• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2257-2285
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• 2022

Cyber-physical systems (CPS) have been growing exponentially due to improved cloud-datacenter infrastructure-as-a-service (CDIaaS). Incremental expandability (scalability), Quality of Service (QoS) performance, and reliability are currently the automation focus on healthy Tier 4 CDIaaS. However, stable QoS is yet to be fully addressed in Cyber-physical data centers (CP-DCS). Also, balanced agility and flexibility for the application workloads need urgent attention. There is a need for a resilient and fault-tolerance scheme in terms of CPS routing service including Pod cluster reliability analytics that meets QoS requirements. Motivated by these concerns, our contributions are fourfold. First, a Distributed Non-Recursive Cloud Model (DNRCM) is proposed to support cyber-physical workloads for remote lab activities. Second, an efficient QoS stability model with Routh-Hurwitz criteria is established. Third, an evaluation of the CDIaaS DCN topology is validated for handling large-scale, traffic workloads. Network Function Virtualization (NFV) with Floodlight SDN controllers was adopted for the implementation of DNRCM with embedded rule-base in Open vSwitch engines. Fourth, QoS evaluation is carried out experimentally. Considering the non-recursive queuing delays with SDN isolation (logical), a lower queuing delay (19.65%) is observed. Without logical isolation, the average queuing delay is 80.34%. Without logical resource isolation, the fault tolerance yields 33.55%, while with logical isolation, it yields 66.44%. In terms of throughput, DNRCM, recursive BCube, and DCell offered 38.30%, 36.37%, and 25.53% respectively. Similarly, the DNRCM had an improved incremental scalability profile of 40.00%, while BCube and Recursive DCell had 33.33%, and 26.67% respectively. In terms of service availability, the DNRCM offered 52.10% compared with recursive BCube and DCell which yielded 34.72% and 13.18% respectively. The average delays obtained for DNRCM, recursive BCube, and DCell are 32.81%, 33.44%, and 33.75% respectively. Finally, workload utilization for DNRCM, recursive BCube, and DCell yielded 50.28%, 27.93%, and 21.79% respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.673-681
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• 2005

As it is the most important to make sure security and reliability for nuclear Power Plant, it's considered the most crucial issues to develop a fault detective and diagnostic system in spite of multiple hardware redundancy in itself. To develop an algorithm for a fault diagnosis in the nuclear PWR steam generator, this paper proposes a method based on ART2(adaptive resonance theory 2) neural network that senses and classifies troubles occurred in the system. The fault diagnosis system consists of fault detective part to sense occurred troubles, parameter estimation part to identify changed system parameters and fault classification part to understand types of troubles occurred. The fault classification part Is composed of a fault classifier that uses ART2 neural network. The Performance of the proposed fault diagnosis a18orithm was corroborated by applying in the steam generator.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.97-110
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• 2012

High performance sensors and modern data logging technology with real-time telemetry facilitate system fault diagnosis in a very precise manner. Fault detection, isolation and identification in fault diagnosis systems are typical steps to analyze the root cause of failures. This systematic failure analysis provides not only useful clues to rectify the abnormal behaviors of a system, but also key information to redesign the current system for retrofit. The main barriers to effective failure analysis are: (i) the gathered data (event) logs are too large in general, and further (ii) they usually contain noise and redundant data that make precise analysis difficult. This paper therefore applies suitable pre-processing techniques to data reduction and feature extraction, and then converts the reduced data log into a new format of event sequence information. Finally the event sequence information is decoded to investigate the correlation between specific event patterns and various system faults. The efficiency of the developed pre-filtering procedure is examined with a terminal box data log of a marine diesel engine.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1085-1091
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• 2014

A model based SOC estimation scheme using parameter identification is described and applied to a Lithium-ion battery module that can be installed in electric vehicles. Simulation studies are performed to verify the effect of sensor faults on the SOC estimation results for terminal voltage sensor and load current sensor. The sensor faults should be detected and isolated as soon as possible because the SOC estimation error due to any sensor fault seriously affects the overall performance of the BMS. A new fault detection and isolation(FDI) scheme by which the fault of terminal voltage sensor and load current sensor can be detected and isolated is proposed to improve the reliability of the BMS. The proposed FDI scheme utilizes the parameter estimation of an input-output model and two fuzzy predictors for residual generation; one for terminal voltage and the other for load current. Recently developed dual polarization(DP) model is taken to develope and evaluate the performance of the proposed FDI scheme. Simulation results show the practical feasibility of the proposed FDI scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.1-8
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• 2004

In this paper, we propose neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, ART2 neural network is used for fault isolation. The performance and effectiveness of the proposed ART2 neural network based fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

• Smart Structures and Systems
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• v.22 no.4
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• pp.383-397
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• 2018

Traditional base isolation systems focus on isolating the seismic response of a structure in the horizontal direction. However, in regions where the vertical earthquake excitation is significant (such as near-fault region), a traditional base-isolated building exhibits a significant vertical vibration. To eliminate this shortcoming, a rocking-isolated system named Telescopic Column (TC) is proposed in this paper. Detailed rocking and isolation mechanism of the TC system is presented. The seismic performance of the TC is compared with the traditional elastomeric bearing (EB) and friction pendulum (FP) base-isolated systems. A 4-storey reinforced concrete moment-resisting frame (RC-MRF) is selected as the reference superstructure. The seismic response of the reference superstructure in terms of column axial forces, base shears, floor accelerations, inter-storey drift ratios (IDR) and collapse margin ratios (CMRs) are evaluated using OpenSees. The results of the nonlinear dynamic analysis subjected to multi-directional earthquake excitations show that the superstructure equipped with the newly proposed TC is more resilient and exhibits a superior response with higher margin of safety against collapse when compared with the same superstructure with the traditional base-isolation (BI) system.

• Structural Monitoring and Maintenance
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• v.10 no.3
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• pp.243-260
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• 2023

Indonesia has had seismic codes for earthquake-resistant structures designs since 1970 and has been updated five times to the latest in 2019. In updating the Indonesian seismic codes, seismic hazard maps for design also update, and there are changes to the Peak Ground Acceleration (PGA). Indonesian seismic design uses the concept of building performance levels consisting of Immediate occupancy (IO), Life Safety (LS), and Collapse Prevention (CP). Related to this performance level, cases still found that buildings were damaged more than their performance targets after the earthquake. Based on the above issues, this study aims to analyze the performance of base isolation design on existing target buildings and analyze the seismic fragility for a case study in Indonesia. The target building is a prototype design 8-story medium-rise residential building using the reinforced concrete moment frame structure. Seismic fragility analysis uses Incremental Dynamic Analysis (IDA) with Nonlinear Time History Analysis (NLTHA) and eleven selected ground motions based on soil classification, magnitude, fault distance, and earthquake source mechanism. The comparison result of IDA shows a trend of significant performance improvement, with the same performance level target and risk category, the base isolation structure can be used at 1.46-3.20 times higher PGA than the fixed base structure. Then the fragility analysis results show that the fixed base structure has a safety margin of 30% and a base isolation structure of 62.5% from the PGA design. This result is useful for assessing existing buildings or considering a new building's performance.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2041_2042
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• 2009

The diagnostic/prognostic problems for condition based maintenance or Prognostics and Health Management has been used. Primary objectives of diagnosis/prognosis are maximizing system availability and minimizing downtime from fault isolation through more effective troubleshooting efforts. Diagnosis aims to detect the onset of failures to improve system performance and reduce life cycle cost by reducing the failure time. The prognosis can reduce operational and support total ownership cost and improve safety of machinery and complex systems. In this Paper, a fault diagnosis methodology has been described using a monopropellant propulsion system model as a test bench.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.4
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• pp.391-397
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• 2006

We present investigations of a hybrid type superconducting fault current limiter (SFCL), which consists of transformers and resistive superconducting elements. The secondary windings of the transformer were separated into several electrically isolated circuits and linked inductively with each other by mutual flux, each of which has a superconducting current limiting element of $YBa_2Cu_3O_7$ (YBCO) stripes as a current limiting element. Simple connection in series of the SFCL elements tends to produce ill-timed quenching because of power dissipation unbalance between SFCL elements. Both electrical isolation and mutual flux linkage of the elements provides a solution to power dissipation unbalance, inducing simultaneous quench and current redistribution of the YBCO films. This design enables to increase the voltage rating of SFCL with given YBCO stripes.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.11
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• pp.1102-1111
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• 2007

The theory for a fault-tolerant control of homopolar magnetic bearings is developed. New coil winding law is utilized such that control fluxes are isolated for an 8-pole homopolar magnetic bearing. Decoupling chokes are not required for the fault tolerant magnetic bearing since C-core fluxes are isolated. If some of the coils or power amplifiers suddenly fail, the remaining coil currents change via a distribution matrix such that the same magnetic forces are maintained before and after failure. Lagrange multiplier optimization with equality constraints is utilized to calculate the optimal distribution matrix that maximizes the load capacity of the failed bearing. Some numerical examples of distribution matrices are provided to illustrate the theory. Simulations show that very much the same dynamic responses (orbits or displacements) are maintained throughout failure events while currents and fluxes change significantly.