• Proceedings of the Korea Institute of Fire Science and Engineering Conference
• /
• 2002.05a
• /
• pp.81-86
• /
• 2002

• The KIPS Transactions:PartA
• /
• v.15A no.3
• /
• pp.151-154
• /
• 2008

A middleware in grid computing environment is required to support seamless on-demand services over diverse resource situations in order to meet various user requirements [1]. Since grid computing applications need situation-aware middleware services in this environment. In this paper, we propose a semantic middleware architecture to support dynamic software component reconfiguration based fault and service ontology to provide fault-tolerance in a grid computing environment. Our middleware includes autonomic management to detect faults, analyze causes of them, and plan semantically meaningful strategies to recover from the failure using pre-defined fault and service ontology trees. We implemented a referenced prototype, Web-service based Application Execution Environment(Wapee), as a proof-of-concept, and showed the efficiency in runtime recovery.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.2
• /
• pp.536-564
• /
• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

• Nuclear Engineering and Technology
• /
• v.54 no.12
• /
• pp.4560-4570
• /
• 2022

Dynamic fault tree (DFT) and its related research methods have received extensive attention in safety analysis and reliability engineering. DFT can perform reliability modelling for systems with sequential correlation, resource sharing, and cold and hot spare parts. A technical modelling method of DFT is proposed for modelling ship collision accidents and loss-of-coolant accidents (LOCAs). Qualitative and quantitative analyses of DFT were carried out using the cutting sequence (CS)/extended cutting sequence (ECS) method. The results show nine types of dynamic fault failure modes in ship collision accidents, describing the fault propagation process of a dynamic system and reflect the dynamic changes of the entire accident system. The probability of a ship collision accident is 2.378 × 10^-9 by using CS. This failure mode cannot be expressed by a combination of basic events within the same event frame after an LOCA occurs in a marine nuclear reactor because the system contains warm spare parts. Therefore, the probability of losing reactor control was calculated as 8.125 × 10^-6 using the ECS. Compared with CS, ECS is more efficient considering expression and processing capabilities, and has a significant advantage considering cost.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.275-278
• /
• 1996

This fault diagnosis system consists of qualitative models, qualitative interpreter, and inference engine. Qualitative models are formed by analysis of the relationships between faults and behaviors of sensor trends, which are described by state transition trees. Qualitative interpreter outputs confidence factors with three qualitative quantities which represent the states of sensor trends. And then, the possible faults are detected by inference module which matches the states of trends within a window size with the qualitative models using the well-known min-max operation.

• Journal of the Korean Society of Safety
• /
• v.12 no.3
• /
• pp.155-160
• /
• 1997

The conventional fault tree and reliability analysis gives in many cases insufficient information concerning the relative frequencies of hazard events. This stems from that the basic events are not stationary and ergodic, and therefore the tolerances of the induced and top events cannot be calculated reliably based on the classical probability theory. To overcome this difficulty, the paper considers the relative frequencies of the basic events as fuzzy numbers and uses instead of probability, possible considerations for evaluating the mean values and tolerances of the top events. The possibility distribution of the basic events can be approximated based on heuristic considerations. This paper shows the use of these operators for constructing fault trees. The use of the method for numerical calculation is demonstrated on a field safety problem.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.3
• /
• pp.363-371
• /
• 1994

This thesis investigates an expert system(ES) to propose fault restoration plan by utilizing tree search strategies. In order to cope with an extensive amount of data and frequent breaker switching operations in distribution systems, the database of system configuration is constructed by using binary trees. This remarkably enhances the efficiency of search algorithm and makes the proposed ES easily adaptable to system changes due to switching operations. The rule-base is established to fully utilize the meris of tree-structured database. The inferring strategy is developed mainly based on the best-first search algorithm to increase computation efficiency. The proposed ES has been implemented to efficiently deal with large distribution systems by reducing computational burden remarkably compared with the conventional ES's.

• ETRI Journal
• /
• v.34 no.3
• /
• pp.478-481
• /
• 2012

Testing memory and repairing faults have become increasingly important for improving yield. Redundancy analysis (RA) algorithms have been developed to repair memory faults. However, many RA algorithms have low analysis speeds and occupy memory space within automatic test equipment. A fast RA algorithm using simple calculations is proposed in this letter to minimize both the test and repair time. This analysis uses the grouped addresses in the faulty bitmap. Since the fault groups are independent of each other, the time needed to find solutions can be greatly reduced using these fault groups. Also, the proposed algorithm does not need to store searching trees, thereby minimizing the required memory space. Our experiments show that the proposed RA algorithm is very efficient in terms of speed and memory requirements.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.886-890
• /
• 2007

Machine fault prognosis techniques have been considered profoundly in the recent time due to their profit for reducing unexpected faults or unscheduled maintenance. With those techniques, the working conditions of components, the trending of fault propagation, and the time-to-failure are forecasted precisely before they reach the failure thresholds. In this work, we propose an approach of Least Square Regression Tree (LSRT), which is an extension of the Classification and Regression Tree (CART), in association with one-step-ahead prediction of time-series forecasting technique to predict the future conditions of machines. In this technique, the number of available observations is firstly determined by using Cao's method and LSRT is employed as prognosis system in the next step. The proposed approach is evaluated by real data of low methane compressor. Furthermore, the comparison between the predicted results of CART and LSRT are carried out to prove the accuracy. The predicted results show that LSRT offers a potential for machine condition prognosis.

• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.5
• /
• pp.429-436
• /
• 2009

Odd network was introduced as one model of graph theory. In [1], it was introduced as a class of fault-tolerant multiprocessor networks and analyzed so many useful properties such as simple routing algorithms, maximal fault tolerance, node axsjoint path, etc. In this paper, we sauw a construction algorithm of edge-axsjoint spanning trees in Odd network $O_d$. Also, we prove that edge-disjoint spanning tree generated by our algorithm is optimal edge-disjoint spanning tree.