서지주요정보
Research on structure health monitoring for composite fuel tank : PZT ultrasonic attenuation and acoustic emission localization = 복합재 연료용기의 구조 건전성 모니터링 방법 연구 : PZT 초음파 감쇠비와 음향방출 위치표정 기법
서명 / 저자 Research on structure health monitoring for composite fuel tank : PZT ultrasonic attenuation and acoustic emission localization = 복합재 연료용기의 구조 건전성 모니터링 방법 연구 : PZT 초음파 감쇠비와 음향방출 위치표정 기법 / KyungHwan Kim.
발행사항 [대전 : 한국과학기술원, 2025].
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8043561

소장위치/청구기호

학술문화관(도서관)2층 학위논문

DAE 25001

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초록정보

As the hydrogen energy industry grows, its applications expand across various sectors, including aerospace engineering. Hydrogen fuel storage systems use composite overwrapped pressure vessels to store hydrogen fuel. Type IV composite pressure vessels comprise a plastic liner and filament-wounded composite materials like CFRP and GFRP. Pressure vessels undergo repeated expansion and contraction during fuel charging and discharging, accumulating damage over time. Therefore, proper structural health monitoring methods are essential for safely operating hydrogen fuel storage systems. In this study, the PZT active sensor network is based on the PZT pitch-catch method to monitor the structure health of the composite pressure vessels. The PZT active sensor network measures the change of attenuation of the ultrasonic wave propagation through the pressure vessel depending on the hydraulic test cycles. Also, the crack density was calculated using the micro-CT imaging method of the hydraulically tested pressure vessels. A correlation was derived from these two hydraulic test cycle-dependent parameters. This correlation allows the PZT active sensor mounted on the operating pressure vessel to monitor the state of the pressure vessel by measuring the ultrasonic signal attenuation. Another structural health monitoring method, acoustic emission based on laser ultrasonic signal modulation, was also proposed. With frequency domain information of the acoustic emission and laser ultrasonic signal, a neural network-based frequency modulation algorithm was proposed. This algorithm modulates the laser ultrasonic signal's frequency components to resemble the emission signal. With this modulated laser ultrasonic signal, a localization of the acoustic emission on the composite pressure vessels was conducted.

수소에너지 산업이 성장함에 따라 항공분야를 포함한 다양한 분야에서 수소에너지의 적용이 늘어나고 있다. 수소에너지는 수소연료를 사용하기 위해 고압의 복합재 압력용기를 이용하여 수소를 저장한다. 이 복합재 압력 용기들 중 Type IV 압력용기는 플라스틱 라이너를 내부에 두고, 그 주위를 탄소섬유 복합재를 필라멘트 와인딩 방식으로 감는 것으로 구성된다. 압력용기는 연료의 충전과 방전에 따라 수축과 팽창을 반복하며 손상이 누적되게 된다. 따라서 안전한 수소연료의 사용을 위해서 수소연료용기의 상태를 모니터링 할 필요가 있다. 본 연구에서는 복합재 연료저장용 압력용기의 구조 건전성 모니터링을 위해 PZT pitch-catch 기반의 PZT 네트워크를 이용하여 수소연료용기의 반복적인 사용에 따라 발생하는 초음파 신호 전파의 감쇠비를 비교를 획득하고, 이를 micro-CT 기법을 이용해 획득한 크랙 밀도 값의 상관관계를 수압반복 시험 횟수에 따라 도출하였다. 이를 이용하면 수소 저장 시스템을 사용하는 장치의 운용 중 PZT 네트워크에서 측정되는 초음파 전파 감쇠비를 이용하여 수소 저장용 압력용기의 현재 상태를 유추할 수 있다. 더불어, 수소저장용 압력용기에서 사용할 수 있는 구조 건전성 모니터링 기법으로, 레이저 초음파 트레이닝 기반 음향방출 위치표정 알고리즘을 제시하였다. 레이저 초음파 신호와 음향방출 모사 신호의 주파수 대역 정보를 이용해 신경망 기반의 주파수 변조 알고리즘을 통해 레이저 초음파 신호가 음향방출 신호와 유사하도록 변조시켜, 레이저 초음파 신호를 바탕으로 음향방출 신호의 위치표정을 수행하였다.

서지기타정보

서지기타정보
청구기호 {DAE 25001
형태사항 v, 69 p. : 삽화 ; 30 cm
언어 영어
일반주기 저자명의 한글표기: 김경환
지도교수의 영문표기: Lee, Jung Ryul
지도교수의 한글표기: 이정률
학위논문 학위논문(박사) - 한국과학기술원 : 항공우주공학과,
서지주기 References: p. 64-68
주제 Composite Fuel Pressure Vessel
Structural Health Monitoring
Ultasonic Wave Propagation Attenuation
Crack Density
Acoustic Emission Localization
복합재 연료용기
구조 건전성 모니터링
초음파 감쇠
크랙밀도
음향방출 위치표정
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Type IV Composite pressure vessel monitoring: NDT VS SHM

Schematic diagram of the GUPI scan procedure (a) Raster scan scenario (b) 1D signal from laser excitation (c) 3D data array as an inspection result

GUPI Inspection setup and schematic of COPV (a) Scan area and investigation direction (b) Scan schematic and rotation of COPV

UWPI freeze frame results from pristine and hydraulic-tested COPVs

Wave propagation speed attenuation results (a) Pristine (b) 22,000 cycles (c) 45,000 cycles

Ultrasonic wave propagation attenuation coefficient results from three pristine COPVs

Ultrasonic wave propagation attenuation coefficient measurement schematic

Attenuation coefficient results of the pristine, 22000 cycled, 45000 cycled COPVs

Specification of the type IV COPV

(a) The Schematic and the cross-section ofNexo's type IV pressure vessel (b) The cross-section of the pressure vessel

Hydraulic test plan for five COPVs

Cumulative damage on the COPVs while hydraulic cycle tests

PZT active sensor network schematic

PZT active sensor network on the Type IV COPV (a) PZT transducer (b) PZT network on the pressure vessel

PZT active sensor network data acquisition principle (a) Actuation signal (b) Data acquisition method

The micro-CT inspection setup for the COPV cut specimen (a) micro-CT facility from KARA (b) micro-CT imaging method setup

Schematic diagram of two-mirror LMS system with galvanometers and pincushion distortion

Curvature scan interval distortion while maneuvering LMS (a) Distorted interval on the curvature structure (b) Modified scan interval

Initial parameters for curvature compensation

Detailed calculation of the scan interval for curvature compensation

Required parameters for the curvature compensation

Used LiDAR imaging system and its configuration (a) LiDAR imaging system (b) LiDAR imaging system coordinates (c) System configuration of LiDAR with GUPI system

GUPI scanning direction types (a) Vertical direction (b) Horizontal direction

LiDAR imaging system-based parameter acquisition for curvature compensation (a) Target structure - 0 direction (b) 0 map with 0 : 0 line, (c) 0 map

Compensated GUPI UWM and wavenumber results (a) Uncompensated UWM (b) Uncompensated wavenumber distribution (c) Compensated UWM (d) Compensated wavenumber distribution

Curvature compensation test setup for the type IV COPV (a) LiDAR integrated setup (b) Scan area and [ map of pressure vessel

Curvature compensation result for the type IV COPV (a) Before compensation (b) After compensation

Schematic of the rotational-GUPI scan area and the sensor location (a) Rotational plane (b) Circumferential plane

The Rotational GUPI setup for the pressure vessels (a) Rotational stage mounted pressure vessel (b) LiDAR imaging system integrated GUPI system

Algorithm of acoustic emission localization with trained laser ultrasonic signals

Schematic diagram of acoustic emission localization

The Ultrasonic wave propagation signal from the sensing PZT transducer with crosstalk (a) from P1 (b) from P9

Crosstalk Compensated signal (a) from P1 (b) from P9

Crosstalk compensated sensing PZT responses in Tank 1 at 15000 cycles

Enveloped Sensing PZT Responses in Tank 1 at 15000 cycles

PZT active sensor network response of Tank1 - 5000 cycles

PZT active sensor network response of Tank1 - 10000 cycles

PZT active sensor network response of Tank1 - 15000 cycles

PZT active sensor network response of Tank1 - 20000 cycles

RMS calculation of the tank 1 with the number ofhydraulic test cycles (a) Raw signal at P1, P5, P9 at 15000 cycles (b) Normalized RMS values per test cycles

Ultrasonic attenuation coefficient result ofhydraulic-tested type IVCOPVs

Ultrasonic wave attenuation measurement and curve-fitting result oftank 1 (a) Tank 1 curve-fitting result (b) The attenuation coefficient tendency of tank1

The quadratic function of the number of hydraulic test cycles and attenuation coefficient

Color histogram adjustment to remove the background for the crack density analysis

The planes of micro-CT results and analysis volume defined at the 20000-cycle specimen (a) Actual specimen (b) Micro-CT results

Micro-CT-based crack density analysis results at each hydraulic test cycle

The micro-CT imaging results of the crack-and-void-labeled fraction (a) Pristine (b) 20,000 cycles

Quadratic curve-fitted crack density against hydraulic test cycles

Parametrization of the attenuation coefficient and crack density of type IV pressure vessels

The quadratic function representation between the attenuation coefficient and the crack density

Rotational GUPI inspection results for the pristine and 10000-cycle tested pressure vesse Left: pristine, Right: 10000 cycles

Reference signal acquisition for gain application and sensor locations with reference points

PLB VS GUPI signal comparison in both time and frequency domain

PLB signal arrival time adjustment with GUPI signal

Signal modulation procedure with gain (a) Signal modulation algorithm (b) Generated optimal gain