Structural Health Monitoring/Management (SHM) in Aerospace Structures
Kiadó: Woodhead Publishing
Megjelenés dátuma: 2024. május 1.
Normál ár:
Kiadói listaár:
EUR 230.00
EUR 230.00
Az Ön ára:
85 419 (81 351 Ft + 5% áfa )
Kedvezmény(ek): 10% (kb. 9 491 Ft)
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A termék adatai:
| ISBN13: | 9780443154768 |
| ISBN10: | 0443154767 |
| Kötéstípus: | Puhakötés |
| Terjedelem: | 550 oldal |
| Méret: | 229x152 mm |
| Nyelv: | angol |
| 700 |
Témakör:
Hosszú leírás:
Structural Health Monitoring/Management (SHM) in Aerospace Structures provides readers with the spectacular progress that has taken place over the last twenty years with respect to the area of Structural Health Monitoring (SHM) Management. The SHM field encompasses transdisciplinary areas, including smart materials, sensors and actuators, damage diagnosis and prognosis, signal and image processing algorithms, wireless intelligent sensing, data fusion, and energy harvesting. This book focuses on how SHM techniques can be applied to aircraft, mechanical and civil engineering structures with particular emphasis on composite materials. This will be a valuable reference resource for R&D managers, materials scientists, and engineers working in the aerospace sector, for researchers and system designers working in industry, and for academia and government research agencies developing new systems for the SHM of aerospace, mechanical, and civil engineering structures.
- Presents new developments in smart materials for sensing and actuation
- Discusses new developments in mechanical metamaterials
- Presents the latest on signal/imaging processing for damage diagnosis
- Explores damage prognosis and integrated vehicle health management (IVHM)
- Covers new developments in machine learning and artificial Intelligence
Tartalomjegyzék:
1 Overview of SHM in airline maintenance: Challenges and opportunities
2 NDE in metal additive manufacturing: Survey
3 Composite sandwich structures: Damage detection and assessment using ultrasonic guided waves
4 Recent advances in loads/strain monitoring: A review
5 Overview of phase array technology in SHM
6 Advances in FBG sensor systems for SHM of composite aerospace structures
7 Ultrasonic wavefield imaging in structural health monitoring: A review
8 State-of-the-art in eddy current techniques for damage detection of composite bolted joints
9 Self-healing polymers and composites: A review of recent developments
10 Using optic fibers for ultrasonic damage detection at high temperatures
11 Flextensional piezoelectric energy harvesting technologies for aerospace applications
12 Mechanical metamaterials for wave-based SHM and vibration isolation
13 Identification of composite material properties by elastic wave propagation methods
14 Spatiotemporal fractal manifold learning for vibration-based structural health monitoring
15 Nonlinear autoregressive exogenous method for structural health monitoring using ultrasonic guided waves
16 A tutorial on digital twin for predictive maintenance
2 NDE in metal additive manufacturing: Survey
3 Composite sandwich structures: Damage detection and assessment using ultrasonic guided waves
4 Recent advances in loads/strain monitoring: A review
5 Overview of phase array technology in SHM
6 Advances in FBG sensor systems for SHM of composite aerospace structures
7 Ultrasonic wavefield imaging in structural health monitoring: A review
8 State-of-the-art in eddy current techniques for damage detection of composite bolted joints
9 Self-healing polymers and composites: A review of recent developments
10 Using optic fibers for ultrasonic damage detection at high temperatures
11 Flextensional piezoelectric energy harvesting technologies for aerospace applications
12 Mechanical metamaterials for wave-based SHM and vibration isolation
13 Identification of composite material properties by elastic wave propagation methods
14 Spatiotemporal fractal manifold learning for vibration-based structural health monitoring
15 Nonlinear autoregressive exogenous method for structural health monitoring using ultrasonic guided waves
16 A tutorial on digital twin for predictive maintenance
