• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1597-1610
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• 2005

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) that is independent of a CNC vendor. The OAC and machine tools with an OAC have led to a convenient environment in which user-defined applications can be efficiently implemented within a CNC. This paper proposes a method of diagnosing the cause of operational faults. The method is based on the status of a programmable logic controller in machine tools with an OAC. An operational fault is defined as a disability that occurs during the normal operation of machine tools. Operational faults constitute more than 70 percent of all faults and are also unpredictable because most of them occur without any warning. To quickly and correctly diagnose the cause of an operational fault, two diagnostic models are proposed: the switching function and the step switching function. The cause of the fault is logically diagnosed through a fault diagnosis system using diagnostic models. A suitable interface environment between a CNC and developed application modules is constructed to implement the diagnostic functions in the CNC domain. The results of the diagnosis were displayed on a CNC monitor for machine operators and transmitted to a remote site through a Web browser. The proposed diagnostic method and its results were useful to unskilled machine operators and reduced the machine downtime.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.5
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• pp.299-304
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• 2018

An ideal circuit breaker should supply electric power to loads without losses in a conduction state and completely isolate the load from the power source by providing insulation strength in a break state. Fault current is relatively easy to break in an Alternating Current (AC) circuit breaker because the AC current becomes zero at every half cycle. However, fault current in DC circuit breaker (DCCB) should be reduced by generating a high arc voltage at the breaker contact point. Large fire may occur if the DCCB does not take sufficient arc voltage and allows the continuous flow of the arc fault current with high temperature. A semiconductor circuit breaker with a power electronic device has many advantages. These advantages include quick breaking time, lack of arc generation, and lower noise than mechanical circuit breakers. However, a large load capacity cannot be applied because of large conduction loss. An extinguishing technology of DCCB with polymeric positive temperature coefficient (PPTC) device is proposed and evaluated through experiments in this study to take advantage of low conduction loss of mechanical circuit breaker and arcless breaking characteristic of semiconductor devices.

• Nuclear Engineering and Technology
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• v.39 no.1
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• pp.51-62
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• 2007

To efficiently design safety-critical systems such as nuclear power plants, with the requirement of high reliability, methodologies allowing for rigorous interactions between the synthesis and analysis processes have been proposed. This paper attempts to develop a reliability-centered design framework through an interactive process between Axiomatic Design (AD) and Fault Tree Analysis (FTA). Integrating AD and FTA into a single framework appears to be a viable solution, as they compliment each other with their unique advantages. AD provides a systematic synthesis tool while FTA is commonly used as a safety analysis tool. These methodologies build a design process that is less subjective, and they enable designers to develop insights that lead to solutions with improved reliability. Due to the nature of the two methodologies, the information involved in each process is complementary: a success tree versus a fault tree. Thus, at each step a system using AD is synthesized, and its reliability is then quantified using the FT derived from the AD synthesis process. The converted FT provides an opportunity to examine the completeness of the outcome from the synthesis process. This study presents an example of the design of a Containment Heat Removal System (CHRS). A case study illustrates the process of designing the CHRS with an interactive design framework focusing on the conversion of the AD process to FTA.

• Progress in Superconductivity and Cryogenics
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• v.5 no.1
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• pp.56-59
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• 2003

As electric power systems grow to supply the increasing electric power demand short-circuit current tends to increase and impose a severe burden on circuit breakers and power system apparatuses. Thus, all electric equipment in a power system has to he designed to withstand the mechanical and thermal stresses of potential short-circuit currents. Among current limiting devices, Fault Current Limiter (FCL) is expected to reduce the short-circuit current. Especially, Superconducting Fault Current Limiters (SFCL) offer ideal performance: in normal operation the SFCL is in its superconducting state and has negligible impedance, in the event of a fault, the transition into the normal conducting state passively limits the current. The SFCL using high-temperature superconductors offers a positive resolution to controlling fault-current levels on utility distribution and transmission networks. This study contributes to the EMTDC based modeling and simulation method of DC Reactor type SFCL. Single and three phase faults in the utility system with DC reactor type SFCLs have been simulated using EMTDC in order to coordinate with other equipments, and the results are discussed in detail.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.760-765
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• 2004

One of the obstacles for a magnetic bearing to be used in the wide range of industrial applications is the failure modes associated with magnetic bearings, which we don't expect for conventional passive bearings. These failure modes include electric power outage, power amplifier faults, position sensor faults, and the malfunction of controllers. Fault-tolerant magnetic bearing systems have been proposed so that the system can operate in spite of some faults in the system. In this paper, we designed and implemented a fault-tolerant magnetic bearing system for a turbo-molecular vacuum pump. The system can cope with the actuator/amplifier faults as well as the faults in position sensors, which are the two major fault modes in a magnetic bearing system.

• International Journal of Air-Conditioning and Refrigeration
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• v.11 no.3
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• pp.125-131
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• 2003

The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of the air-conditioning system. In this paper, two fault detection methods were considered. One is a generic neural network, and the other is an moving average neural network. In order to compare the performance of fault detection results from these methods, two different types of faults in an air-conditioning system were applied. These are the condenser 30% fouling and the evaporator fan 25% slowdown. Test results showed that the moving average neural network was more effective for the detection of partial faults in the air-conditioning system.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.19-25
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• 1998

Remote fault diagnosis and maintenance system using general telecommunication network is necessary for an effective fault diagnosis and higher productivity of NC machine tools. In order to monitor machine tool condition and diagnose alarm states due to electrical and mechanical faults, a remote data communication system for monitoring of NC machine fault diagnosis and status is developed. The developed system consists of (1) remote communication module among NC's and host PC using PSTN. (2) 8 channels analog data sensing module, (3) digital I/O module for control or NC machine, (4) communication module between NC machine and remote data communication system via RS-232C, and (5) software man-machine interface. Diagnostic monitoring results generated through a successive type inference engine are displayed in user-friendly graphics. The validity and reliability of the developed system is verified to be a powerful commercial version on a vertical machining center through a series of experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.513-518
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• 2007

In this paper, we propose a fault diagnosis scheme tor induction motor by adopting a hierarchical classifier consisting of k-Nearest Neighbors(k-NN) and Support Vector Machine(SVM). First, some motor conditions are classified by a simple k-NN classifier in advance. And then, more complicated classes are distinguished by SVM. To obtain the normal and fault data, we established an experimental unit with induction motor system and data acquisition module. Feature extraction is performed by Principal Component Analysis(PCA). To show its effectiveness, the proposed fault diagnostic system has been intensively tested with various data acquired under the different electrical and mechanical faults with varying load.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.41-47
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• 1997

Fault diagnosis problem is currently a subject of extensive research in the control field. Although there are several works on the fault detection and isolation observers and the residual generators, those are con- cerned with only the detection of actuator failures or sensor failures. So, the perfect detection and isolation for the actuator and sensor failures is strongly required in the field of the practical applications. In this paper, a strategy of fault diagnosis using multiple proportional integral (PI) observers including the magnitude of actuator failures is provided. It is shown that actuator failures are detected and isolated perfectly by monitoring the integrated error between actual output and estimated output by a PI observer. Also in presence of complex actuator and sensor failures, these failures are detected and isolated by multiple PI observers.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1604-1612
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• 2002

Rollers in the continuous process systems are ones of key components that determine the quality of web products. The condition of rollers (e.g. eccentricity, runout) should be consistently monitored in order to maintain the process conditions (e.g. tension, edge position) within a required specification. In this paper, a new diagnosis algorithm is suggested to detect the defective rollers based on the frequency analysis of web tension signals. The kernel of this technique is to use the characteristic features (RMS, Peak value, Power spectral density) of tension signals which allow the identification of the faulty rollers and the diagnosis of the degree of fault in the rollers. The characteristic features could be used to train an artificial neural network which could classify roller conditions into three groups (normal, warning, and faulty conditions) The simulation and experimental results showed that the suggested diagnosis algorithm can be successfully used to identify the defective rollers as well as to diagnose the degree of the defect of those rollers.