[HTML][HTML] Latent variable models in the era of industrial big data: Extension and beyond
A rich supply of data and innovative algorithms have made data-driven modeling a popular
technique in modern industry. Among various data-driven methods, latent variable models …
technique in modern industry. Among various data-driven methods, latent variable models …
A review on deep learning based condition monitoring and fault diagnosis of rotating machinery
Rotating machine faults are unavoidable; thus, early diagnosis is essential to avoid further
damage to the machine or other machine attached to it. Various signal analysis based …
damage to the machine or other machine attached to it. Various signal analysis based …
Global and local feature extraction using a convolutional autoencoder and neural networks for diagnosing centrifugal pump mechanical faults
Centrifugal pumps are important types of electro-mechanical machines used for fluid and
energy conveyance. Mechanical faults in centrifugal pumps lead to abnormal impacts in the …
energy conveyance. Mechanical faults in centrifugal pumps lead to abnormal impacts in the …
A deep autoencoder-based convolution neural network framework for bearing fault classification in induction motors
RN Toma, F Piltan, JM Kim - Sensors, 2021 - mdpi.com
Fault diagnosis and classification for machines are integral to condition monitoring in the
industrial sector. However, in recent times, as sensor technology and artificial intelligence …
industrial sector. However, in recent times, as sensor technology and artificial intelligence …
Fault diagnosis of hydro-turbine runner based on improved masking signal method incorporate RLMD
S Xu, F Dao, Y Zeng, J Qian - Applied Acoustics, 2025 - Elsevier
Sediment erosion and foreign object impacts can cause irreversible damage to hydro-
turbine runner. It is proposed to use the Improved Masked Signal method combined with the …
turbine runner. It is proposed to use the Improved Masked Signal method combined with the …
Analysis of the interdecadal and interannual variability of autumn extreme rainfall in taiwan using a deep-learning-based weather ty** approach
LH Hsu, Y Wu, CC Chiang, JL Chu, YC Yu… - Asia-Pacific Journal of …, 2023 - Springer
This study sought to assess the interdecadal and interannual variability of autumn extreme
rainfall (ER) in Taiwan from 1979 to 2019. Three types of ER events were identified based …
rainfall (ER) in Taiwan from 1979 to 2019. Three types of ER events were identified based …
Rotating blade faults classification of a rotor-disk-blade system using artificial neural network
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery
faults detection and classification. First, experiments were performed to measure the lateral …
faults detection and classification. First, experiments were performed to measure the lateral …
Rub-impact fault identification of a bladed rotor based on chaotic features
H Kou, C Yue, HP Lee, T Zhang, J Du, Z Zhu, F Zhang… - 2023 - researchsquare.com
The bladed rotor is an important part in turbine machines. Timely detection of its blade
rubbing fault may avoid serious accidents. This paper developed a rub-impact fault …
rubbing fault may avoid serious accidents. This paper developed a rub-impact fault …
[PDF][PDF] Undercomplete Autoencoder for dimensional reduction applied to Pulsed thermography
Non-destructive testing and evaluation techniques are essential in structural health
monitoring and safety control in industry and aerospace. Among the different NDT …
monitoring and safety control in industry and aerospace. Among the different NDT …