This paper reviews the recent literature on machine learning (ML) models that have been
used for condition monitoring in wind turbines (eg blade fault detection or generator …

An electrocardiogram (ECG) records the electrical signal from the heart to check for different
heart conditions, but it is susceptible to noises. ECG signal denoising is a major pre …

Structural damages occur in modern structures during operations due to environmental and
human factors. The damages accumulating with time may lead to a significant decrease in …

Signal processing is one of the essential components in vibration-based approaches and
damage detection for structural health monitoring. Since signals in the real world are often …

A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach
consists of sifting an ensemble of white noise-added signal (data) and treats the mean as …

Data analysis has been one of the core activities in scientific research, but limited by the
availability of analysis methods in the past, data analysis was often relegated to data …

Electric load forecasting is an important issue for power utility, associated with the
management of daily operations such as energy transfer scheduling, unit commitment, and …

A multi-dimensional ensemble empirical mode decomposition (MEEMD) for multi-
dimensional data (such as images or solid with variable density) is proposed here. The …

This book addresses the steps needed to monitor health assessment systems and the
anticipation of their failures: choice and location of sensors, data acquisition and processing …

Monitoring the road pavement is a challenging task. Authorities spend time and finances to
monitor the state and quality of the road pavement. This paper investigate road surface …