Acoustic Emission Signal Analysis and Damage Mode Identification of Composite Wind Turbine Blades
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74 235 Ft (70 700 Ft + 5% VAT)
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74 235 Ft
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Product details:
- Publisher Elsevier
- Date of Publication 24 May 2023
- ISBN 9780323886529
- Binding Paperback
- No. of pages364 pages
- Size 228x152 mm
- Weight 450 g
- Language English
- Illustrations Approx. 200 illustrations 506
Categories
Long description:
Acoustic Emission Signal Analysis and Damage Mode Identification of Composite Wind Turbine Blades covers both the underlying theory and various techniques for effective structural monitoring of composite wind turbine blades via acoustic emission signal analysis, helping readers solve critical problems such as noise elimination, defect detection, damage mode identification, and more. Author Pengfei Liu introduces techniques for identifying and analyzing progressive failure under tension, delamination, damage localization, adhesive composite joint failure, and other degradation phenomena, outlining methods such as time-difference, wavelet, machine learning, and more including combined methods.
The disadvantages and advantages of using each method are covered as are techniques for different blade-lengths and various blade substructures. Piezoelectric sensors are discussed as is experimental analysis of damage source localization. The book also takes great lengths to let readers know when techniques and concepts discussed can be applied to composite materials and structures beyond just wind turbine blades.
MoreTable of Contents:
1. Introduction to Acoustic Emission Techniques for Composite Wind Turbine Blades
2. Failure Mechanisms in Wind Turbine Blades: Delamination, Adhesive Composite Joint Failure
3. Delamination Analysis of Composite Laminates
4. Damage Analysis of Adhesive Composite Joints
5. Damage Mechanisms of Blade Structures Under Accelerated Fatigue Loads
6. Waveform-Based Feature Extraction Model
7. Experimental Analysis of Damage Source Localization
8. Clustering Method for Damage Mode Identification
Acoustic Emission Signal Analysis and Damage Mode Identification of Composite Wind Turbine Blades
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