• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1527-1534
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• 2016

Online voltage stability monitoring using real-time measurements is one of the most important tasks in a smart grid system to maintain the grid stability. Loading margin is a good indicator for assessing the voltage stability level. This paper presents an Extreme Learning Machine (ELM) approach for estimation of voltage stability level under credible contingencies using real-time measurements from Phasor Measurement Units (PMUs). PMUs enable a much higher data sampling rate and provide synchronized measurements of real-time phasors of voltages and currents. Depth First (DF) algorithm is used for optimally placing the PMUs. To make the ELM approach applicable for a large scale power system problem, Mutual information (MI)-based feature selection is proposed to achieve the dimensionality reduction. MI-based feature selection reduces the number of network input features which reduces the network training time and improves the generalization capability. Voltage magnitudes and phase angles received from PMUs are fed as inputs to the ELM model. IEEE 30-bus test system is considered for demonstrating the effectiveness of the proposed methodology for estimating the voltage stability level under various loading conditions considering single line contingencies. Simulation results validate the suitability of the technique for fast and accurate online voltage stability assessment using PMU data.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.83-86
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• 2015

In this paper, we propose a real-tim measurement management system UI development linked the Water treatment facilities broadband Convergence Network. The sensor and the image data received by the server develop a program to interact with Web through water treatment facilities broadband convergence network. So, Separately develop UI capable of independently operating. Building a web server for remote monitoring of the transmission sensor and the image data. And Monitoring and control is possible the sensor data and image data through the Web-based UI. We can grasp the current state such as measurement time, concentration and depth of interface through the proposed real-time measurement management system UI development liked the water treatment facilities broadband convergence network. So, we can check in whether the normal operation of water treatment facilities and whether the casualties such as fire and security. As well as real time to see the information at a glance due to UI development can be raal-time monitoring of real-time measurement management system.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.77-79
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• 2000

Industrial communication networks have attracted much attention in the area of decentralized control systems for factory automation and computer integrated manufacturing. In this paper, we investigate the rate-based traffic control of industrial communication networks employing LonWorks to improve the performance measures of throughput, fairness, and error rates. To this end, we utilize the Feedback channel information through the additional network monitoring node and make the overall system closed-loop. We demonstrate the improved performance of the controlled network system by the experimentation upon an implemented lab-scale network system.

• Journal of Integrative Natural Science
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• v.10 no.4
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• pp.232-239
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• 2017

The researcher set up multiple sensor units on the road slope such as national highway and highway where there is a possibility of loss, and using the acceleration sensor built into the sensor unit the researcher will sense whether the inclination of the road slope occur in real time, and Based on the sensed data, the researcher tries to implement a system that detects collapse of road slope and dangerous situation. In the experiment of measuring the error between the actual measurement time and the judgment time of the monitoring system when judging the warning of the sensor and falling rock detection by using the acceleration sensor, the error between measurement time and the judgment time at the sensor warning was 0.34 seconds on average, and an error between measurement time and judgment time at falling rock detection was 0.21 seconds on average. The error is relatively small, the accuracy is high, and thus the change of the slope can be clearly judged.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.57.4-57
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• 2001

Polishing a die that has free-form surfaces is a time-consuming and tedious job, and requires a considerable amount of high-precision skill. Some workers tend to gradually avoid the polishing work because of the poor working conditions caused by dust and noise. In the our previous study, an automatic polishing system was developed to reduce the polishing time and cope with the shortage of skilled workers. And, to operate the polishing robot system from remote sites, communication network was constructed and monitoring programs (a server program and a client program)) were developed. However, to monitor polishing process in remote sites, users have to install monitoring programs in a client PC. Thus, user can only operate the polishibg system ...

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.1-12
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• 2008

Home network is a technology that provides possibilities of monitoring/controling/mutilating-recognition between optional home network machines in residences. Currently, home network or other networks like entertainment, residential electronic networks are jumbled together with heterogeneous networks in a rampaging condition. In a reality of high expectation for home networks system like the mutual application for various machines, we are required to have the unification technology for conveniences to satisfy expectations. This thesis reflects how to develop Java applications or mutual products based on convenient interfaces actually that process various sensors which create real time data stream in Java platform through Java based sensor data-stream processing embedded middleware design and realization in real time.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.136-141
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• 2021

Research on wireless sensor networks has focused on the monitoring and characterization of large-scale physical environments and the tracking of various environmental or physical conditions, such as temperature, pressure, and wind speed. We propose a stochastic mobility model that can be applied to a MANET (Mobile Ad-hoc NETwork). environment, and apply this mobility model to a newly proposed clustering-based routing protocol. To verify its stability and durability, we compared the proposed stochastic mobility model with a random model in terms of energy efficiency. The FND (First Node Dead) was measured and compared to verify the performance of the newly designed protocol. In this paper, we describe the proposed mobility model, quantify the changes to the mobile environment, and detail the selection of cluster heads and clusters formed using a fuzzy inference system. After the clusters are configured, the collected data are sent to a base station. Studies on clustering-based routing protocols and stochastic mobility models for MANET applications have shown that these strategies improve the energy efficiency of a network.

• Journal of the Korean Society of Systems Engineering
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• v.13 no.2
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• pp.9-17
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• 2017

Concept development of a real-time Field Programmable Gate Array (FPGA)-based switched Ethernet data communication network for the Man-Machine Interface System (MMIS) is presented in this paper. The proposed design discussed in this research is based on the systems engineering (SE) approach. The design methodology is effectively developed by defining the concept development stage of the life-cycle model consisting of three successive phases, which are developed and discussed: needs analysis; concept exploration; and concept definition. This life-cycle model is used to develop an FPGA-based time-triggered Ethernet (TTE) switched data communication network for the non-safety division of MMIS system to provide real-time data transfer from the safety control systems to the non-safety division of MMIS and between the non-safety systems including control, monitoring, and information display systems. The original IEEE standard 802.3 Ethernet networks were not typically designed or implemented for providing real-time data transmission, however implementing a network that provides both real-time and on-demand data transmission is achievable using the real-time Ethernet technology. To develop the design effectively, context diagrams are implied. Conformance to the stakeholders needs, system requirements, and relevant codes and standards together with utilizing the TTE technology are used to analyze, synthesize, and develop the MMIS non-safety data communication network of the APR1400 nuclear power plant.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2676-2689
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• 2013

Due to increased consumption of energy in the building environment, the building energy management systems (BEMS) solution has been developed to achieve energy saving and efficiency. However, because of the shortage of building energy management specialists and incompatibility among the energy management systems of different vendors, the BEMS solution can only be applied to limited buildings individually. To solve these problems, we propose a building cluster based remote energy monitoring and management (EMM) system and its functionalities and roles of each sub-system to simultaneously manage the energy problems of several buildings. We also introduce a novel energy demand forecasting algorithm by using past energy consumption data. Extensive performance evaluation study shows that the proposed regression based energy demand forecasting model is well fitted to the actual energy consumption model, and it also outperforms the artificial neural network (ANN) based forecasting model.