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MR 댐퍼를 기반으로 하는 스마트 수동제어 시스템

대한토목학회 정기 학술대회 2004 년 10 월 21 일. MR 댐퍼를 기반으로 하는 스마트 수동제어 시스템. 조상원 : KAIST 건설환경공학과 , 박사 이헌재 : KAIST 건설환경공학과 , 박사과정 오주원 : 한남대학교 토목환경공학과 , 교수 이인원 : KAIST 건설환경공학과 , 교수. CONTENTS. Introduction Electromagnetic Induction System for MR Damper Numerical Examples Conclusions

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MR 댐퍼를 기반으로 하는 스마트 수동제어 시스템

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  1. 대한토목학회 정기 학술대회 2004년 10월 21일 MR댐퍼를 기반으로 하는 스마트 수동제어 시스템 조상원: KAIST 건설환경공학과, 박사 이헌재: KAIST 건설환경공학과, 박사과정 오주원: 한남대학교 토목환경공학과, 교수 이인원: KAIST 건설환경공학과, 교수

  2. CONTENTS • Introduction • Electromagnetic Induction System for MR Damper • Numerical Examples • Conclusions • Further Study

  3. Introduction • Backgrounds • Semi-active control device has reliability of passive and adaptability of active system. • MR dampers are quite promising semi-active device for small power requirement, reliability, and inexpensive to manufacture.

  4. Characteristics of MR damper With Magnetic Fields Without Magnetic Fields Wires to Electromgnet Diaphragm MR Fluid Coil Bearing & Seal Accumulator

  5. Installation of Conventional MR Damper MR damper • External power source, controller, sensors • Complicated network using many MR dampers • Difficulties to set up and maintain

  6. Objective and Scope Development of simple and effective control device • Consists of permanent magnets and solenoid • Changes kinetic energy of MR damper to electric energy

  7. Electromagnetic Induction (EMI) System • Schematic diagram Conventional MR Damper MR fluid Line for external power source Solenoid MR Damper with EMI System MR fluid Solenoid Permanent magnet EMI system

  8. Mechanism Conventional MR Damper MR Damper External power Permanent magnet MR Damper with EMI System MR Damper Solenoid MR Damper

  9. Estimation of induced voltages by EMI system • Faraday’s law of induction • n : turns/m • B : magnetic flux • B : magnetic field • A : cross area (1)

  10. If we assume as below - Magnetic field : 1.2 T (Tesla) - Turns of solenoid : 900 turns/m - Area of cross section : 13.2 (cm2) - Velocity of stroke : 9 cm/s (max. value of uncontrolled) This EMI system will be applied to numerical example for examination of applicability Area : 13.2cm2 Length : 5cm

  11. Numerical Example • Three-story building (Dyke et al. 1996) MR Damper

  12. System data

  13. Determination of coil turns for solenoid By varying two parameters, Sa and Si Sa : summation of peak acceleration at each floor Si : summation of peak interstory drift at each floor which are normalized by uncontrolled responses Using envelope of maximum value of Sa and Si for El Centro, Hachinohe, Kobe earthquakes Two EMI systems are designed: EMI-A from Sa and EMI-D from Si • Design of EMI system

  14. El Centro El Centro Kobe Kobe Hachinohe Hachinohe Max. envelope of Sa Sa EMI-A : 2.6104 Coil turns/m Coil turns/m Variations of Sa Envelope of max. responses Max. envelope of Si Si EMI-D : 2.2104 Coil turns/m Coil turns/m

  15. Analysis • Comparisons • Proposed EMI systems : EMI-A, EMI-D • Previous clipped optimal controllers : Clipped-A, Clipped-D • Performances • Normalized acceleration and drift at each floor • El Centro, Hachinhe, Kobe, Northridge earthquakes

  16. ResultsAnalysis Induced voltages for various earthquakes by EMI system EL Centro Hachinohe Voltage (V) Kobe Northridge Voltage (V) Time (sec) Time (sec)

  17. Normalized accelerations at each floor EL Centro Hachinohe Normalized accel. Clipped-D Clipped-A EMI-D EMI-A Kobe Northridge Normalized accel. Floor level Floor level

  18. Normalized interstory drifts at each floor EL Centro Hachinohe Normalized accel. Clipped-D Clipped-A EMI-D EMI-A Kobe Northridge Normalized accel. Floor level Floor level

  19. Normalized peak responses for various earthquakes Clipped-D Clipped-A EMI-D EMI-A El Centro Hachinohe Kobe Northridge Peak Accel. Peak Drift

  20. EMI system Developed for MR damper-based control system Consists of permanent magnet and solenoid Simple structure without power, controller, sensors Shows comparable performances to clipped optimal controller • Conclusions

  21. 특허등록: 등록번호 0416398 Experimental tests Numerical modeling of EMI system using neural network • Further Study

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