Abstract The use of Machine Learning (ML) has rapidly spread across several fields of
applied sciences, having encountered many applications in Structural Dynamics and …

Purpose This study aims to bring awareness to the developing of fault detection systems
using the data collected from sensor devices/physical devices of various systems for …

Industry 4.0 is strongly intertwined with big data streaming flows from intelligent sensors and
machinery installed in industrial facilities. Failures can disrupt production and lead the …

This study reports a method for the detection of mechanical signaling anomalies in cardiac
tissue through the use of deep learning and the design of two anomaly detectors. In contrast …

The recent development of highly automated machinery and intelligent industrial plants has
increasingly enabled the continuous monitoring of their efficiency and condition, with the aim …

The operating conditions of compressor systems used in shale gas fields are variable. To
enhance the performance of anomaly detection methods, it is crucial to capture the running …

Purpose The objective of this article is to evaluate and compare the performance of two
machine learning (ML) algorithms, ie support vector machines (SVMs) and random forests …

In the energy generation business steam powered turbo-generators still play an important
role in electrical power generation all over the world. Every facility using steam turbines …

In order to improve the control performance of rotating limit device on the motion range of
rotating parts of mechanical equipment, the multi model identification and fusion control …

Computer network plays a very important role in today's world. With the development of
network technology and the increasing popularity of network topology, network management …