[HTML][HTML] A review on autoencoder based representation learning for fault detection and diagnosis in industrial processes

J Qian, Z Song, Y Yao, Z Zhu, X Zhang - Chemometrics and Intelligent …, 2022 - Elsevier
Process monitoring technologies play a key role in maintaining the steady state of industrial
processes. However, with the increasing complexity of modern industrial processes …

Intelligent computational methods for damage detection of laminated composite structures for mobility applications: a comprehensive review

MM Azad, Y Cheon, I Raouf, S Khalid… - Archives of Computational …, 2024 - Springer
The mobility applications of laminated composites are constantly expanding due to their
improved mechanical properties and superior strength-to-weight ratio. Such advancements …

Graph convolutional network soft sensor for process quality prediction

M Jia, D Xu, T Yang, Y Liu, Y Yao - Journal of Process Control, 2023 - Elsevier
The nonlinear time-varying characteristics of the process industry can be modeled using
numerous data-driven soft sensor methods. However, the intrinsic relationships among the …

Deep convolutional autoencoder thermography for artwork defect detection

Y Liu, F Wang, K Liu, M Mostacci, Y Yao… - Quantitative InfraRed …, 2023 - Taylor & Francis
Infrared thermography is a cost-effective non-destructive evaluation technique that plays a
critical role in extracting information about defects in cultural heritage such as works of art …

A novel in-situ sensor calibration method for building thermal systems based on virtual samples and autoencoder

Z Sun, Q Yao, H Jin, Y Xu, W Hang, H Chen, K Li, L Shi… - Energy, 2024 - Elsevier
Sensor networks are playing an increasingly important role in modern buildings. With the
growing size of building sensor networks and the increasing use of low-cost sensors, the …

Attention-Gate-based U-shaped Reconstruction Network (AGUR-Net) for color-patterned fabric defect detection

H Zhang, S Wang, S Lu, L Yao… - Textile Research …, 2023 - journals.sagepub.com
Color-patterned fabrics possess changeable patterns, low probability of defective samples,
and various forms of defects. Therefore, the unsupervised inspection of color-patterned …

[HTML][HTML] Dual-IRT-GAN: A defect-aware deep adversarial network to perform super-resolution tasks in infrared thermographic inspection

L Cheng, M Kersemans - Composites Part B: Engineering, 2022 - Elsevier
InfraRed Thermography (IRT) is a valuable diagnostic tool for detecting defects in fiber-
reinforced polymers in a non-destructive manner through the measurement of surface …

Latent-enhanced variational adversarial active learning assisted soft sensor

Y Dai, C Yang, Y Liu, Y Yao - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
As the acquisition of variables that measure quality is typically challenging, labeled samples
for building a model for soft sensors are often inadequate. Additionally, owing to the …

A complex-valued slow independent component analysis based incipient fault detection and diagnosis method with applications to wastewater treatment processes

C Xu, D Huang, B Cai, H Chen, Y Liu - ISA transactions, 2023 - Elsevier
Multivariate statistical process monitoring are the essential approaches to achieve better
prognostics and health management (PHM) of process industries. However, incipient faults …

[HTML][HTML] Depth classification of defects in composite materials by long-pulsed thermography and blind linear unmixing

R Marani, DU Campos-Delgado - Composites Part B: Engineering, 2023 - Elsevier
This paper presents the automatic analysis of surface thermograms in response to a long-
pulsed thermography inspection to classify buried defects in composite materials. Time …