… According to the results on the topic of machine fault diagnosis by using machine learning,
the number of publications has rapidly increased since the 2010s. Therefore, we roughly …

… state of the drive and correctly locating faults as soon as they occur. We present a machine
learning approach to train a diagnostic system, fault diagnostic neural network (FDNN), that …

… fault diagnosis of WT, there are still some challenges encountered in many aspects. In this
paper, typical fault diagnosis … machine learning (TML), artificial neural networks (ANN), deep …

… of machine learning theory to machinery fault diagnosis. To overcome the above shortcomings,
data-driven machinery fault diagnosis methods based on machine learning algorithms …

… This study presents a procedure for detection of bearing fault by classifying them using
two machine learning methods, namely, ANNs and SVMs. Features are extracted from time-…

… fault diagnostic models is given in Chap. 2. In this book, this generalized diagnostic framework
is treated from a machine learning … is viewed as an unsupervised learning problem. Three …

… and intelligent fault diagnosis such as machine learning (ML), … on ML-based power system
fault diagnosis. However, ML … on ML-based power system fault diagnosis, is not available in …

… fault diagnosis of wind turbine gearbox [31]. Several studies were proposed to detect the wind
turbine blades faults (… For this work, the focus is to study the fault diagnosis of wind turbine …

… of using machine learning techniques to diagnose faults of … We applied Machine learning
techniques in order to identify … We used Support Vector Machine for Regression to analyze …

… fault diagnosis using machine learning approaches. This article analyses various machine
learning approaches used for fault diagnosis of … of different machine learning strategies which …