From corrective to predictive maintenance—A review of maintenance approaches for the power industry
Appropriate maintenance of industrial equipment keeps production systems in good health
and ensures the stability of production processes. In specific production sectors, such as the …
and ensures the stability of production processes. In specific production sectors, such as the …
A survey of machine-learning techniques for condition monitoring and predictive maintenance of bearings in grinding machines
It is important to minimize the unscheduled downtime of machines caused by outages of
machine components in highly automated production lines. Considering machine tools such …
machine components in highly automated production lines. Considering machine tools such …
[HTML][HTML] Multi-class sentiment classification on Bengali social media comments using machine learning
Abstract Multi-class Sentiment Analysis (SA) is an important field of computational linguistics
that extracts multiple opinions expressed in a text using NLP and text-mining techniques …
that extracts multiple opinions expressed in a text using NLP and text-mining techniques …
Transfer learning based on improved stacked autoencoder for bearing fault diagnosis
Deep transfer learning algorithm is regarded as a promising method to address the issue of
rolling bearing fault diagnosis with limited labeled data. Stacked autoencoder (SAE) has …
rolling bearing fault diagnosis with limited labeled data. Stacked autoencoder (SAE) has …
Variable speed induction motors' fault detection based on transient motor current signatures analysis: A review
Induction motor is a major component in the industrial sector. It is experiencing great
development concerning size, market share, and technological design. Any sudden failure …
development concerning size, market share, and technological design. Any sudden failure …
Condition monitoring and fault diagnosis of induction motor
Background An induction motor is at the heart of every rotating machine and hence it is a
very vital component. Almost in every industry, around 90% of the machines apply an …
very vital component. Almost in every industry, around 90% of the machines apply an …
Data-driven fault diagnosis for electric drives: A review
The need to manufacture more competitive equipment, together with the emergence of the
digital technologies from the so-called Industry 4.0, have changed many paradigms of the …
digital technologies from the so-called Industry 4.0, have changed many paradigms of the …
Motor fault diagnostics based on current signatures: a review
Electric motors act as the backbone of industrial development. Their reliable and safe
operation is essential to various industries. At present, motor fault diagnosis based on …
operation is essential to various industries. At present, motor fault diagnosis based on …
Bearing fault diagnosis using time segmented Fourier synchrosqueezed transform images and convolution neural network
In this paper, a time segmented Fourier synchro-squeezed transform-based convolution
neural network is proposed for the bearing fault diagnosis. The proposed method acquired …
neural network is proposed for the bearing fault diagnosis. The proposed method acquired …
[HTML][HTML] Understanding lithium-ion battery management systems in electric vehicles: Environmental and health impacts, comparative study, and future trends: A review
The future of transportation is moving toward electric vehicles (EVs), driven by the global
demand for sustainability. At the core of EV technology is the Battery Management System …
demand for sustainability. At the core of EV technology is the Battery Management System …