Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
Intelligent maintenance systems and predictive manufacturing
With continued global market growth and an increasingly competitive environment,
manufacturing industry is facing challenges and desires to seek continuous improvement …
manufacturing industry is facing challenges and desires to seek continuous improvement …
Bearing fault diagnosis of induction motors using a genetic algorithm and machine learning classifiers
RN Toma, AE Prosvirin, JM Kim - Sensors, 2020 - mdpi.com
Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is
challenging but necessary to ensure safety and economical operation in industries …
challenging but necessary to ensure safety and economical operation in industries …
Early fault diagnosis of bearing and stator faults of the single-phase induction motor using acoustic signals
A Glowacz, W Glowacz, Z Glowacz, J Kozik - Measurement, 2018 - Elsevier
An article describes an early fault diagnostic technique based on acoustic signals. The
presented technique was used for a single-phase induction motor. The authors measured …
presented technique was used for a single-phase induction motor. The authors measured …
Enhanced human activity recognition based on smartphone sensor data using hybrid feature selection model
Human activity recognition (HAR) techniques are playing a significant role in monitoring the
daily activities of human life such as elderly care, investigation activities, healthcare, sports …
daily activities of human life such as elderly care, investigation activities, healthcare, sports …
Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network
MMM Islam, JM Kim - Computers in Industry, 2019 - Elsevier
Bearings are one of the most crucial components in many industrial machines. Effective
bearing fault diagnosis is essential for normal and safe machine operation. Existing fault …
bearing fault diagnosis is essential for normal and safe machine operation. Existing fault …
Emotional stress state detection using genetic algorithm-based feature selection on EEG signals
D Shon, K Im, JH Park, DS Lim, B Jang… - International Journal of …, 2018 - mdpi.com
In recent years, stress analysis by using electro-encephalography (EEG) signals
incorporating machine learning techniques has emerged as an important area of research …
incorporating machine learning techniques has emerged as an important area of research …
The bearing faults detection methods for electrical machines—the state of the art
Electrical machines are prone to faults and failures and demand incessant monitoring for
their confined and reliable operations. A failure in electrical machines may cause …
their confined and reliable operations. A failure in electrical machines may cause …
A comprehensive survey on the process, methods, evaluation, and challenges of feature selection
Feature selection is employed to reduce the feature dimensions and computational
complexity by eliminating irrelevant and redundant features. A vast amount of increasing …
complexity by eliminating irrelevant and redundant features. A vast amount of increasing …
A two-stage feature selection and intelligent fault diagnosis method for rotating machinery using hybrid filter and wrapper method
X Zhang, Q Zhang, M Chen, Y Sun, X Qin, H Li - Neurocomputing, 2018 - Elsevier
Selecting the most discriminative features from the original high dimensional feature space
and finding out the optimal parameters for recognition model both have vital influences on …
and finding out the optimal parameters for recognition model both have vital influences on …