• Nuclear Engineering and Technology
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• v.50 no.3
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• pp.396-410
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• 2018

To assist operators to properly assess the current situation of the plant, accurate fault diagnosis methodology should be available and used. A reliable fault diagnosis method is beneficial for the safety of nuclear power plants. The major idea proposed in this work is integrating the merits of different fault diagnosis methodologies to offset their obvious disadvantages and enhance the accuracy and credibility of on-line fault diagnosis. This methodology uses the principle component analysis-based model and multi-flow model to diagnose fault type. To ensure the accuracy of results from the multi-flow model, a mechanical simulation model is implemented to do the quantitative calculation. More significantly, mechanism simulation is implemented to provide training data with fault signatures. Furthermore, one of the distance formulas in similarity measurement-Mahalanobis distance-is applied for on-line failure degree evaluation. The performance of this methodology was evaluated by applying it to the reactor coolant system of a pressurized water reactor. The results of simulation analysis show the effectiveness and accuracy of this methodology, leading to better confidence of it being integrated as a part of the computerized operator support system to assist operators in decision-making.

• Journal of International Society for Simulation Surgery
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• v.1 no.2
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• pp.95-98
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• 2014

Two-dimensional cephalometric analysis has been used for diagnosis and treatment of correction of mandibular asymmetry by many maxillofacial surgeons. And 2D analysis showed excellent results in many cases, however 2D has some drawbacks in diagnosis and treatment planning because of its fundamental limitation like overlapping. Today many physicians use 3D diagnosis & treatment tools to expect better results and reduce possible errors. The aim of this report is to present treatment procedures using 3D analysis and treatment modalities for mandibular asymmetry patients.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.437-450
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• 1994

The problem of testing for a change in the parameter of a stochastic process is particularly important in simulation studies. In studies of the steady state characteristics of a simulation model, it is important to identify initialization bias and to evaluate efforts to control this problem. A simulation output have the characteristics of chaotic behavior because of sensitive dependence on initial conditions. For that reason, we will apply Lyapunov exponent for diagnosis of chaotic motion to simulation output analysis. This paper proposes two methods for diagnosis of steady state in simulation output. In order to evaluate the performance and effectiveness of these methods using chaos theory, M/M/I(.inf.) queueing model is used for testing point estimator, average bias.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• Journal of International Society for Simulation Surgery
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• v.3 no.2
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• pp.69-73
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• 2016

Traditionally 2D cephalometric analysis has been used for diagnosis and treatment of maxillofacial deformities. However, 2D has some limitations in diagnosis and treatment planning especially facial asymmetry cases. The most weakness of 2D is overlapping and unpredictability. Today 3D treatment tools are used by many maxillofacial surgeons. 3D treatment tools can show ungarbled facial anatomy and do virtual surgery. The aim of this report is to present usefulness of using 3D analysis and virtual orthognathic surgery for severe facial asymmetry patients.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.553-571
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• 2019

Geometric variation including welding distortion accumulates as many parts are joined together, ultimately affecting the final product. This variation is then subjected to correction, which requires considerable effort, time, and cost. This variation can be categorized as in-plane/out-of-plane variation. To date, studies on variation simulation have largely focused on the out-of-plane variation, however the variation generated in the in-plane direction requires more time and efforts to correct afterwards. This research aims to construct a variation simulation model considering both the in-plane and out-of-plane variations. A geometric analysis was performed to derive an equation that reflects the coupling effect of the out-of-plane variation on the in-plane variation. The proposed model is validated with case study analysis and the results shows that good fidelity in predicting and diagnosing the in-plane variation during the block assembly process considering welding distortion.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.2
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• pp.253-259
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• 2006

There is few study which automatically diagnoses the fault from ship's monitored data. The bigger control and monitoring system is. the more important fault diagnosis and maintenance is to reduce damage caused by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault from monitored data and is composed of fault detection knowledge base and fault diagnosis knowledge base. For all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem, To verify capability of fault detection, diagnosis and prediction, FMS(Fault Management System) is developed by C++. Simulation by FMS is carried out with population data set made by the log book data of 2 months duration from a large full container ship of H shipping company.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.251-256
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• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Tribology and Lubricants
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• v.3 no.1
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• pp.52-60
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• 1987

Many kinds of condition monitoring technique as the preventive maintenance technique have been studied, so this study has investigated the possibility of chbcking the trend in the fault diagnosis of ball bearing, one of the important elements of rotating machine, by applying the cepstral analysis method. And computer simulation is conducted in order to identify obviously the physical meaning of cepstral analysis. It is identified that cepstral analysis is effective method to distinguish between the basic and reflected wave by computer simulation, and we know that it is possible to apply the cepstral analysis to the arbitrary elements of rotating machine which are different in fundamental frequency. It is verified that cepstral analysis method is more effective than the other conventional method in bearing fault diganosis.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.836-841
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• 1987

Many kinds of conditioning monitoring technique have been studied, so this study has investigated the possibility of checking the trend in the fault diagnosis of ball bearing, one of the elements of rotating machine, by applying the cepstral analysis method using the adaptive noise cancelling (ANC) method. And computer simulation is conducted in oder to identify obviously the physical meaning of ANC. The optimal adaptation gain in adaptive filter is estimated, the performance of ANC according to the change of the signal to noise ratio and convergence of LMS algorithm is considered by simulation. It is verified that cepstral analysis using ANC method is more effective than the conventional cepstral analysis method in bearing fault diagnosis.