A review on guided-ultrasonic-wave-based structural health monitoring: From fundamental theory to machine learning techniques
The development of structural health monitoring (SHM) techniques is of great importance to
improve the structural efficiency and safety. With advantages of long propagation distances …
improve the structural efficiency and safety. With advantages of long propagation distances …
A survey of Bouc-Wen hysteretic models applied to piezo-actuated mechanical systems: Modeling, identification, and control
Hysteretic nonlinearity behavior ubiquitously occurs in mechanical systems, particularly in
high-precision instruments, which severely degrades system output performance …
high-precision instruments, which severely degrades system output performance …
Enhanced ANN predictive model for composite pipes subjected to low-velocity impact loads
This paper presents an enhanced artificial neural network (ANN) to predict the displacement
in composite pipes impacted by a drop weight having different velocities. The impact …
in composite pipes impacted by a drop weight having different velocities. The impact …
Load-independent multi-objective sensor placement method for localization and reconstruction of external excitations under interval uncertainties
The direct measurement of external excitations under operation conditions remains
challenging in many engineering applications. This study proposes a method of optimal …
challenging in many engineering applications. This study proposes a method of optimal …
Quantification, localization, and reconstruction of impact force on interval composite structures
Impact force identification has been intensively studied owing to its profound effects on
health monitoring and safety assessment. This study investigates a novel uncertainty …
health monitoring and safety assessment. This study investigates a novel uncertainty …
Prediction-based human-robot collaboration in assembly tasks using a learning from demonstration model
Most robots are programmed to carry out specific tasks routinely with minor variations.
However, more and more applications from SMEs require robots work alongside their …
However, more and more applications from SMEs require robots work alongside their …
Impact force reconstruction and localization using Distance-assisted Graph Neural Network
In this paper, a novel impact force identification method named Distance-assisted Graph
Neural Network (DAGNN) is proposed for simultaneous force localization and force history …
Neural Network (DAGNN) is proposed for simultaneous force localization and force history …
A lightweight SHM framework based on adaptive multisensor fusion network and multigeneration knowledge distillation
Structural health monitoring (SHM) technology is of great importance to ensure the long-term
and reliable operation of engineering structures. The monitoring systems for large structures …
and reliable operation of engineering structures. The monitoring systems for large structures …
Hydrogen solubility in n-alkanes: Data mining and modelling with machine learning approach
Hydrogen solubility in hydrocarbons plays an important role in designing, optimizing, and
modelling many processes including underground hydrogen storage. This study applies four …
modelling many processes including underground hydrogen storage. This study applies four …
Impact load identification and localization method on thin-walled cylinders using machine learning
C Guo, L Jiang, F Yang, Z Yang… - Smart Materials and …, 2023 - iopscience.iop.org
In this paper, a novel impact load identification and localization method on actual
engineering structures using machine learning is proposed. Three machine learning …
engineering structures using machine learning is proposed. Three machine learning …