• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.383-388
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• 2008

The safe and efficient operation of the chemical processes has become one of the primary concerns of chemical companies, and a variety of fault diagnosis methods have been developed to diagnose faults when abnormal situations arise. Recently, many research efforts have focused on fault diagnosis methods based on quantitative history data-based methods such as statistical models. However, when the history data-based models trained with the data obtained on an operation mode are applied to another operating condition, the models can make continuous wrong diagnosis, and have limits to be applied to real chemical processes with various operation modes. In order to classify operation modes of chemical processes, this study considers three multivariate models of Euclidean distance, FDA (Fisher's Discriminant Analysis), and PCA (principal component analysis), and integrates them with process dynamics to lead dynamic Euclidean distance, dynamic FDA, and dynamic PCA. A case study of the TE (Tennessee Eastman) process having six operation modes illustrates the conclusion that dynamic PCA model shows the best classification performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.3
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• pp.52-58
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• 2008

The importance of. identifying the causes of electrical faults cannot be overstated because of the accidents caused by over-current that take place at the home, the office and electrical facilities due to misuse, poor products and system faults. It is necessary to gather objective, scientific data pertaining to electrical fault investigation in a product liability(PL) environment. To date, no database(DB) has been built concerning the accurate cause analysis of faultyfacilities. In this paper, accident hazard and arc scattering when over-current flows in copper wire was investigated. It was found that when over-current flows in a copper wire, the copper wire became heated and bent and beads were scattered around the wire with a flash. It was determinedthat the fusing current and time was related to the current rise per second. For example, when the current rise per second was largethe fusing current was higher than when the current rise per second was small, and the beads dispersed along a wide area. Fusing time, however, was shorter. The possibility of electrical fault became highest when the fusing current was higher. As the current rise per second is short, the dendrite structure is distributed in the surface of the copper wire. These experimental results can be utilized for a fault process DB system in the investigation and the prevention of electrical faults.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.335-342
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• 2013

In this study, reliability software cost model considering logarithmic fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software cost model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. In this research, Software developers to identify the best time to release some extent be able to help is considered.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.275-284
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• 2016

The software used in the nuclear safety field has been ensured through the development, validation, safety analysis, and quality assurance activities throughout the entire process life cycle from the planning phase to the installation phase. However, this evaluation through the development and validation process needs a lot of time and money, and there are limitations to ensure that the quality is improved enough. Therefore, the effort to calculate the reliability of the software continues for a quantitative evaluation instead of a qualitative evaluation. In this paper, we propose a reliability evaluation method for the software to be used for a specific operation of the digital controller in a nuclear power plant. After injecting weighted faults in the internal space of a developed controller and calculating the ability to detect the injected faults using diagnostic software, we can evaluate the software reliability of a digital controller in a nuclear power plant.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.29-35
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• 2019

The structure of the machinery industry due to the 4th industrial revolution is changing from precision and durability to intelligent and smart machinery through sensing and interconnection(IoT). There is a growing need for research on prognostics and health management(PHM) that can prevent abnormalities in processing machines and accurately predict and diagnose conditions. PHM is a technology that monitors the condition of a mechanical system, diagnoses signs of failure, and predicts the remaining life of the object. In this study, the vibration generated during machining is measured and a classification algorithm for normal and fault signals is developed. Arbitrary fault signal is collected by changing the conditions of un stable supply cutting oil and fixing jig. The signal processing is performed to apply the measured signal to the learning model. The sampling rate is changed for high speed operation and performed machine learning using raw signal without FFT. The fault classification algorithm for 1D convolution neural network composed of 2 convolution layers is developed.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.605-614
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• 2021

Water inrush from fault is one of the most severe hazards during tunnel excavation. However, the traditional evaluation methods are deficient in both quantitative evaluation and uncertainty handling. In this paper, a comprehensive methodology method combined intuitionistic fuzzy AHP with a Bayesian network for the risk assessment of water inrush from fault in the subsea tunnel was proposed. Through the intuitionistic fuzzy analytic hierarchy process to replace the traditional expert scoring method to determine the prior probability of the node in the Bayesian network. After the field data is normalized, it is classified according to the data range. Then, using obtained results into the Bayesian network, conduct a risk assessment with field data which have processed of water inrush disaster on the tunnel. Simultaneously, a sensitivity analysis technique was utilized to investigate each factor's contribution rate to determine the most critical factor affecting tunnel water inrush risk. Taking Qingdao Kiaochow Bay Tunnel as an example, by predictive analysis of fifteen fault zones, thirteen of them are consistent with the actual situation which shows that the IFAHP-Bayesian Network method is feasible and applicable. Through sensitivity analysis, it is shown that the Fissure development and Apparent resistivity are more critical comparing than other factor especially the Permeability coefficient and Fault dip. The method can provide planners and engineers with adequate decision-making support, which is vital to prevent and control tunnel water inrush.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.20-27
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• 2000

A chatter vibration and a workpiece burn are the main phenomena to be monitored in modern grinding processes. This study describes a trouble diagnosis of the cylindrical plunge grinding process using the power and acoustic emission (AE) signals. The raw signals of the power and the AE occurred during the grinding operation were sampled and analyzed to determine the relationship between each fault and change of signals. A neural network that has a high success rate of the fault detection was used. Furthermore, an analysis on the influence of parameters to the chatter vibration and the grinding burn was conducted.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.9
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• pp.1351-1363
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• 1990

In this paper, a reliable control system structured with dual CPU modules and dual I/O modules is implemented as a means of achieving a highly reliable fault tolerant control system. For this, faults in the system modules are first examined, and a fault detection technique consisting of self diagnostic, comparison process, and exception processing is applied. Self diagnostic is used to locate which components in the modules have been failed, while comparison process is to cmpare control outputs computed by both CPU modules and protect the plant from malfunction by blocking failed control outputsin advance. Finally exception processing is used to determine the faults that are not detected immediately by the self diagnostic and comparison process, e.g. bus error processing when acknowledge signal for data transfer is not activeted in the I/O modules. Also reliability analysis is conducted for the discrete time Markov model with dual structure. It is shown quantitatively that the reliability is improved in the control system with dual structure in comparison with a system with single module structure.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.170-178
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• 2011

In general, a software fault detection phenonenon is described by a software reliability model based on a nonhomogeneous Poisson process(NHPP). In this paper, we propose a software reliability growth model considering the differences of the software environments in both the testing phase and the operational phase. Also, we consider the problem of determining the optimal release time and the optimal warranty period that minimize the total expected software cost which takes account of periodic software maintenance(e.g. patch, update, etc). Finally, we analyze the sensitivity of the optimal release time and warranty period based on the fault data observed in the actual testing process.

• Earthquakes and Structures
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• v.14 no.5
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• pp.399-409
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• 2018

The dynamic response and seismic damage of single-layer reticulated shells in the near field of a rupturing fault can be different from those in the far field due to the different characteristics in the ground motions. To investigate the effect, the dynamic response and seismic damage of this spatial structures subjected to two different ground motions were numerically studied by nonlinear dynamic response analysis. Firstly, twelve seismic waves with an apparent velocity pulse, including horizontal and vertical seismic waves, were selected to represent the near-fault ground motion characteristics. In contrast, twelve seismic records recorded at the same site from other or same events where the epicenter was far away from the site were employed as the far-fault ground motions. Secondly, the parametric modeling process of Kiewitt single-layer reticulated domes using the finite-element package ANSYS was described carefully. Thirdly, a nonlinear time-history response analysis was carried out for typical domes subjected to different earthquakes, followed by analyzing the dynamic response and seismic damage of this spatial structures under two different ground motions based on the maximum nodal displacements and Park-Ang index as well as dissipated energy. The results showed that this spatial structures in the near field of a rupturing fault exhibit a larger dynamic response and seismic damage than those obtained from far-fault ground motions. In addition, the results also showed that the frequency overlap between structures and ground motions has a significant influence on the dynamic response of the single-layer reticulated shells, the duration of the ground motions has little effects.