Artificial intelligence (AI)-based rotor fault diagnosis (RFD) poses a variety of challenges to
the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults …

Rotating machine vibration signals typically represent a large collection of responses from
various sources in a machine, along with some background noise. This makes it challenging …

Determining the optimal features that are invariant under changes in the rotational speed
variations of rolling element bearings is a challenging task. To address this issue, this paper …

Condition monitoring schemes are essential for increasing the reliability and ensuring the
equipment efficiency in industrial processes. The feature extraction and dimensionality …

Gearboxes and induction motors are important components in industrial applications and
their monitoring condition is critical in the industrial sector so as to reduce costs and …

The efficiency issue of energy systems in the oil and gas industry is a crucial factor
nowadays. Energy share in the production costs of oil and gas can reach 50%. Among the …

Rotating machinery (RM) fault diagnosis based on artificial intelligence (AI) is an esteemed
industrial IoT application and an inevitable constituent of the Industry 4.0 revolution. Notably …

In this paper, we propose a new bearing fault diagnosis method without the feature
extraction, based on Convolutional Neural Network (CNN). The 1-D vibration signal is …

In today's interconnected industrial landscape, the ability to predict and monitor the
operational status of equipment is crucial for maintaining efficiency and safety. Diesel …

Benefiting from the recent successes of convolutional neural networks (CNNs), many studies
have modeled the vibration signal of energy system into a two-dimensional (2-D) input …