Data fusion approaches for structural health monitoring and system identification: Past, present, and future

RT Wu, MR Jahanshahi - Structural Health Monitoring, 2020 - journals.sagepub.com
During the past decades, significant efforts have been dedicated to develop reliable
methods in structural health monitoring. The health assessment for the target structure of …

A Comprehensive review of emerging trends in aircraft structural prognostics and health management

S Khalid, J Song, MM Azad, MU Elahi, J Lee, SH Jo… - Mathematics, 2023 - mdpi.com
This review paper addresses the critical need for structural prognostics and health
management (SPHM) in aircraft maintenance, highlighting its role in identifying potential …

The role of surrogate models in the development of digital twins of dynamic systems

S Chakraborty, S Adhikari, R Ganguli - Applied Mathematical Modelling, 2021 - Elsevier
Digital twin technology has significant promise, relevance and potential of widespread
applicability in various industrial sectors such as aerospace, infrastructure and automotive …

Deep learning based car damage classification

K Patil, M Kulkarni, A Sriraman… - 2017 16th IEEE …, 2017 - ieeexplore.ieee.org
Image based vehicle insurance processing is an important area with large scope for
automation. In this paper we consider the problem of car damage classification, where some …

A novel deep convolutional image-denoiser network for structural vibration signal denoising

Q Xiong, H Xiong, C Yuan, Q Kong - Engineering Applications of Artificial …, 2023 - Elsevier
Vibration-based approach is of great importance for structural health monitoring and
condition assessment, while inevitable noise existing in field measurement casts great …

Structural health monitoring as a big-data problem

C Cremona, J Santos - Structural Engineering International, 2018 - Taylor & Francis
Structural health monitoring (SHM) has evolved over decades of continuous progress in
measuring, processing, collecting and storing massive amounts of data that can provide …

A multi-branch deep neural network model for failure prognostics based on multimodal data

Z Yang, P Baraldi, E Zio - Journal of Manufacturing Systems, 2021 - Elsevier
Non-numerical data, such as images and inspection records, contain information about
industrial system degradation, but they are rarely used for failure prognostic tasks given the …

Critical insights into the state‐of‐the‐art NDE data fusion techniques for the inspection of structural systems

W Nsengiyumva, S Zhong, M Luo… - Structural Control and …, 2022 - Wiley Online Library
In recent years, the demand for reliable and accurate nondestructive evaluation (NDE) of
structural systems has been growing and several nondestructive testing (NDT) techniques …

Damage‐sensitive feature extraction with stacked autoencoders for unsupervised damage detection

MF Silva, A Santos, R Santos… - … Control and Health …, 2021 - Wiley Online Library
In most real‐world monitoring scenarios, the lack of measurements from damaged
conditions requires the application of unsupervised approaches, mainly the ones based on …

Recent advancements in AI-enabled smart electronics packaging for structural health monitoring

VB Sharma, S Tewari, S Biswas, B Lohani, UD Dwivedi… - Metals, 2021 - mdpi.com
Real-time health monitoring of civil infrastructures is performed to maintain their structural
integrity, sustainability, and serviceability for a longer time. With smart electronics and …