Freshly Printed - allow 10 days lead
Couldn't load pickup availability
Acoustic Emission Signal Analysis and Damage Mode Identification of Composite Wind Turbine Blades
Covers the theory and techniques for monitoring composite wind turbine blades via acoustic emission signal analysis
Pengfei Liu (Author)
9780323886529, Elsevier Science
Paperback / softback, published 24 May 2023
364 pages, Approx. 200 illustrations
22.9 x 15.2 x 2.3 cm, 0.45 kg
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.
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
Subject Areas: Signal processing [UYS], Civil engineering, surveying & building [TN], Mechanical engineering [TGB], Electricity, electromagnetism & magnetism [PHK]
