• Title/Summary/Keyword: sensor prediction

Search Result 567, Processing Time 0.037 seconds

Prediction of the Penetration Energy for Composite Laminates Subjected to High-velocity Impact Using the Static Perforation Test (정적압입 관통실험을 이용한 복합재 적층판의 고속충격 관통에너지 예측)

  • You, Won-Young;Lee, Seokje;Kim, In-Gul;Kim, Jong-Heon
    • Composites Research
    • /
    • v.25 no.5
    • /
    • pp.147-153
    • /
    • 2012
  • In this paper, static perforation tests are conducted to predict the penetration energy for the composite laminates subjected to high velocity impact. Three methods are used to analyze the perforation energy accurately. The first method is to select the perforation point using the AE sensor signal energy, the second method is to retest the tested specimen and use the difference between initial and retested perforation energy, and the third method is to select the perforation point based on the maximum loading point in the retested load-displacement curve of the tested specimen. The predicted perforation energy results are presented and verified by comparing with those by the high velocity tests.

A Study on Fault Prediction Method in a Pump Tower of LNG FPSO (LNG FPSO 펌프타워 고장 예지 방안에 관한 연구)

  • Kim, Yongjae;Cho, SangJe;Jun, Hong-Bae;Ha, Chunghun;Shin, Jongho
    • Korean Journal of Computational Design and Engineering
    • /
    • v.21 no.2
    • /
    • pp.111-121
    • /
    • 2016
  • The plant equipment usually has a long life cycle. During its O&M (Operation & Maintenance) phase, since the occurrence of an accident of offshore plant equipment causes catastrophic damage, it is necessary to make more efforts for managing critical offshore equipment. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the health status data of important offshore equipment and their environment data, which leads to much concern on CBM (Condition-Based Maintenance). In this study, we will propose an approach to estimate the remaining lifetime of an offshore plant equipment (pump tower) based on gathered ocean environment data.

Multi-modal Vibration Control of Intelligent Laminated Composite Plates Using System Identification and Optimal Control (시스템식별과 최적제어를 이용한 지능형 복합적층판의 다중보드 진동제어)

  • 김정수;강영규;박현철
    • Transactions of the Korean Society for Noise and Vibration Engineering
    • /
    • v.12 no.1
    • /
    • pp.5-11
    • /
    • 2002
  • Active vibration control of intelligent laminated composite plates is performed experimental1y Laminated composite place is modeled by the system identification method. For the system identification process, the laminated composite place is excited by two piezoelectric actuators with PRBS signals. At the same time, the displacement of the laminated composite plate is measured by a gap sensor. From these excited PRBS signals and the measured displacement sequence, system parameters of the laminated composite plate are estimated using a recursive prediction error method. Model of the laminated composite plate with two piezoeletric actuators is assumed to be the form of ARMAX. From the estimated ARHMAX model, a state space equation of the observable canonical form is obtained. With this state space equation, a controller and an observer for active vibration control is designed using the optimal control method. Controller and observer are implemented on a digital system. Experiments on the vibration control are Performed with changing the outer layer fiber orientation of intelligent composite plates.

Measurement of Radiative Heat Flux of Kick Motor at Ground Test (킥 모터 지상 시험의 플룸 복사 열유속 측정)

  • Kim, Seong-Lyong;Choi, Sang-Ho;Ko, Ju-Yong;Kim, In-Sun
    • 한국전산유체공학회:학술대회논문집
    • /
    • 2008.03b
    • /
    • pp.440-443
    • /
    • 2008
  • Plume radiation has been measured during ground tests of KSLV-I kick motor in order to predict the thermal load on the equipment around the kick motor at flight. The measuring positions are the kick motor base, and the measured heats were about 2${\sim}$5 w/cm$^2$. The measured heat showed a lot of shot fluctuation in their values, and the radiative heats at the latter half of time are higher than those of the first half. A plausible explanation for these phenomena was given as the variation of alumina particles with time. The radiative heats along the plume axis were also measured recently at 8 positions with 1.5m radius from plume axis, but only the initial parts of the results could be acceptable because the sensor were damaged by the accumulated heat. The strongest heat occurred at the middle of the plume, which can be explained with different view factors. Despite of the plausible explanation, it seems to need more analysis because the plume structure such as temperature, alumina particle, after burning has not been revealed until yet. The measure heat flux has been reflected in the prediction of the plume radiation at high altitude where the kick motor operates.

  • PDF

A Study on Frictional Characteristics and Polishing Result of SiO2 Slurry in CMP (CMP시 SiO2 슬러리의 마찰 특성과 연마결과에 관한 연구)

  • Lee Hyunseop;Park Boumyoung;Seo Heondeok;Jung Jaewoo;Jeong Sukhoon;Jeong Haedo
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.29 no.7 s.238
    • /
    • pp.983-989
    • /
    • 2005
  • The effects of mechanical parameters on the characteristics of chemical mechanical polishing(CMP) can be directly evaluated by friction force. The piezoelectric quartz sensor for friction force measurement was installed, and friction force could be detected during CMP process. Furthermore, friction energy can be calculated by multiplying relative velocity by integration of the friction force throughout the polishing time. $SiO_2$ slurry for interlayer dielectric(ILD) CMP was used in this experiment to consider the relation of frictional characteristics and polishing results. From this experiment, it is proven that the friction energy is an essential factor of removal rate. Also, the friction force is related to removal amount per unit length(dH/ds) and friction energy has corelation to the removal rate(dH/dt) and process temporature. Moreover, within wafer non-unifornity(WIWNU) is related to coefficient of friction because of the mechanical moment equilibrium. Therefore, the prediction of polishing result would be possible by measuring friction force.

Analysis of Cavity Resonances caused by Knocking in Chamber of High Power Engine (고출력 엔진에서 연소실 내의 노킹음에 의한 공진현상 분석)

  • Lee, Du-Gon;Jang, Seok-Hyung;Yi, Chong-Ho;Park, Kyung-Suk;Jun, Kye-Suk
    • The Journal of the Acoustical Society of Korea
    • /
    • v.11 no.4
    • /
    • pp.31-35
    • /
    • 1992
  • Cavity resonances are caused by combustion such as the rapid of pressure rise that occurs from knock in high power gasoline engines. These resonances generally occur at frequencies greater than 5KHz. Analysis of these resonances is important for knock control system design in high power gasoline engines. In this paper, in order to design knock control system for the high power gasoline engine, knock phenomena that occur in chamber were analized theoretically and resonance frequencies of knock signals were predicted. Also, experiments were performed using Soupe x-engine and non-resonance type knock sensor of Bosch co. in Germany. In the result, good agreement was obtained between theoretical prediction and experimental observation.

  • PDF

Damage Behavior of Singly Oriented Ply Fiber Metal Laminate under Concentrated Loading Conditions (집중하중을 받는 일방향 섬유 금속 적층판의 손상 거동)

  • Nam, H.W.;Kim, Y.H.;Jung, S.W.;Jung, C.K.;Han, K.S.
    • Proceedings of the KSME Conference
    • /
    • 2001.06a
    • /
    • pp.407-412
    • /
    • 2001
  • In this research, damage behavior of singly oriented ply (SOP) fiber metal laminate (FML) subject to concentrated load was studied. The static indentation tests were conducted to study fiber orientation effect on damage behavior of FML. During the static indentation tests, Acoustic Emission technique (AE) was adopted to study damage characteristics of FML. AE signals were obtained by using AE sensor with 150kHz resonance frequency and the signals were compared with indentation curves of FML. As fiber orientation angle increases, the crack initiation load of SOP FML increases because the stiffness induced by fiber orientation is increased. The penetration load of SOP FML is influenced by the deformation tendency and boundary conditions. Cumulative AE counts were well predicted crack initiation and crack propagation and AE amplitude were useful for prediction of damage failure mode. During the matrix cracking, fiber debonding and fiber breakage, AE amplitude has $45{\sim}60dB,\;60{\sim}80dB\;and\;90{\sim}100dB$, respectively.

  • PDF

Investigation on the Characteristics of the Stationary Feed Motor Current (절삭력 간접측정을 위한 정계모터 전류의 특성 연구)

  • Jeong, Young-Hun;Kim, Seong-Jin;Cho, Dong-Woo
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.19 no.9
    • /
    • pp.66-73
    • /
    • 2002
  • Since cross-feed directional cutting force which is normal to machined surface directly influences the machined surface of the workpiece and total force loaded in cutter, it is necessary to estimate this force to control the roughness of the machined surface and total force in cutter. However, there have been difficulties in using the current existing in a stationary motor for cutting state prediction because of some unpredictable behavior of the current. Empirical approach was conducted to resolve the problem. As a result, we showed that the current and its unpredictable behavior are related to the infinitesimal rotation of the motor. Subsequently, the relationship between the current and the cutting force was identified with the error less than 50%. And, the estimation results of the two machine tools with different characteristics were compared to each other to confirm the validity of the presented estimation method and the characteristics of current of the stationary feed motor.

Prediction and Evaluation of Power Output for Energy Scavengers using the Piezoelectric Material (압전 재료를 이용한 에너지 변환 시스템의 출력 파워 예측 및 평가)

  • Oh, Jae-Eung;Kim, Seong-Hyeon;Sim, Hyoun-Jin;Lee, Jung-Yoon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
    • /
    • 2006.05a
    • /
    • pp.827-830
    • /
    • 2006
  • With recent advanced in portable electric devices, wireless sensor, MEMS and bio-Mechanics device, the new typed power supply, not conventional battery but self-powered energy source is needed. Particularly, the system that harvests from their environments are interests for use in self powered devices. For very low powered devices, environmental energy may be enough to use power source. In the generality of cases, these energy harvesting systems are used in the piezoelectric materials as mechanisms to convert mechanical vibration energy into electric energy. Through the piezoelectric materials, the ambient vibration energy could be used to prolong the power supply or in the ideal case provide endless energy f9r the devices. Therefore, the piezoelectric power harvesting cantilever beam is developed. Also, the output voltage and power are predicted in this study. We also discuss the developing system of the piezoelectric energy scavenger. An experimental verification of the model is also performed to ensure its accuracy.

  • PDF

Neural Network-Based Modeling for Fuel Consumption Prediction of Vehicle (차량 연료 소모량 예측을 위한 신경회로망 기반 모델링)

  • Lee, Min-Goo;Jung, Kyung-Kwon;Yi, Sang-Hoi
    • 전자공학회논문지 IE
    • /
    • v.48 no.2
    • /
    • pp.19-25
    • /
    • 2011
  • This paper presented neural network modeling method using vehicle data to predict fuel consumption. To acquire data for training and testing the proposed neural network, medium-class gasoline vehicle drove at downtown and parameters measured include speed, engine rpm, throttle position sensor (TPS), and mass air flow (MAF) as input data, and fuel consumption as target data from OBD-II port. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the neural network model can predict the vehicle quite well with mean squared error was $1.306{\times}10^{-6}$ for the fuel consumption.