Lamb wave-based quantitative identification of delamination in CF/EP composite structures using artificial neural algorithm
Source abstract
Abstract
Abstract Delamination in composite structures plays a major role in lowering structural strength and stiffness, consequently downgrading system integrity and reliability. A Lamb wave-based quantitative identification technique for delamination in CF/EP composite structures was established. Propagation of Lamb waves in a series of composite laminates, individually bearing a delamination, was evaluated using dynamic FEM analyses. Taking advantage of wavelet transform and artificial neural algorithms, an Intelligent Signal Processing and Pattern Recognition (ISPPR) package was developed, by which the spectrographic characteristics of simulated Lamb wave signals in the time-frequency domain were extracted and digitised as Digital Damage Fingerprints (DDF), to construct a Damage Parameters Database (DPD). The DPD was then used offline to train a multi-layer feedforward artificial neural network (ANN) under supervision of an error-backpropagation (BP) algorithm. Assisted by an active online structural health monitoring (AO-SHM) system with an active piezoelectric actuator/sensor network, the proposed methodology was validated online by identifying actual delaminations in CF/EP (T650/F584) quasi-isotropic composite laminates.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Ultrasonics and Acoustic Wave Propagation · Structural Health Monitoring Techniques · Smart Materials for Construction
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (31)
Show source-provided references
1. Damage detection in composite structures using piezoelectric materials10.1088/0964-1726/3/3/008 ↗
2. Lamb waves for the NDE of composite laminates
3. Diagnostic Lamb waves in an integrated piezoelectric sensor/actuator plate: analytical and experimental studies10.1088/0964-1726/10/5/307 ↗
4. The use of 0–3 piezocomposite embedded Lamb wave sensors for detection of damage in advanced fibre composites10.1088/0964-1726/9/3/307 ↗
5. Kessler SS, Spearing SM, Atalla MJ. In-situ damage detection of composites structures using Lamb wave methods. In: Balageas D, editor. Proceedings of the 1st European Workshop on Structural Health Monitoring, 10–12 July 2002, Paris, France. p. 374–81
6. Built-in diagnostics for impact damage identification of composite structures
7. Damage localization in composite plates using wavelet transform processing on Lamb wave signals
8. The interaction of Lamb waves with defects10.1109/58.143172 ↗
9. Damage identification method for smart composite cantilever beams with piezoelectric materials
10. Modelling of splitting and delamination in notched cross-ply laminates10.1016/S0266-3538(00)00170-6 ↗
11. Su Z, Ye L. Lamb wave propagation-based damage identification for quasi-isotropic CF/EP composite laminates using artificial neural algorithm, Part I: methodology and database development. J Intell Mater Syst Struct, in press10.1177/1045389X05047599 ↗
12. Su Z, Ye L. Lamb wave propagation-based damage identification for quasi-isotropic CF/EP composite laminates using artificial neural algorithm, Part II: implementation and validation. J Intell Mater Syst Struct, in press10.1177/1045389X05047600 ↗
13. Su Z, Ye L, Bu X. Evaluation of delamination in laminated composites based on Lamb wave modes: FEM simulation and experimental verification. In: Balageas, D, editor. Proceedings of the 1st European Workshop on Structural Health Monitoring, 10–12 July 2002, Paris, France. p. 328—35
14. Hibbitt, Karlsson & Sorensen, Inc. ABAQUS user's manual, ver. 6.2, 2001
15. Modelling the elastic properties of knitted fabric-reinforced composites10.1016/0266-3538(96)00053-X ↗
16. Selective generation of Lamb wave modes and their propagation characteristics in defective composite laminates
17. MSC. PATRAN user's manual, ver. 2002 (r2), 2001
18. Huang N, Ye L, Su Z. Parameterised modelling technique and its application in structural health monitoring. In: Proceedings of 4th Asian–Australasian Conference on Composite Materials, 6–9 July 2003, Sydney, Australia, 2004
19. Su Z, Ye L. An intelligent signal processing and patterns recognition technique for wave propagation-based structural health monitoring. Smart Mater Struct, in press
20. The Mathworks, Inc. Wavelet toolbox: for use with Matlab (user's guide), ver. 1.0, 2000
21. Flandrin · 1999
22. Su Z, Ye L. Artificial neural algorithm-based damage assessment for laminated composite structures using distributed actuators/sensors. In: Paipetis AS, editor. Proceedings of the 5th International Symposium on Advanced Composites, 5–7 May 2003, Corfu, Greece
23. Intelligent signal processing for damage detection in composite materials10.1016/S0266-3538(02)00008-8 ↗
24. The Mathworks, Inc. Neural network toolbox (user's guide), ver. 4.0, 2000
25. On-line identification of holes/cracks in composite structures10.1088/0964-1726/10/4/303 ↗
26. Delamination prediction in composite beams with built-in piezoelectric devices using modal analysis and neural network10.1088/0964-1726/5/3/012 ↗
27. Structural damage detection and identification using neural networks10.2514/3.11964 ↗
28. Substructural identification using neural networks10.1016/S0045-7949(99)00199-6 ↗
29. Damage detection using neural networks: an initial experimental study on debonded beams10.1177/1045389X9400500416 ↗
30. Structural damage detection using artificial neural networks and measured FRF data reduced via principal component projection10.1006/jsvi.2000.3390 ↗
31. A damage identification technique for CF/EP composite laminates using distributed piezoelectric transducers10.1016/S0263-8223(02)00115-0 ↗