• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.5-10
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• 2015

With the advance of ICT, understanding the condition of network and analysing network monitoring have become an important issue. On the TCP/IP network, SNMP is the typical protocol that catches the condition of network by using polling method. If polling method is implemented for a long period, to catch the change of the condition of the network is not easy. On the other hand, in case of short-term polling, even if it could catch the condition of the network in real time, responsive messages to results of the polling cause the increase of traffic and therefore burden the network. There have been studies to control the overhead of responsive messages by controlling the polling period. However, not considering the characteristics of an agent, and running randomly, they cannot decrease the overhead although they would have an instant effect. This paper suggests an efficient polling method that decreases the traffic overhead of polling and catches the condition of the network in real time. Proposed method an polling for a short period and gave weight based on the characteristics of agents to catch the network condition, and a manager decided polling differentially based on the weight so that it decreased the overhead of polling traffic.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.6
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• pp.505-513
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• 2018

Main engine failures in ship operations can lead to a major damage in terms of the vessel itself and the financial cost. In this respect, monitoring of a vessel's main engine condition is crucial in ensuring the vessel's performance and reducing the maintenance cost. The collection of a huge amount of vessel operational data in the maritime industry has never been easier with the advent of advanced data collection technologies. Real-time monitoring of the condition of a vessel's main engine has a potential to create significant value in maritime industry. This study presents a case study on the establishment of upper control limit to detect vessel's main engine failures using multivariate control chart. The case study uses sample data of an ocean-going vessel operated by a major marine services company in Korea, collected in the period of 2016.05-2016.07. This study first reviews various main engine-related variables that are considered to affect the condition of the main engine, and then attempts to detect abnormalities and their patterns via multivariate control charts. This study is expected to help to enhance the vessel's availability and provide a basis for a condition-based maintenance that can support proactive management of vessel's main engine in the future.

• Smart Structures and Systems
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• v.29 no.1
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• pp.41-51
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• 2022

Cables are critical components of cable-stayed bridges. A structural health monitoring system provides real-time cable tension recording for cable health monitoring. However, the measurement data involve multiple sources of variability, i.e., varying environmental and operational factors, which increase the complexity of cable condition monitoring. In this study, a one-class classification method is developed for cable condition assessment using Bayesian factor analysis (FA). The single-peaked vehicle-induced cable tension is assumed to be relevant to vehicle positions and weights. The Bayesian FA is adopted to establish the correlation model between cable tensions and vehicles. Vehicle weights are assumed to be latent variables and the influences of different transverse positions are quantified by coefficient parameters. The Bayesian theorem is employed to estimate the parameters and variables automatically, and the damage index is defined on the basis of the well-trained model. The proposed method is applied to one cable-stayed bridge for cable damage detection. Significant deviations of the damage indices of Cable SJS11 were observed, indicating a damaged condition in 2011. This study develops a novel method to evaluate the health condition of individual cable using the FA in the Bayesian framework. Only vehicle-induced cable tensions are used and there is no need to monitor the vehicles. The entire process, including the data pre-processing, model training and damage index calculation of one cable, takes only 35 s, which is highly efficient.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.271-276
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• 2009

An local area weather condition monitoring system to minimize many disasters from the sudden change of weather condition in local and mountain area is proposed. Firstly, the comparison of present state of the related monitoring systems and the possibility of realization with some merits are investigated. Moreover, this paper present direction of local area weather condition monitoring system based on integration of wireless sensor network and CDMA network following some case study. Through the efficient integration of both networks, the measured weather condition data from sensors can be transmitted to the server or mobile to monitor with high reliability. The proposed monitoring system will guide new type of project in wireless sensor network and support alarm service of the sudden change of weather condition to mobile user from central official regulations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.161-167
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• 2020

In the process of cutting large aircraft parts, the tool may be abnormally worn or damaged due to various factors such as mechanical vibration, disturbances such as chips, and physical properties of the workpiece, which may result in deterioration of the surface quality of the workpiece. Because workpieces used for large aircrafts parts are expensive and require strict processing quality, a maintenance plan is required to minimize the deterioration of the workpiece quality that can be caused by unexpected abnormalities of the tool and take maintenance measures at an earlier stage that does not adversely affect the machining. In this paper, we propose a method to indirectly monitor the tool condition that can affect the machining quality of large aircraft parts through real-time monitoring of the current signal applied to the spindle motor during machining by comparing whether the monitored current shows an abnormal pattern during actual machining by using this as a reference pattern. First, 30 types of tools are used for machining large aircraft parts, and three tools with relatively frequent breakages among these tools were selected as monitoring targets by reflecting the opinions of processing experts in the field. Second, when creating the CNC machining program, the M code, which is a CNC auxiliary function, is inserted at the starting and ending positions of the tool to be monitored using the editing tool, so that monitoring start and end times can be notified. Third, the monitoring program was run with the M code signal notified from the CNC controller by using the DAQ (Data Acquisition) device, and the machine learning algorithms for detecting abnormality of the current signal received in real time could be used to determine whether there was an abnormality. Fourth, through the implementation of the prototype system, the feasibility of the method proposed in this paper was shown and verified through an actual example.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.5
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• pp.835-841
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• 1997

Microscopic examination of the morphology of wear debris is an accepted method for machine condition and fault diagnosis. However wear particle analysis has not been widely accepted in industry because it is dependent on expert interpretation of particle morphology and subjective assessment criteria. This paper was undertaken to analyze the morphology of wear debris for machine condition diagnosis of the lubricated moving surfaces by image processing and analysis. The lubricating wear test was performed under different sliding conditions using a wear test device made in our laboratory and wear testing specimen of the pin-on-disk-type was rubbed in paraffine series base oil. In order to describe characteristics of debris of various shape and size, four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) have been developed and outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring, thus to overcome many of the difficulties in current methods and to facilitate wider use of wear particle analysis in machine condition monitoring.

• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.129-150
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• 2018

This paper presents the structural performance monitoring of an urban footbridge located in Hangzhou, China. The structural health monitoring (SHM) system is designed and implemented for the footbridge to monitor the structural responses of the footbridge and to ensure the structural safety during the period of operation. The monitoring data of stress and displacement measured by the fiber Bragg grating (FBG)-based sensors installed at the critical locations are used to analyze and assess the operation performance of the footbridge. A linear regression method is applied to separate the temperature effect from the stress monitoring data measured by the FBG-based strain sensors. In addition, the static vertical displacement of the footbridge measured by the FBG-based hydrostatic level gauges are presented and compared with the dynamic displacement remotely measured by a machine vision-based measurement system. Based on the examination of the monitored stress and displacement data, the structural safety evaluation is executed in combination with the defined condition index.

• Proceedings of the KIEE Conference
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• 2001.11a
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• pp.224-226
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• 2001

In this paper, a novel high-voltage motor monitoring system (HVMMS) is proposed. This system monitors the insulation condition of the stator winding by on-line measurements of partial discharge (PD). Sensor, EMC (Epoxy-Mica Coupler) is used for PD measurement PD signals are continuously measured and digitized with a peak-hold A/D converter to build the database of the high-voltage motor's insulation condition. Also, this system can communicate with the central monitoring system via RS-485. This helps more efficient operation and maintenance of the generator.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.6
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• pp.648-660
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• 2012

Reliable response measurements are extremely important for proper bridge health monitoring but incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In the case of a sensor malfunction, parts of the measured data can be missing so that the structural health condition cannot be monitored reliably. This means that the dynamic characteristics of natural frequencies can change as if the structure is damaged due to environmental effects, such as temperature variations. To overcome these problems, this paper proposes a systematic procedure of data analysis to recover missing data and eliminate the environmental effects from the measured data. It also proposes a health index calculated statistically using revised data to evaluate the health condition of a bridge. The proposed method was examined using numerically simulated data with a truss structure and then applied to a set of field data measured from a cable-stayed bridge.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.92-96
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• 2011

In this paper, in order to reduce the electrical disaster such as electrical fire at traditional markets, we need to develop the ESMS(electrical safety monitoring system) which is able to monitor the power status of electrical equipments. Therefore, for solving the those problems, we developed the detection censor(ZCT, CT) and equipment of data analysis and transmission. The detection censor and equipment are able to monitor the electrical equipments condition(over current, leakage current, arc, etc.). We constructed Test-Bed for testing reliability of the ESMS and obtained certification. And we tested the over current, leakage current and arc under the normal condition.