Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …

Renewable energy (RE) does not pollute environment at the point of energy generation, and
generally has a much lower pollution footprint than traditional energy from installing to …

This paper compares the performance of common edge detectors and deep convolutional
neural networks (DCNN) for image-based crack detection in concrete structures. A dataset of …

Structural health monitoring for lightweight complex composite structures is being
investigated in this paper with a data-driven deep learning approach to facilitate automated …

The short-term load forecasting is crucial in the power system operation and control.
However, due to its nonstationary and complicated random features, an accurate forecast of …

Rolling bearing fault diagnosis is a meaningful yet challengeable task. To improve the
performance of rolling bearing fault diagnosis, this paper proposes an enhanced selective …

Fault diagnosis and remaining useful life (RUL) prediction are always two major issues in
modern industrial systems, which are usually regarded as two separated tasks to make the …

In recent years, unmanned aerial vehicles (UAVs) have been used in several fields
including, for example, archaeology, cargo transport, conservation, healthcare, filmmaking …

Acoustic emission is a nondestructive control technique as it does not involve any input of
energy into the materials. It is based on the acquisition of ultrasonic signals spontaneously …

Accuracy metrics have been widely used for the evaluation of predictions in machine
learning. However, the selection of an appropriate accuracy metric for the evaluation of a …