A probabilistic framework for source localization in anisotropic composite using transfer learning based multi-fidelity physics informed neural network (mfPINN)-Reference-Cited by-同舟云学术

A probabilistic framework for source localization in anisotropic composite using transfer learning based multi-fidelity physics informed neural network (mfPINN)

Published:2023-08 Issue: Volume:197 Page:110360
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Kalimullah Nur M.M.,Shelke Amit,Habib Anowarul^ORCID

Funder

Universitetet i Tromsø

Indian Space Research Organisation

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference55 articles.

1. Health Monitoring of Aerospace Structures: Smart Sensor Technologies and Signal Processing;Staszewski,2004

2. Impact damage location in composite structures using optimized sensor triangulation procedure;Coverley;Smart Mater. Struct.,2003

3. Damage prognosis: the future of structural health monitoring;Farrar;Philos. Trans. R. Soc. A Math. Phys. Eng. Sci.,2007

4. Structural health monitoring: from sensing technology stepping to health diagnosis;Hui;Procedia Eng.,2011

5. An introduction to failure mechanisms and ultrasonic inspection;Jata,2007

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Acoustic emission monitoring for damage diagnosis in composite laminates based on deep learning with attention mechanism;Mechanical Systems and Signal Processing;2025-01

2. An intelligent method for temperature load of arch dams;Engineering Structures;2024-12

3. Deep transfer learning for efficient and accurate prediction of composite pressure vessel behaviors;Composites Part A: Applied Science and Manufacturing;2024-11

4. Probabilistic impact localization in composites using wavelet scattering transform and multi-output Gaussian process regression;Measurement;2024-08

5. MFC-PINN: A method to improve the accuracy and robustness of acoustic emission source planar localization;Measurement;2024-08