• Progress in Superconductivity and Cryogenics
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• v.8 no.2
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• pp.43-45
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• 2006

Recently, the resistive Fault Current Limiter (SFCL) made with Coated Conductor (CC) has been researched with an advanced capability in CC. Current limiting elements must be connected in series in order to fabricate the resistive SFCL having large capacity. By the way, unless the applied voltage in the SFCL is distributed to the elements when the fault occurred, those elements will be critically damaged. Thus simultaneous quench of the elements is an important factor to design the resistive SFCL. In this paper, simultaneous quench characteristics of current limiting module by using BSCCO 2223 were researched before manufacturing the resistive SFCL by using CC. At the first fault stage, the elements generated the resistance at the same time. However, the unequal voltage is applied to the each element in process of time. The method is suggested to solve the problem of the unequal distribution. These experimental results will play an important part in developing for the resistive SFCL by using CC.

• Journal of Power Electronics
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• v.17 no.4
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• pp.1014-1026
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• 2017

The traditional fault diagnosis method for photovoltaic (PV) inverters has a difficult time meeting the requirements of the current complex systems. Its main weakness lies in the study of nonlinear systems. In addition, its diagnosis time is long and its accuracy is low. To solve these problems, a hidden Markov model (HMM) is used that has unique advantages in terms of its training model and its recognition for diagnosing faults. However, the initial value of the HMM has a great influence on the model, and it is possible to achieve a local minimum in the training process. Therefore, a genetic algorithm is used to optimize the initial value and to achieve global optimization. In this paper, the HMM is combined with a genetic algorithm (GHMM) for PV inverter fault diagnosis. First Matlab is used to implement the genetic algorithm and to determine the optimal HMM initial value. Then a Baum-Welch algorithm is used for iterative training. Finally, a Viterbi algorithm is used for fault identification. Experimental results show that the correct PV inverter fault recognition rate by the HMM is about 10% higher than that of traditional methods. Using the GHMM, the correct recognition rate is further increased by approximately 13%, and the diagnosis time is greatly reduced. Therefore, the GHMM is faster and more accurate in diagnosing PV inverter faults.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.3-13
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• 2010

Differential Fault Analysis (DFA) is widely known for one of the most efficient method analyzing block cipher. In this paper, we propose a new type of DFA on DES (Data Encryption Standard). DFA on DES was first introduced by Biham and Shamir, then Rivain recently introduced DFA on DES middle rounds (9-12 round). However previous attacks on DES can only be applied to the encryption process. Meanwhile, we first propose the DFA on DES key-schedule. In this paper, we proposed a more efficient DFA on DES key schedule with random fault. The proposed DFA method retrieves the key using a more practical fault model and requires fewer faults than the previous DFA on DES.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.271-277
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• 2022

PBFT (Practical Byzantine Fault Tolerant) is a consensus algorithm that can achieve consensus by resolving unintentional and intentional faults in a distributed network environment and can guarantee high performance and absolute finality. However, as the size of the network increases, the network load also increases due to message broadcasting that repeatedly occurs during the consensus process. Due to the characteristics of the PBFT algorithm, it is suitable for small/private blockchain, but there is a limit to its application to large/public blockchain. Because PBFT affects the performance of blockchain networks, the industry should test whether PBFT is suitable for products and services, and academia needs a unified evaluation metric and technology for PBFT performance improvement research. In this paper, quantitative evaluation metrics and evaluation frameworks that can evaluate PBFT family consensus algorithms are studied. In addition, the throughput, latency, and fault tolerance of PBFT are evaluated using the proposed PBFT evaluation framework.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.185-195
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• 2018

As machines have been automated in the field of industries in recent years, it is a paramount importance to manage and maintain the automation machines. When a fault occurs in sensors attached to the machine, the machine may malfunction and further, a huge damage will be caused in the process line. To prevent the situation, the fault of sensors should be monitored, diagnosed and classified in a proper way. In the paper, we propose a sensor fault detection scheme based on SVM and CNN to detect and classify typical sensor errors such as erratic, drift, hard-over, spike, and stuck faults. Time-domain statistical features are utilized for the learning and testing in the proposed scheme, and the genetic algorithm is utilized to select the subset of optimal features. To classify multiple sensor faults, a multi-layer SVM is utilized, and ensemble technique is used for CNN. As a result, the SVM that utilizes a subset of features selected by the genetic algorithm provides better performance than the SVM that utilizes all the features. However, the performance of CNN is superior to that of the SVM.

• Economic and Environmental Geology
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• v.56 no.3
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• pp.293-300
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• 2023

The Shape Preferred Orientation (SPO) method has been used to analyze the orientation of fault motion, which is utilized as basic data for fault kinematics studies. The rigid grains, which as quartz, feldspar, and rock fragments, in the fault gouge are arranged in the P-shear direction through rigid body rotation by a given shear stress. Using this characteristic, the fault motion can be estimated from the SPO inversely. Recently, a method for securing precision and reliability by measuring 3D-SPO using X-ray CT images and examining the shape of a large number of particles in a short time has been developed. As a result, the SPO method analyzes the orientation of thousands to tens of thousands of particles at high speed, suggests the direction of fault motion, and provides easy accessibility and reliable data. In addition, the shape information and orientation distribution data of particles, which are by-products obtained in the SPO analysis process, are expected to be used as basic data for conducting various studies such as the local deformation of fault rocks and the fault generation mechanism.

• Applied Biological Chemistry
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• v.50 no.4
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• pp.245-252
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• 2007

FTA (fault tree analysis), an analytical method for system failure management, was employed in the management of faults in running PCR analysis. PCR is executed through several processes, in which the process of PCR machine operation was selected for the analysis by FTA. The reason for choosing the simplest process in the PCR analysis was to adopt it as a first trial to test a feasibility of the FTA approach. First, fault events-top event, intermediate event, basic events-were identified by survey on expert knowledge of PCR. Then those events were correlated deductively to build a fault tree in hierarchical structure. The fault tree was evaluated qualitatively and quantitatively, yielding minimal cut sets, structural importance, common cause vulnerability, simulation of probability of occurrence of top event, cut set importance, item importance and sensitivity. The top event was 'errors in the step of PCR machine operation in running PCR analysis'. The major intermediate events were 'failures in instrument' and 'errors in actions in experiment'. The basic events were four events, one event and one event based on human errors, instrument failure and energy source failure, respectively. Those events were combined with Boolean logic gates-AND or OR, constructing a fault tree. In the qualitative evaluation of the tree, the basic events-'errors in preparing the reaction mixture', 'errors in setting temperature and time of PCR machine', 'failure of electrical power during running PCR machine', 'errors in selecting adequate PCR machine'-proved the most critical in the occurrence of the fault of the top event. In the quantitative evaluation, the list of the critical events were not the same as that from the qualitative evaluation. It was because the probability value of PCR machine failure, not on the list above though, increased with used time, and the probability of the events of electricity failure and defective of PCR machine were given zero due to rare likelihood of the events in general. It was concluded that this feasibility study is worth being a means to introduce the novel technique, FTA, to the management of faults in running PCR analysis.

• 전기의세계
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• v.25 no.6
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• pp.8-13
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• 1976

The industrial processes have become complicated on a large scale bacause of improvement of productivity, research of efficiency, and shortage of locations to be suited for foundation of factories. Consequently, the instrumentation and control systems for operating these industrial processes have also been highly improved with the development of mass information means. In order to operate these large-sized and complicated industrial processes safely, the man-machine interface for correspondence between man and machines and the instrumentation system regarding process fault processing are playing an important role increasingly. This paper describes recent instrumentation system in the water purifying plant as an example of these industrial processes, and covers both man-machine interface and process fault processing. The annual water supply quantity and diffusion were 2, 000, 000, 000m$^{3}$ and 25.0% in 1950 inJapan, but they amounted to 12, 000, 000, 000m$^{3}$ and 86.7% in 1974, respectively. The demands of water will increase incessantly, while it becomes gradually difficult to secure water sources. Accordingly, local self-governing bodies such as municipal cooperation, towns, and villages often construct a large-scale water purifying plant at one place in common, as required, without constructing respective plants independently. It is an absolute requirement for the water purifying plant to avoid stopping water supply to fullfil its social responsibility from the viewpoints of its public utility enterprise, and also it has gradually become difficult to secure skilled operators enough to cover such water purifying plants that are additionally provided in various districts. Thus, the importance of the man-machine interface for assuring safety operation of the water purifying plant irrespective of unskillfulness of operators as well as the instrumentation system regarding process fault processing, or, safety instrumentation, is more and more increasing as the water purifying plants are on a large scale.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.806-818
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• 2009

Since the invention of the integrated circuit (IC) in 1950s, semiconductor technology has undergone dramatic development up to these days. A complete semiconductor is manufactured through a diversity of processes. For better semiconductor productivity, fault detection and classification (FDC) has been rigorously studied for finding faults even before the processes are completed. For FDC, various kinds of sensors are attached in many semiconductor manufacturing devices, and sensor values are collected in a periodic manner. The collection of sensor values consists of sequences of real numbers, and hence is regarded as a kind of time-series data. In this paper, we propose an algorithm for detecting and clustering faults in semiconductor processes. The proposed algorithm is a modification of the existing anomaly detection algorithm dealing with symbolically-represented time-series. The contributions of this paper are: (1) showing that a modification of the existing anomaly detection algorithm dealing with general time-series could be used for semiconductor process data and (2) presenting experimental results for improving correctness of fault detection and clustering. As a result of our experiment, the proposed algorithm caused neither false positive nor false negative.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.273-282
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• 2023

Probabilistic safety assessment (PSA) has been widely used to evaluate the seismic risk of nuclear power plants (NPPs). However, studies on seismic PSA for process plants, such as gas plants, oil refineries, and chemical plants, have been scarce. This is because the major disasters to which these process plants are vulnerable include explosions, fires, and release (or dispersion) of toxic chemicals. However, seismic PSA is essential for the plants located in regions with significant earthquake risks. Seismic PSA entails probabilistic seismic hazard analysis (PSHA), event tree analysis (ETA), fault tree analysis (FTA), and fragility analysis for the structures and essential equipment items. Among those analyses, ETA can depict the accident sequence for core damage, which is the worst disaster and top event concerning NPPs. However, there is no general top event with regard to process plants. Therefore, PSA cannot be directly applied to process plants. Moreover, there is a paucity of studies on developing fragility curves for various equipment. This paper introduces PSA for gas plants based on FTA, which is then transformed into Bayesian network, that is, a probabilistic graph model that can aid risk-informed decision-making. Finally, the proposed method is applied to a gas plant, and several decision-making cases are demonstrated.