Research into fault diagnosis in rotating machinery with a wide range of variable loads and
speeds, such as the gearboxes of wind turbines, is of great industrial interest. Although …

Purpose–The purpose of this paper is to test the applicability and the performance of an
approach called logical analysis of data (LAD) on the detection of faults in rotating …

Although the diagnosis methods of rotating machinery based on convolutional neural
network (CNN) have achieved great success, they generally assume the number of normal …

Identifying fault of rotating machinery under different load conditions with high accuracy is a
remaining challenge for vibration signal based fault diagnosis. Aiming at this challenge, this …

Support vector machines (SVMs) have become one of the most popular approaches to
learning from examples and have many potential applications in science and engineering …

Fault diagnosis methods based on dimensionless indicators have long been studied for
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …

Condition-based monitoring of rotating machines requires robust features for accurate fault
diagnosis, which is indeed directly linked to the quality of the features extracted from the …

Most intelligent fault diagnosis methods of rotating machinery generally consider that normal
samples and fault samples as equally important for pattern recognition training. It ignores …

Fault diagnosis of rotating machinery is receiving more and more attentions. Vibration
signals of rotating machinery are commonly analyzed to extract features of faults, and the …

Fault Detection and Diagnosis of electrical machine and drive systems are of utmost
importance in modern industrial automation. The widespread use of Machine Learning …