Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor
Reciprocating compression machinery is the primary source of compressed air in the
industry. Undiagnosed faults in the machinery's components produce a high rate of …
industry. Undiagnosed faults in the machinery's components produce a high rate of …
Fusing convolutional generative adversarial encoders for 3D printer fault detection with only normal condition signals
C Li, D Cabrera, F Sancho, RV Sánchez… - … Systems and Signal …, 2021 - Elsevier
Collecting data from mechanical systems in abnormal conditions is expensive and time
consuming. Consequently, fault detection approaches based on classical supervised …
consuming. Consequently, fault detection approaches based on classical supervised …
Exploring an efficient remote biomedical signal monitoring framework for personal health in the COVID-19 pandemic
Z Tang, H Hu, C Xu, K Zhao - International Journal of Environmental …, 2021 - mdpi.com
Nowadays people are mostly focused on their work while ignoring their health which in turn
is creating a drastic effect on their health in the long run. Remote health monitoring through …
is creating a drastic effect on their health in the long run. Remote health monitoring through …
One-shot fault diagnosis of three-dimensional printers through improved feature space learning
C Li, D Cabrera, F Sancho, RV Sanchez… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Signal acquisition from mechanical systems working in faulty conditions is normally
expensive. As a consequence, supervised learning-based approaches are hardly …
expensive. As a consequence, supervised learning-based approaches are hardly …
Generative adversarial networks selection approach for extremely imbalanced fault diagnosis of reciprocating machinery
D Cabrera, F Sancho, J Long, RV Sánchez… - IEEE …, 2019 - ieeexplore.ieee.org
At present, countless approaches to fault diagnosis in reciprocating machines have been
proposed, all considering that the available machinery dataset is in equal proportions for all …
proposed, all considering that the available machinery dataset is in equal proportions for all …
Generative transfer learning for intelligent fault diagnosis of the wind turbine gearbox
Intelligent fault diagnosis algorithms based on machine learning and deep learning
techniques have been widely used in industrial applications and have obtained much …
techniques have been widely used in industrial applications and have obtained much …
Pre-classified reservoir computing for the fault diagnosis of 3D printers
Fault diagnosis is crucial for the printing quality assurance of a 3D printer. This paper
presents a pre-classified reservoir computing (PCRC) method to diagnose the health …
presents a pre-classified reservoir computing (PCRC) method to diagnose the health …
Transmission condition monitoring of 3d printers based on the echo state network
Three-dimensional printing quality is critically affected by the transmission condition of 3D
printers. A low-cost technique based on the echo state network (ESN) is proposed for …
printers. A low-cost technique based on the echo state network (ESN) is proposed for …
Rainfall Forecasting using a Bayesian framework and Long Short-Term Memory Multi-model Estimation based on an hourly meteorological monitoring network. Case …
Rainfall forecasting is a challenging task due to the time-dependencies of the variables and
the stochastic behavior of the process. The difficulty increases when the zone of interest is …
the stochastic behavior of the process. The difficulty increases when the zone of interest is …
Low-cost and small-sample fault diagnosis for 3D printers based on echo state networks
With the 3D printing rapidly expanding into various fields, 3D printers, as the equipment,
should adopt a low-cost and small-sample fault diagnosis methods. A fault diagnosis …
should adopt a low-cost and small-sample fault diagnosis methods. A fault diagnosis …