• Journal of Korea Multimedia Society
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• 제25권2호
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• pp.197-205
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• 2022

The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.

• Applied Science and Convergence Technology
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• 제26권6호
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• pp.157-163
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• 2017

Immobilized enzymes have become the subject of considerable interest due to their excellent functional properties such as reusability, cost-effectiveness, and optimality during the past decades. Enzyme immobilization technology is not only used in industrial processes, but also a component technology of products for medical diagnostics, therapy, food industry, bio energy, and biomaterial detection. In this review, new methods for enzyme immobilization are introduced, and the advantages and disadvantages of a variety of techniques in enzyme immobilization will be also discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.692-695
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• 2000

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2009년도 추계학술대회 논문집
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• pp.558-559
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• 2009

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.98-101
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• 2009

Recently, there is use of the vehicle network for vehicle diagnostic method and Increased use of the vehicle protocol such as (CAN(Controller Area Network), MOST, LIN, FlexRay), Distributed control and data about the vehicle are being sought methods for real-time observation and monitoring and trend tends to have gone into this. In this case of automotive diagnostic module in today, there is Primarily to use DLC(Data Link Connector)Connector called self-check terminal. Generally, vehicle Diagnoses to use DLC Connector such as OBD2(On Board Diagnostics) Through Diagnostic Module(scanner). But there limit diagnostic as engine and powertrain part, and not consider user's perspective In this paper, By designing Vehicle diagnostic monitoring system using Ethernet Port, transmit and Receives CAN protocol vehicle data, and implement Easily monitoring system that provide and Diagnoses to provide vehicle's state and information to use PC.

• Smart Structures and Systems
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• 제5권4호
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• pp.457-468
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• 2009

A novel approach for integrating active sensing data interrogation algorithms for structural health monitoring (SHM) applications is presented. These algorithms cover Lamb wave propagation, impedance methods, and sensor diagnostics. Contrary to most active-sensing SHM techniques, which utilize only a single signal processing method for damage identification, a suite of signal processing algorithms are employed and grouped into one package to improve the damage detection capability. A MATLAB-based user interface, referred to as HOPS, was created, which allows the analyst to configure the data acquisition system and display the results from each damage identification algorithm for side-by-side comparison. By grouping a suite of algorithms into one package, this study contributes to and enhances the visibility and interpretation of the active-sensing methods related to damage identification. This paper will discuss the detailed descriptions of the damage identification techniques employed in this software and outline future issues to realize the full potential of this software.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 한국전기전자재료학회 2007년도 하계학술대회 논문집 Vol.8
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• pp.525-526
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• 2007

Continuous on-line temperature monitoring provides the means to evaluate current condition of equipment and detect abnormality. It allows corrective measures to be taken to prevent upcoming failure. Continuous temperature monitoring and event recording provides information on the energized equipment's response to normal and emergency conditions. On-line temperature monitoring helps to coordinate equipment specifications and ratings, determine the real limits of the monitored equipment and optimize facility operations. Using wireless technique eliminates any need for special cables and wires with lower installation costs if compared to other types of online condition monitoring equipment. In addition, wireless temperature monitoring works well under difficult conditions in strategically important locations. Wireless technology for on-line condition monitoring of energized equipment is applicable both as standalone system and with an interface with power quality monitoring system.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 한국추진공학회 2003년도 제21회 추계학술대회 논문집
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• pp.267-270
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• 2003

An intelligent performance diagnostic computer program of a gas turbine using the NN(Neural Network) was developed. Recently on-condition performance monitoring of major gas path components using the GPA(Gas Path Analysis) method has been performed in analyzing of engine faults. However because the types and severities of engine faults are various and complex, it is not easy that all fault conditions of the engine would be monitored only by the GPA approach. Therefore in order to solve this problem, application of using the NNs for learning and diagnosis would be required. Among then, a BPN (Back Propagation Neural Network) with one hidden layer, which can use an updating learning rate, was proposed for diagnostics of PT6A-62 turboprop engine in this work.

• Composites Research
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• 제28권4호
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• pp.148-154
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• 2015

In order to detect damage in early stages and properly maintaining structures, the structural health monitoring technology is employed. In most cases, active-sensing SHM needs many piezoelectric (PZT) sensors and actuators. Thus, if there is a defect on PZT used for active-sensing SHM, the structural status could be misclassified. This study, for reliable SHM performance, investigated to detect defects of sensors by using the admittance-based sensor diagnostics. This study also introduced an algorithm that can diagnose sensor defects based only on data measured from the sensors in case that information about the changes in adhesive and environmental investigation, this study confirms that the proposed algorithm could be efficiently applied to real-world structures in which a significant temperature variation could take place.

• Smart Structures and Systems
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• 제7권3호
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.