used in this experiment. This method can be applied to real-time endpoint and fault detections.

• Archives of Orthopedic and Sports Physical Therapy
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• v.14 no.2
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• pp.109-115
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• 2018

Purpose: McKenzie is a widely-used and conventional clinical therapeutic exercise for patients with mechanical lower back pain. It is a well-designed assessment and classification system for the spine. Main issue: Patients with mechanical lower back pain are classified into one of three mechanical syndromes (posture, dysfunction, or derangement syndrome) by mechanical loading strategies. These methods evaluate symptomatic and mechanical responses during repeated end-range movement and sustained postures. The goal of McKenzie mechanical syndrome diagnosis is to determine directional preferences. Directional preference is a phenomenon of preference for posture or movement in one direction, which reduces or centralizes pain. However, in Korea, there is a lack of awareness of basic McKenzie mechanical syndromes diagnostic concepts. Koreans tend to think of the McKenzie method as a simple lumbar extension exercise. However, an accurate diagnosis of a mechanical syndrome must precede the application of McKenzie exercise. Conclusions: Thus, in this study, I present a classification method of McKenzie mechanical syndrome diagnosis and clinical characteristics of each mechanical syndrome.

• Research in Plant Disease
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• v.29 no.2
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• pp.130-136
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• 2023

Citrus melanoses caused by Diaporthe citri, has been one of the serious diseases in many citrus orchards of Jeju Island. To protect melanose in citrus farms, a fast and exact diagnosis method is necessary. In this study, diseased leaves and dieback twigs were collected from a total of 49 farms within March to April in 2022. A total of 465 fungal isolates were obtained from a total of 358 isolated plant samples. Among these fungal isolates, 40 representatives of D. citri isolates which were isolated from 22 twigs and 18 leaves on 23 farms were found based on cultural characteristics on potato dextrose agar and conidial morphology. Additionally, the molecular assay was carried out and compared with those by morphological diagnosis. All isolates were identified as D. citri by analyzing the sequences at the internal transcribed spacer (ITS) rDNA region using primers of ITS1/ITS4 or at β-tubulin using primer Btdcitri-F/R. Therefore, based on the present study, where the results of morphological identification of conidial type were consistent with DNA sequence analysis of certain gene, choosing a suitable method for a fast diagnosis of citrus melanose was suggested.

• KIEAE Journal
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• v.17 no.4
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• pp.41-48
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• 2017

Purpose : Currently, 25% of the domestic energy consumption structure is used as building energy, and more than 18% of this energy is consumed in the residential. Accordingly, various efforts and policies that can save energy of the building is being performed. The various researchers are conducting research to diagnose the thermal performance of existing buildings. This study is to apply in the field of precision thermal insulation performance diagnostic method for thermal performance analysis of existing detached house in Seoul, Gangreung, Gyeongju, Pohang. And this paper is analyzed quantitatively measure the existing detached house energy performance. Method: Research methodology analyzed the thermal performance over the Heat Flow Meter method by applying the measurement process and method by applying the criteria of ISO 9869-1 & ASTR method. In this study, the surface heat transfer coefficient was calibrated by applying indoor surface heat transfer resistance with reference to ISO 6946 standard. The measurement error rate between the HFM diagnosis method and the ASTR diagnosis method was reduced and the measurement reliability was obtained through measurement method error verification. Result : As a result of the study, the thermal performance vulnerable parts of the building were quantitatively analyzed, and presented for methods which can be improved capable of efficient energy use buildings.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.7
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• pp.75-83
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• 2007

IEC code based decision nile have been widely applied to detect incipient faults in power transformers. However, this method has a drawback to achieve the diagnosis with accuracy without experienced experts. In order to resolve this problem, we propose an artificial diagnosis algorithm to detect faults of power transformers using Self-Organizing Feature Map(SOM). The proposed method has two stages such as model construction and diagnostic procedure. First, faulty model is constructed by feature maps obtained by unsupervised learning for training data. And then, diagnosis is performed by compare feature map with it obtained for test data. Also the proposed method usぉms the possibility and degree of aging as well as the fault occurred in transformer by clustering and distance measure schemes. To demonstrate the validity of proposed method, various experiments are unformed and their results are presented.

• Journal of Power Electronics
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• v.17 no.1
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• pp.56-66
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• 2017

Fast and accurate fault detection is the primary step and one of the most important tasks in fault tolerant converters. In this paper, a fast and simple method is proposed to detect and diagnosis the faulty cell in a cascaded H-bridge multilevel inverter under a short circuit fault. In this method, the reference voltage is calculated using switching control pulses and DC-Link voltages. The comparison result of the output voltage and the reference voltage is used in conjunction with active cell pulses to detect the faulty cell. To achieve this goal, the cell which is active when the Fault signal turns to "0" is detected as the faulty cell. Furthermore, consideration of generating the active cell pulses is completely described. Since the main advantage of this method is its simplicity, it can be easily implemented in a programmable digital device. Experimental results obtained with an 11-level inverter prototype confirm the effectiveness of the proposed fault detection technique. In addition, they show that the diagnosis method is unaffected by variations of the modulation index.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1950-1963
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• 2016

A novel open-circuit fault diagnosis method for 3-phase 4-wire 3-level active power filters based on voltage error correlation is proposed in this paper. This method is based on observing the output pole voltage error of the active power filter through two kinds of algorithms. One algorithm is a voltage error analytical algorithm, which derives four output voltage error analytic expressions through the pulse state, current value and dc bus voltage, respectively, assuming that all of the IGBTs of a certain phase come to an OC fault. The other algorithm is a current circuit equation algorithm, which calculates the real-time output voltage error through basic circuit theory. A correlation is introduced to measure the similarity of the output voltage errors between the two algorithms, and OC faults are located by the maximum of the correlations. A FPGA has been chosen to implement the proposed method due to its fast prototyping. Simulation and experimental results are presented to show the performance of the proposed OC fault diagnosis method.