• Title/Summary/Keyword: Network Load Model

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Building Bearing Fault Detection Dataset For Smart Manufacturing (스마트 제조를 위한 베어링 결함 예지 정비 데이터셋 구축)

  • Kim, Yun-Su;Bae, Seo-Han;Seok, Jong-Won
    • Journal of IKEEE
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    • v.26 no.3
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    • pp.488-493
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    • 2022
  • In manufacturing sites, bearing fault in eletrically driven motors cause the entire system to shut down. Stopping the operation of this environment causes huge losses in time and money. The reason of this bearing defects can be various factors such as wear due to continuous contact of rotating elements, excessive load addition, and operating environment. In this paper, a motor driving environment is created which is similar to the domestic manufacturing sites. In addition, based on the established environment, we propose a dataset for bearing fault detection by collecting changes in vibration characteristics that vary depending on normal and defective conditions. The sensor used to collect the vibration characteristics is Microphone G.R.A.S. 40PH-10. We used various machine learning models to build a prototype bearing fault detection system trained on the proposed dataset. As the result, based on the deep neural network model, it shows high accuracy performance of 92.3% in the time domain and 98.3% in the frequency domain.

Implementation of Dynamic Context-Awareness Platform for Internet of Things(IoT) Loading Waste Fire-Prevention based on Universal Middleware (유니버설미들웨어기반의 IoT 적재폐기물 화재예방 동적 상황인지 플랫폼 구축)

  • Lee, Hae-Jun;Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.8
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    • pp.1231-1237
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    • 2022
  • It is necessary to dynamic recognition system with real time loading height and pressure of the loading waste, the drying of wood, batteries, and plastic wastes, which are representative compositional wastes, and the carbonization changes on the surface. The dynamic context awareness service constituted a platform based on Universal Middleware system using BCN convergence communication service as a Ambient SDK model. A context awareness system should be constructed to determine the cause of the fire based on the analysis data of fermentation heat point with natural ignition from the load waste. Furthermore, a real-time dynamic service platform that could be apply to the configuration of scenarios for each type from early warning fire should be built using Universal Middleware. Thus, this issue for Internet of Things realize recognition platform for analyzing low temperature fired fire possibility data should be dynamically configured and presented.

Damaged cable detection with statistical analysis, clustering, and deep learning models

  • Son, Hyesook;Yoon, Chanyoung;Kim, Yejin;Jang, Yun;Tran, Linh Viet;Kim, Seung-Eock;Kim, Dong Joo;Park, Jongwoong
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.17-28
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    • 2022
  • The cable component of cable-stayed bridges is gradually impacted by weather conditions, vehicle loads, and material corrosion. The stayed cable is a critical load-carrying part that closely affects the operational stability of a cable-stayed bridge. Damaged cables might lead to the bridge collapse due to their tension capacity reduction. Thus, it is necessary to develop structural health monitoring (SHM) techniques that accurately identify damaged cables. In this work, a combinational identification method of three efficient techniques, including statistical analysis, clustering, and neural network models, is proposed to detect the damaged cable in a cable-stayed bridge. The measured dataset from the bridge was initially preprocessed to remove the outlier channels. Then, the theory and application of each technique for damage detection were introduced. In general, the statistical approach extracts the parameters representing the damage within time series, and the clustering approach identifies the outliers from the data signals as damaged members, while the deep learning approach uses the nonlinear data dependencies in SHM for the training model. The performance of these approaches in classifying the damaged cable was assessed, and the combinational identification method was obtained using the voting ensemble. Finally, the combination method was compared with an existing outlier detection algorithm, support vector machines (SVM). The results demonstrate that the proposed method is robust and provides higher accuracy for the damaged cable detection in the cable-stayed bridge.

Design of a Service Broker for Large Scale Connections to Support Pubsub QoS between TOS and Mobile Devices (TOS와 Mobile device 간의 펍섭 QoS를 지원하는 대량 커넥션 서비스 브로커 설계)

  • Jeon, Young-Jun;Hwang, Hee-Joung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.5
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    • pp.137-142
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    • 2016
  • A two-step open system(TOS) was proposed to relay between a healing platform and a repository of personal health documents. TOS was designed by taking into consideration the pubsub service based on large scale connections to monitor a provider's access/request process for health documents in real time. TOS, however, uses WebSocket as a communication protocol in case of pubsub. Given the operational environment of low quality wireless networks for mobile devices that are user terminals in a healing platform, there is a need to add a messaging protocol to support QoS as well as a transmission protocol. As a light messaging protocol optimized for mobile devices, MQTT defines reliable messaging QoS to consider a wireless network situation of low speed/low quality. This study designed an MQTT protocol-based message broker to support QoS in case of large scale connections and pubsub by taking into consideration mobile devices that are user terminals in a healing platform. After designing a model between TOS and MQTT message broker, the study implemented a prototype based on the proposed design and compared it with its counterparts from previous studies based on the performance indicators in a load-test with the MQTT client tool.

Railway Line Planning Considering the Configuration of Lines with Various Halting Patterns (다양한 정차 패턴을 고려한 열차 노선계획의 수립)

  • Park, Bum-Hwan;Oh, Seog-Moon;Hong, Soon-Heum;Moon, Dae-Seop
    • Journal of Korean Society of Transportation
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    • v.23 no.6 s.84
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    • pp.115-125
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    • 2005
  • The line planning problem is to determine the origin and destination stations of the lines with their frequencies so as to meet the OD demands. Since the advent of high speed trains, Korea railway is confronted with the urgent difficulty to reconstruct the line configuration with the frequencies of each line and each fleet type so the demands could be newly created as well as satisfied. Furthermore. the existing trains except the high speed trains suffer from a longer traveling time than before. Now, to reduce the passenger traveling time, the trains with the various halting patterns are run in the same line. Therefore, it is necessary to develop a new line planning model to consider the various halting patterns. Most of studies find the frequencies of each lines which meet the link traffic loads or minimum link frequencies. But these are based on the assumption of all stop patterns. Furthermore, it is not easy to include the actual constraints as like the minimum number of stops at a station, the maximum number of stops or a train, etc. We develop the line planning model considering not only the various halting patterns but also the actual constraints which is based on the multicommodity network flow model with the additional constraints.

Implementation of A Safe Driving Assistance System and Doze Detection (졸음 인식과 안전운전 보조시스템 구현)

  • Song, Hyok;Choi, Jin-Mo;Lee, Chul-Dong;Choi, Byeong-Ho;Yoo, Ji-Sang
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.3
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    • pp.30-39
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    • 2012
  • In this paper, a safe driving assistance system is proposed by detecting the status of driver's doze based on face and eye detection. By the level of the fatigue, safe driving system alarms or set the seatbelt on vibration. To reduce the effect of backward light and too strong solar light which cause a decrease of face and eye detection rate and false fatigue detection, post processing techniques like image equalization are used. Haar transform and PCA are used for face detection. By using the statistic of the face and eye structural ratio of normal Koreans, we can reduce the eye candidate area in the face, which results in reduction of the computational load. We also propose a new eye status detection algorithm based on Hough transform and eye width-height ratio, which are used to detect eye's blinking status which decides doze level by measuring the blinking period. The system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. In this paper, four algorithms are implemented and proposed algorithm is made based on the probability model and we achieves 84.88% of correct detection rate through indoor and in-car environment experiments. And also we achieves 69.81% of detection rate which is better result than that of other algorithms using IR camera.

High-Frequency Parameter Extraction of Insulating Transformer Using S-Parameter Measurement (S-파라메타를 이용한 절연 변압기의 고주파 파라메타 추출)

  • Kim, Sung-Jun;Ryu, Soo-Jung;Kim, Tae-Ho;Kim, Jong-Hyeon;Nah, Wan-Soo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.25 no.3
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    • pp.259-268
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    • 2014
  • In this paper, we suggest a method of extracting circuit parameters of the insulating transformer using S-parameter measurement, especially in high frequency range. At 60 Hz, conventionally, no load test and short circuit test are used to extract the circuit parameters. In this paper S-parameters measured from VNA(Vector Network Analyzer) were used to extract the transformer parameters using data fitting method (optimization). The S-parameters from the equivalent circuit using the extracted parameters showed good agreement with those from measurement. Furthermore, the transformer secondary voltages from the equivalent circuit model also coincide quite exactly to the measured secondary voltages in sinusoidal forms. Finally we assert that the proposed method to extract the parameters for the insulating transformer using S-parameter is valid especially in high frequency.

Development of Artificial Intelligence Joint Model for Hybrid Finite Element Analysis (하이브리드 유한요소해석을 위한 인공지능 조인트 모델 개발)

  • Jang, Kyung Suk;Lim, Hyoung Jun;Hwang, Ji Hye;Shin, Jaeyoon;Yun, Gun Jin
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.48 no.10
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    • pp.773-782
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    • 2020
  • The development of joint FE models for deep learning neural network (DLNN)-based hybrid FEA is presented. Material models of bolts and bearings in the front axle of tractor, showing complex behavior induced by various tightening conditions, were replaced with DLNN models. Bolts are modeled as one-dimensional Timoshenko beam elements with six degrees of freedom, and bearings as three-dimensional solid elements. Stress-strain data were extracted from all elements after finite element analysis subjected to various load conditions, and DLNN for bolts and bearing were trained with Tensorflow. The DLNN-based joint models were implemented in the ABAQUS user subroutines where stresses from the next increment are updated and the algorithmic tangent stiffness matrix is calculated. Generalization of the trained DLNN in the FE model was verified by subjecting it to a new loading condition. Finally, the DLNN-based FEA for the front axle of the tractor was conducted and the feasibility was verified by comparing with results of a static structural experiment of the actual tractor.

Recent Progress in Air-Conditioning and Refrigeration Research : A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2016 (설비공학 분야의 최근 연구 동향 : 2016년 학회지 논문에 대한 종합적 고찰)

  • Lee, Dae-Young;Kim, Sa Ryang;Kim, Hyun-Jung;Kim, Dong-Seon;Park, Jun-Seok;Ihm, Pyeong Chan
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.29 no.6
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    • pp.327-340
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    • 2017
  • This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2016. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of flow, heat and mass transfer, the reduction of pollutant exhaust gas, cooling and heating, the renewable energy system and the flow around buildings. CFD schemes were used more for all research areas. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results of the long-term performance variation of the plate-type enthalpy exchange element made of paper, design optimization of an extruded-type cooling structure for reducing the weight of LED street lights, and hot plate welding of thermoplastic elastomer packing. In the area of pool boiling and condensing, the heat transfer characteristics of a finned-tube heat exchanger in a PCM (phase change material) thermal energy storage system, influence of flow boiling heat transfer on fouling phenomenon in nanofluids, and PCM at the simultaneous charging and discharging condition were studied. In the area of industrial heat exchangers, one-dimensional flow network model and porous-media model, and R245fa in a plate-shell heat exchanger were studied. (3) Various studies were published in the categories of refrigeration cycle, alternative refrigeration/energy system, system control. In the refrigeration cycle category, subjects include mobile cold storage heat exchanger, compressor reliability, indirect refrigeration system with $CO_2$ as secondary fluid, heat pump for fuel-cell vehicle, heat recovery from hybrid drier and heat exchangers with two-port and flat tubes. In the alternative refrigeration/energy system category, subjects include membrane module for dehumidification refrigeration, desiccant-assisted low-temperature drying, regenerative evaporative cooler and ejector-assisted multi-stage evaporation. In the system control category, subjects include multi-refrigeration system control, emergency cooling of data center and variable-speed compressor control. (4) In building mechanical system research fields, fifteenth studies were reported for achieving effective design of the mechanical systems, and also for maximizing the energy efficiency of buildings. The topics of the studies included energy performance, HVAC system, ventilation, renewable energies, etc. Proposed designs, performance tests using numerical methods and experiments provide useful information and key data which could be help for improving the energy efficiency of the buildings. (5) The field of architectural environment was mostly focused on indoor environment and building energy. The main researches of indoor environment were related to the analyses of indoor thermal environments controlled by portable cooler, the effects of outdoor wind pressure in airflow at high-rise buildings, window air tightness related to the filling piece shapes, stack effect in core type's office building and the development of a movable drawer-type light shelf with adjustable depth of the reflector. The subjects of building energy were worked on the energy consumption analysis in office building, the prediction of exit air temperature of horizontal geothermal heat exchanger, LS-SVM based modeling of hot water supply load for district heating system, the energy saving effect of ERV system using night purge control method and the effect of strengthened insulation level to the building heating and cooling load.

Techniques for Acquisition of Moving Object Location in LBS (위치기반 서비스(LBS)를 위한 이동체 위치획득 기법)

  • Min, Gyeong-Uk;Jo, Dae-Su
    • The KIPS Transactions:PartD
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    • v.10D no.6
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    • pp.885-896
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    • 2003
  • The typws of service using location Information are being various and extending their domain as wireless internet tochnology is developing and its application par is widespread, so it is prospected that LBS(Location-Based Services) will be killer application in wireless internet services. This location information is basic and high value-added information, and this information services make prior GIS(Geographic Information System) to be useful to anybody. The acquisition of this location information from moving object is very important part in LBS. Also the interfacing of acquisition of moving object between MODB and telecommunication network is being very important function in LBS. After this, when LBS are familiar to everybody, we can predict that LBS system load is so heavy for the acquisition of so many subscribers and vehicles. That is to say, LBS platform performance is fallen off because of overhead increment of acquiring moving object between MODB and wireless telecommunication network. So, to make stable of LBS platform, in this MODB system, acquisition of moving object location par as reducing the number of acquisition of unneccessary moving object location. We study problems in acquiring a huge number of moving objects location and design some acquisition model using past moving patternof each object to reduce telecommunication overhead. And after implementation these models, we estimate performance of each model.