• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1998-2008
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• 2020

Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.

• Journal of Internet of Things and Convergence
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• v.6 no.1
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• pp.39-43
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• 2020

The Internet of Things plays a role as an important element technology of the 4th Industrial Revolution. This study is currently developing intelligent cars with IT technology, and is at a time when the development of intelligent cars is active and network data communication is possible. However, security solutions are needed as security is still at a weak stage, which can be threatened by intrusions into the network from outside. In this paper, in order to improve security of intelligent cars without causing security problems, we will apply blockchain technology, propose biometric authentication techniques using users' biometric information, and continue to study them in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.139-151
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• 1997

An ATM switching system may be designed so that communications between processors of its control part can be performed via its switching network rather than a separate inter-processor communications (IPC) network. In such a system, there should be interfaces to convent IPC traffic from message format to cell format and vice versa, that is, mechanisms to perform the SAR (Segmentation And Reassembly) sublayer functions. In this paper, we concern the cell reassembly mechanism among them, mainly focussed on buffer management schemes. We consider a few alternatives to implement cell reassembly function block, namely, separated buffering, reserved buffering and shared buffering in this paper. In case of separated and reserved buffering, we employ a continuous time Markov chain for the performance evaluation of cell reassembly mechanism, judicially defining the states of the mechanism. Performance measures such as measage loss probability, mean number of message queued in buffer and average reassembly delay are obtianed in closed forms. In case of shared buffering, we compare the alternatives for implementing cell reassembly function block using simulation because it is almost impossible to analyze the mechanism of shared buffering by analytical modeling. Some illustrations are given for the performance analysis of the alternatives to implement cell reassembly function block.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.290-292
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• 2009

With advance in technologies for wireless sensor networks(WSNs), 2.4 GHz band has become gradually attractive due to increase in low-power wireless communication devices. Especially ZigBee(IEEE 802.15.4-based) technology whose frequency band includes the 2.4GHz industrial, scientific and medical band providing nearly worldwide availability has been universally applicable to a various remote monitoring system and applications related home network system. However network throughput of these systems is significantly deteriorated due to this ISM band is a license-exemption used in a variety of low-power wireless communication devices. For instance, other IEEE 802 wireless standards such as Bluetooth, WLAN, Wi-Fi and others cause radio interference to ZigBee. The experiments was carried out to analyze radio frequency interference between heterogeneous devices using ISM bands to improve the limited frequency utility factor. Finally this paper suggests a frequency hopping-based adaptive multi-channel methods to decrease interference with empirical results.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.1
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• pp.116-123
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• 2008

In the launch mission, mission control systems and tracking systems need time synchronization for data monitoring and data analysis. There are several standards for time synchronization and an adequate standard is selected according to the requirement of time accuracy and cost among time synchronization standards. Oscillators are used to maintain time accuracy. There are some kinds of oscillators with diverse characteristics and an adequate oscillator can be adopted according to time accuracy. In this paper, we will specify characteristics of several oscillators and standards generally used for time synchronization. And we will also introduce TSDN(time synchronization and display network) for time synchronization in Naro Space Center.

• IE interfaces
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• v.22 no.3
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• pp.205-213
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• 2009

Warfare information system is a core factor of future combat operation under NCW(Network centric Warfare) environment. In this paper, we proposed a new MOE(Measure of Effectiveness) that can assess the combat power synergistic effect of warfare information system in the theater-level joint fire operation. This new MOE uses the rule of Newton's second law($F=(m{\Delta}{\upsilon})/{\Delta}t{\Rightarrow}(M{\upsilon}I)/T$). Four factors considered in combat power evaluation are network power(M), movement velocity(v), information superiority(I), command and control time(T). We applied this new MOE to the JFOS-K(Joint Fire Operating System-Korea) to assess its combat power effect and compared with other's effects obtained from different MOE.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.23-30
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• 2001

Among the various welding conditions, the welding current that is inversely proportional to the tip-to-work-piece distance is an essential parameter as to monitor the GMAW process and to implement the welding automation. Considering the weld pool surface geometry including weld defects, it should modify the signal processing method for automatic seam tracking in horizontal fillet welding. To meet the above necessities, a mathematical model related with the weld pool geometry was proposed as in a conjunction with the two-dimensional heat flow analysis of the horizontal fillet welding. The signal processing method based on the artificial neural network (Adaptive Resonance Theory) was proposed for discriminating the sound weld pool surface from that with the weld defects. The reliability of the numerical model and the signal processing method proposed were evaluated through the experiments of which showed that they are effective for predicting the weld bead shape with or without the weld defects in a horizontal fillet welding.

• Journal of Welding and Joining
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• v.23 no.4
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• pp.41-47
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• 2005

Generally, the use of robots in manufacturing industry has been increased during the past decade. GMA(Gas Metal Arc) welding process is an actively Vowing area, and many new procedures have been developed for use with high strength alloys. One of the basic requirement for the automatic welding applications is to investigate relationships between process parameters and bead geometry. The objective of this paper is to develop a new approach involving the use of neural network and multiple regression methods in the prediction of bead geometry for GMA welding process and to develop an intelligent system that visualize bead geometry in order to employ the robotic GMA welding processes. Examples of the simulation for GMA welding process are supplied to demonstrate and verify the proposed system developed using MATLAB. The developed system could be effectively implemented not oかy for estimating bead geometry, but also employed to monitor and control the bead geometry in real time.

• Journal of the Korean Institute of Gas
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• v.9 no.2 s.27
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• pp.28-33
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• 2005

Because chemical industrial facilities deal with large amount of hazardous materials, the damage affect to off-site as well as on-site when an accident occurs. So it is necessary to develop a Risk Representation System for effective control and response to major accidents. In this study a Risk Representation System(S/W) was developed to help analyzing actual risk and to set an alternative that can reduce the analyzed risk by drawing the level of individual plant's risk on a digital map network.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.625-627
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• 2022

In the construction and development of modern industrial production technology, the traditional technology management mode is faced with many problems such as low qualification rates and high application costs. In the research, an improved workpiece defect detection method based on deep learning is proposed, which can control the application cost and improve the detection efficiency of irregular defects. Based on the research of the current situation of deep learning applications, this paper uses the improved Faster R-CNN network structure model as the core detection algorithm to automatically locate and classify the defect areas of the workpiece. Firstly, the robustness of the model was improved by appropriately changing the depth and the number of channels of the backbone network, and the hyperparameters of the improved model were adjusted. Then the deformable convolution is added to improve the detection ability of irregular defects. The final experimental results show that this method's average detection accuracy (mAP) is 4.5% higher than that of other methods. The model with anchor size and aspect ratio (65,129,257,519) and (0.2,0.5,1,1) has the highest defect recognition rate, and the detection accuracy reaches 93.88%.