• Title/Summary/Keyword: Network Performance Monitoring

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LonWorks-based Distributed Monitoring and Control for Predictive Maintenance (PM)

  • Park, Gi-Heung
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.150.3-150
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    • 2001
  • Requirements for Distributed Monitoring and Control Networks (DMCN) differ greatly from those of typical data networks. Specifically, any DMCN technology which employs a fieldbus protocol is different from If network protocol TCP/IP. In general, one needs to integrate fieldbus protocol and TCP/IP to realize DMCN over IP network or internet Interoperability between devices and equipments is essential to enhance the quality and the performance of predictive maintenance (PM). This paper suggests a basic framework for LonWorks-based DMCN over IP network and a method to guarantee interoperability between devices and equipments.

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Efficient Crossroad Wireless LAN Vehicular Communication Network for Remote Driving and Monitoring Autonomous Vehicle (무인자동차 원격운행 및 모니터링을 위한 효율적인 사거리 교차로 무선랜 자동차통신망)

  • Jo, Jun-Mo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.9 no.3
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    • pp.387-392
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    • 2014
  • Now a days, there are various application functions to transmit from vehicles to the Internet and vice versa. And the communication can be operated through a roadside infrastructure including with possible use of routing protocols. Specifically, autonomous vehicles for remote driving and monitoring requires transmitting of high depth of multimedia such as video. Especially in a populated urban area, an efficient network is vital because of handling a great amount of the data. Therefore, in this paper, efficient network topology for a crossroad in urban area is suggested by performance evaluation of vehicular networks using a wireless LAN and a routing protocol. For the performance evaluation, various vehicular network topologies are designed and simulated in OPNet simulator.

Structural health monitoring data anomaly detection by transformer enhanced densely connected neural networks

  • Jun, Li;Wupeng, Chen;Gao, Fan
    • Smart Structures and Systems
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    • v.30 no.6
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    • pp.613-626
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    • 2022
  • Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

Performance Comparisons of Wavelet Based T2-Test and Neural Network in Monitoring Process Profiles (공정프로파일 모니터링에서 웨이블릿기 반 T2-검정과 신경회로망의 성능비교)

  • Kim, Seong-Jun;Choi, Deok-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.6
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    • pp.737-745
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    • 2008
  • Recent developments of process and measurement technology bring much interest to the online monitoring of process operations such as milling, grinding, broaching, etc. The objective of online monitoring systems is to detect process changes as early as possible. This is helpful in protecting facilities against unexpected failures and then preventing unnecessary loss. This paper investigates, when the process monitoring data are obtained as a profile, the monitoring performances of a statistical $T^2$-statistic and a feedforward neural network by using a wavelet transform. Numerical experiments using cutting force data presented by Axinte show that the proposed wavelet based $T^2$-test has an acceptable power in detecting profile changes. However, its operating characteristic is very sensitive to autocorrelation. On the contrary, compared with $T^2$-test, the neural network has more stable performance in the presence of autocorrelation. This indicates that an adaptive feature to analyze noises should be incorporated into the wavelet based $T^2$-test.

Development of On-line Performance Diagnostic Program of a Helicopter Turboshaft Engine

  • Kong, Chang-Duk;Koo, Young-Ju;Kho, Seong-Hee;Ryu, Hye-Ok
    • International Journal of Aeronautical and Space Sciences
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    • v.10 no.2
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    • pp.34-42
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    • 2009
  • Gas turbine performance diagnostics is a method for detecting, isolating and quantifying faults in gas turbine gas path components. On-line precise fault diagnosis can promote greatly reliability and availability of gas turbine in real time operation. This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module are used for reducing computer calculating time and a signal generation module for simulating real time performance data. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. Evaluation of the proposed on-line diagnostic program is performed through application to the helicopter engine health monitoring.

Application of Principal Components Analysis Method to Wireless Sensor Network Based Structural Monitoring Systems

  • Congyi, Zhang;Mission, Jose Leo;Kim, Sung-Ho;Youk, Yui-Su;Kim, Hyeong-Joo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.1
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    • pp.11-17
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    • 2008
  • Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.

Performance Analysis of Monitoring Process using the Stochastic Model (추계적 모형을 이용한 모니터링 과정의 성능 분석)

  • 김제숭
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.17 no.32
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    • pp.145-154
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    • 1994
  • In this paper, monitoring processor in a circuit switched network is considered. Monitoring processor monitors communication links, and offers a grade of service in each link to controller. Such an information is useful for an effective maintenance of system. Two links with nonsymmetric system Parameters are considered. each link is assumed independent M/M/1/1 type. The Markov process is introduced to compute busy and idle portions of monitoring processor and monitored rate of each link. Inter-idle times and inter-monitoring times of monitoring processor between two links are respectively computed. A recursive formula is introduced to make computational procedure rigorous.

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Full-scale bridge expansion joint monitoring using a real-time wireless network

  • Pierredens Fils;Shinae Jang;Daisy Ren;Jiachen Wang;Song Han;Ramesh Malla
    • Structural Monitoring and Maintenance
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    • v.9 no.4
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    • pp.359-371
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    • 2022
  • Bridges are critical to the civil engineering infrastructure network as they facilitate movement of people, the transportation of goods and services. Given the aging of bridge infrastructure, federal officials mandate visual inspections biennially to identify necessary repair actions which are time, cost, and labor-intensive. Additionally, the expansion joints of bridges are rarely monitored due to cost. However, expansion joints are critical as they absorb movement from thermal effects, loadings strains, impact, abutment settlement, and vehicle motion movement. Thus, the need to monitor bridge expansion joints efficiently, at a low cost, and wirelessly is desired. This paper addresses bridge joint monitoring needs to develop a cost-effective, real-time wireless system that can be validated in a full-scale bridge structure. To this end, a wireless expansion joint monitoring was developed using commercial-off-the-shelf (COTS) sensors. An in-service bridge was selected as a testbed to validate the performance of the developed system compared with traditional displacement sensor, LVDT, temperature and humidity sensors. The short-term monitoring campaign with the wireless sensor system with the internet protocol version 6 over the time slotted channel hopping mode of IEEE 802.15.4e (6TiSCH) network showed reliable results, providing high potential of the developed system for effective joint monitoring at a low cost.

Chromatic Dispersion Monitoring of CSRZ Signal for Optimum Compensation Using Extracted Clock-Frequency Component

  • Kim, Sung-Man;Park, Jai-Young
    • ETRI Journal
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    • v.30 no.3
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    • pp.461-468
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    • 2008
  • This paper presents a chromatic dispersion monitoring technique using a clock-frequency component for carrier-suppressed return-to-zero (CSRZ) signal. The clock-frequency component is extracted by a clock-extraction (CE) process. To discover which CE methods are most efficient for dispersion monitoring, we evaluate the monitoring performance of each extracted clock signal. We also evaluate the monitoring ability to detect the optimum amount of dispersion compensation when optical nonlinearity exists, since it is more important in nonlinear transmission systems. We demonstrate efficient CE methods of CSRZ signal to monitor chromatic dispersion for optimum compensation in high-speed optical communication systems.

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Design and Implementation of Monitoring Software for Heterogeneous Control Network (이종 제어 네트워크를 위한 모니터링 소프트웨어의 설계 및 구현)

  • Heo, Jong-Man;Ha, Jae-Yeol;Kim, Nam-Hoon;Jeon, Joseph;Lee, Kam-Rok;Chung, Bum-Jin;Kwon, Wook-Hyun
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.114-116
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    • 2006
  • XCP (eXtensive Control Protocol) is an information oriented protocol which delivers information with high reliability according to the predefined rule. XCP network system can be implemented on top of several physical layer such as power line, IEEE 802.15.4 and so on. In this paper. a monitoring software that evaluates the reliability and performance of the XCP network is designed and implemented. This paper presents the structure and method of the packet monitoring in the network through several interfaces such as RS-232, ethernet.

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