• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.3
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• pp.223-236
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• 1999

The need to monitor and undertake remidial works on large structures has greatly increased in recent years due to the appearance of widespread faults in large structures such as bridges and buildings, etc, of 20 or more years of age. The health condition of structures must be monitored continuously to maintenance the structures. In order to do in-situ monitoring, the sensor is necessary to be embedded in the structures. Fiber optic sensors can be embedded in the structures to get the health information in the structures. The fiber sensor was constructed with $3{\times}3$ fiber couplers to sense the multi-point strains and failure instants. The 4 RC (reinforced concrete) beams were made to 2 of A type, 2 of B type beams. These beams were reinforced by the reinforcing bars, and were tested under the flexural loading. The behavior of the beams was simultaneously measured by the fiber optic sensors, electrical strain gages, and LVDT. The states of the beams were interpreted by these all signals. By these experiments, There were verified that the fiber optic sensors could measure the structural strains and failure instants of the RC beams, The fiber sensors were well operated until the failure of the beams. It was shown that the strains of the reinforcing steel bar can be used to monitor the health condition of the beams through the flexural test of RC beams. On the other words, the results were arrived that the two strains in the reinforcing bar measured at the same point can give the information of the structural health status. Also, the failure instants of beams were well detected from the fiber optic filtered signals.

• Journal of the Korean Society of Safety
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• v.26 no.6
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• pp.104-110
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• 2011

In FMEA, the risk priority number(RPN) is used for risk evaluation on each failure mode. It is obtained by multiplying three components, i.e., severity, occurrence, and detectability of the corresponding failure mode. Each of the three components are usually determined on the basis of the past experience and technical knowledge. But this approach is not strictly objective in evaluating risk of a given failure mode and thus provide somewhat less scientific measure of risk. Assuming a homogeneous Poisson process for occurrence of the failures and causes, we propose a more scientific approach to evaluation of risk in FMEA. To quantify severity of each failure mode, the mission period is taken into consideration for the system. If the system faces no failure during its mission period, there are no losses. If any failure occurs during its mission period, the losses corresponding to the failure mode incurs. A longer remaining mission period is assumed to incur a larger loss. Detectability of each failure mode is then incorporated into the model assuming an exponential probability law for detection time of each failure cause. Based on the proposed model, an illustrative example and numerical analyses are provided.

• Journal of Veterinary Clinics
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• v.18 no.1
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• pp.35-43
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• 2001

Present study was undertaken in order to document early renal ultrasonographic changes of gentamicin nephrotoxicosis and to show the value of renal ultrasonography as a contributory means of early diagnosis of acute renal failure in dogs. The experimental design was a randomized complete block design with six treatments in two blocks (gentamicin-treated & saline-treated). Acute renal failure was induced by toxic dosage of gentamicin (30 mg/kg) and saline solution sham equivalent in volume to that of the toxic dosage of gentamicin (1.5-3ml). Subjective visualization of increased renal cortex was visible as homogenous echoes that were hypoechoic relative to the surrounding tissues, whereas the renal medulla was anechoic to slightly hypoechoic. After treatment, the renal cortex was hyperechoic relative to the surrounding tissue. Increased renal cortex echogenicity was associated with significant nephrotoxicosis and was superior to serum creatinine elevation in nephrotoxicosis detection. Urine GGT was superior to other clinicopathological data utilized in the diagnosis of nephrotoxicosis. Based on the above results, increased renal cortex echogenicity seemed to be of use in detecting of acute renal failure.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.483-489
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• 2009

Electrolytic capacitors are used in variety of equipments as smoothening element of the power converters because it has high capacitance for its size and low price. Electrolytic capacitors, which is most of the time affected by aging effect, plays a very important role for the power electronics system quality and reliability. Therefore it is important to estimate the parameter of an electrolytic capacitor to predict the failure. This objective of this paper is to propose a new method to detect the rise of equivalent series resistor(ESR) in order to realize the online failure prediction of electrolytic capacitor for DC output filter of power converter. The ESR of electrolytic capacitor estimated from RMS result of filtered waveform(BPF) of the ripple capacitor voltage/current. Therefore, the preposed online failure prediction method has the merits of easy ESR computation and circuit simplicity. Simulation and experimental results are shown to verify the performance of the proposed on-line method.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.219-223
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• 2002

Voltage and current signals during impulse tests on transformer are treated as non-stationary signals. A new method incorporating signal-processing method such as Wavelets and courier transform is proposed for failure identification. It is now possible to distinguish failure during impulse tests. The method is experimentally validated on a transformer winding. The wavelet transforms enables the detection of the time of occurrence of switching or failure events. After establishing the time of occurrence, the original waveform is split into two or more sections. The wavelet transform has ability to analysis the failure signal on time domain as well as frequency domain. Therefore, the wavelet transform is superior than courier transform to analysis the failure signal. In this paper, the fact was proved by real data which was achieved.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.103-110
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• 2000

This paper deal with the stability evaluation and suggestion of progressive failure slope in biotite granite area of Andong. Based on geological site investigation and field test, stability analysis of slope was performed in conjunction with limit equilibrium methods and stereographic projection. Additionally, initial design and construction procedure was critically evaluated. Series of the slope stability analysis reveals the detection of local wedge and plane failure under the current slope condition. It is additionally appeared that a certain synthetic behavior of circle and plane failure exists on the right spot where the overall failure's going in progress. In order to construct more stable slope based on the suitability for the real state of the slope circumstances, this study issues a solution to eliminate the primary factors which cause the instability, by means of the grade of weathering and RMR classification of rock mass.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.13 no.1
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• pp.40-47
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• 2017

In this paper, we investigate the feasibility of a strategy of failure detection and identification. The point of proposed strategy includes a pattern extraction approach for failure identification using Auto-Associative Kernel Regression (AAKR). We consider a simulation data concerning 605 signals of a Generic Pressurized Water Reactor(GPWR). In the application, the reconstructions are provided by a set of AAKR models, whose input signals have been selected by Correlation Analysis(CA) for the identification of the groups. The failure pattern is extracted by analyzing the residuals of observations and reconstructions. We present the possibility of extraction of patterns for six failure.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1401-1410
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• 2014

This paper presents a modified adaptive fading EKF (AFEKF) for sensor fault detection and isolation in the satellite. Also, the fault detection and isolation (FDI) scheme is developed in three phases. In the first phase, the AFEKF is modified to increase sensor fault detection performance. The sensor fault detection and sensor selection method are proposed. In the second phase, the IMM filer with scalar penalty is designed to detect wherever actuator faults occur. In the third phase of the FDI scheme, the sub-IMM filter is designed to identify the fault type which is either the total or partial fault. An important feature of the proposed FDI scheme can decrease the number of filters for detecting sensor fault. Also, the proposed scheme can classify fault detection and isolation as well as fault type identification.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.1
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• pp.160-166
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• 2010

Railroad level crossing systems are used to prevent train from collisions by informing pedestrians and vehicles of approaching trains on the level crossing. The current detection systems mostly use track-based electrical circuits to detect approaching trains. The making and breaking of the circuit when the train wheel passes along the track sends a signal to barriers that restrict access to the track. Unfortunately, this track-based signal system is vulnerable to malfunctions in certain situations. If the rail becomes rusted due to moisture, weather conditions, or infrequent use, the electrical circuit detection system could fail. Such a failure could lead to a train-vehicle or train-pedestrian collision. This paper suggests a replacement of the electrical circuit-based system with an infrared detection system. The research shows that an infrared detection system improves safety by reducing the frequency of detection failure of the alarming circuit to system.

• ETRI Journal
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• v.36 no.5
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.