Monitoring structural damage is extremely important for sustaining and preserving the
service life of civil structures. While successful monitoring provides resolute and staunch …

This article gives an overview of the artificial intelligence (AI) applications for power
electronic systems. The three distinctive life-cycle phases, design, control, and maintenance …

During the last decade, Convolutional Neural Networks (CNNs) have become the de facto
standard for various Computer Vision and Machine Learning operations. CNNs are feed …

This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …

Deep learning (DL) based methods have swept the field of mechanical fault diagnosis,
because of the powerful ability of feature representation. However, many of existing DL …

In the Engineering discipline, prognostics play an essential role in improving system safety,
reliability and enabling predictive maintenance decision-making. Due to the adoption of …

Fault detection and diagnosis in time series data are becoming mainstream in most
industrial applications since the increase of monitoring sensors in machinery. Traditional …

Real-time smart grid monitoring is critical to enhancing resiliency and operational efficiency
of power equipment. Cloud-based and edge-based fault detection systems integrating deep …

Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …

1D Convolutional Neural Networks (CNNs) have recently become the state-of-the-art
technique for crucial signal processing applications such as patient-specific ECG …