We propose a model assisted method to identify damage types and severity based on mode converted wave strength. Machine learning techniques are employed to develop classification models complemented by the finite element simulation models. Finite element simulation models provide the training data for various cases of damage and severity involving common types of damages in composites. Damage classification models are based on mode conversion strength versus frequency curves of participating four wave modes. For damage recognition and classification, a multi-layer Convoluted Neural Network (CNN) has been trained using the back-propagation paradigm on the generated dataset.

Machine learning enabled damage classification in composite laminated beams using mode conversion quantification

Delamination is the most common type of damage that can occur in a composite structure at a very early stage of its operation. Detection, localization and classification of delamination parameters in composite laminates assist in determining the operating condition of the structure. Such a task, especially involving global localization on the structure and local localization along the thickness of the laminate is difficult using guided waves that are inherently multimodal leading to complicated mixed mode response of transducers. This paper proposes the use of embedded thin film sensors to decouple the response due to each wave mode enabling easy interpretation of the signals for damage detection. Delamination damage has been considered and the strength of reflected guided wave modes has been studied in the purview of delamination localization along with the thickness. The variation of mode conversion strength for fundamental and higher order wave modes further provides additional data to determine the delamination parameters.

Extracting Mode Converted Guided Wave Response due to Delamination using Embedded Thin Film Sensors

This paper presents a Lamb wave virtual time reversal algorithm with transducer transfer function compensation to eliminate the transducer influence for dispersive, multimodal Lamb waves. This virtual time reversal procedure builds upon a complete 2D analytical model for Lamb wave generation, propagation, and reception. The analytical solution shows that, with the transducer transfer function compensation, a perfect reconstruction of the original excitation waveform can be achieved for both symmetric and antisymmetric Lamb wave modes. In addition, the Finite Element Modeling (FEM) and experimental validations are further performed to verify the compensated virtual time reversal procedure. Finally, a time reversal tomography experiment is conducted with a piezoelectric transducer array for structural damage imaging. The Lamb wave virtual time reversal algorithm with transducer transfer function compensation can achieve more accurate and robust damage imaging results. The paper finishes with discussion, concluding remarks, and suggestions for future work.

Lamb wave virtual time reversal damage detection algorithm with transducer transfer function compensation

This paper presents a systematic numerical investigation of guided wave generation, propagation, interaction with damage, and reception in anisotropic piezoelectric composite plates. This approach employs piezoelectric composite materials as both load bearing and sensing elements. Finite element modal analysis of a plate unit cell with Bloch-Floquet boundary condition is performed to understand the guided wave propagation characteristics in piezoelectric composite plates. The guided wave generation and tuning characteristics are investigated using the harmonic analysis model with absorbing boundary conditions. The relationship between the generated wave modes and the laminate layup orientations is studied. Subsequently, an impact damage is introduced and modeled as a group of cone shape delaminated layers and stiffness losses within the layers through the thickness direction. 2D and 3D transient dynamic coupled-field finite element models are constructed to simulate the procedure of guided wave generation, propagation, interaction with the impact damage, and reception in an orthotropic piezoelectric composite plate using the commercial finite element software (ANSYS). In addition, Contact Acoustic Nonlinearity (CAN) is simulated via time domain transient analysis. Advanced signal processing techniques are used to extract the distinctive nonlinear features. The frequency-wavenumber analysis is further adopted to decipher wave modes and frequency components in the scattered wave field. This paper finishes with concluding remarks and suggestions for future work.

Guided Wave Generation and Propagation in Self-Sensing Piezoelectric Composite Plates for Structural Health Monitoring

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Junzhen Wang

Author Tools

Chat about Author

Papers

Guided Wave Generation and Propagation in Self-Sensing Piezoelectric Composite Plates for Structural Health Monitoring