Acoustic Emission Signal Analysis and Damage Mode Identification of Composite Wind Turbine Blades

Pengfei Liu

• Publisher: Elsevier
• Year: 2023
• Print ISBN:
  9780323886529
• eBook ISBN:
  9780323886475
• Topic: Technology & Engineering
• Subtopic: Electromagnetism
• Index: Technology & Engineering

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. - Features fundamental acoustic emission theories and techniques for monitoring the structural integrity of wind turbine blades - Covers sensor arrangements, noise elimination, defect detection, and dominating damage mode identification using acoustic emission techniques - Outlines the wavelet method, the time-difference defect detection method, and damage mode identification techniques using machine learning - Discusses how the techniques covered can be extended and adapted for use in other composite structures under complex loads and in different environments

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Preface
• 1. AE health monitoring technique for composite wind turbine blade: a state-of-art review
• 2. AE tests and signal analysis of composite laminates with a central hole under tension
• 3. AE tests and signal analysis on delamination of composite laminates under three-point bending and different temperature
• 4. AE tests and signal analysis on delamination of composite laminates under three-point bending and hygrothermal environments
• 5. AE tests and signal analysis of composite laminates under tensile strain rate loads
• 6. AE tests and signal analysis on Delamination of composite laminates under tension–tension fatigue loads
• 7. AE tests and damage mode identification of composite wind turbine blade under bending fatigue loads
• 8. A waveform-based feature extraction model for AE signal analysis for structural health monitoring of composite wind turbine blade
• 9. Damage mode identification of composite materials based on global AE data and clustering analysis
• 10. AE feature extraction and signal representation model based on wavelet packet decomposition
• 11. Dynamic feature evaluation and information mining for AE data stream
• 12. Prediction model of residual load-bearing capacity of composite laminates using deep learning
• Index