The feasibility and usefulness of frequency domain fusion of data from multiple vibration
sensors installed on typical industrial rotating machines, based on coherent composite …

This study presents an efficient vibration-based fault detection method for rotating machines
utilising the poly-coherent composite spectrum (pCCS) and machine learning techniques …

The availability of complex rotating machines is vital for the prevention of catastrophic
failures in a significant number of industrial operations. Reliability engineering theories …

Rotating machines are pivotal to the achievement of core operational objectives within
various industries. Recent drives for developing smart systems coupled with the significant …

The composite spectrum (CS) data fusion technique has been shown to simplify rotating
machines faults diagnosis by earlier studies. Faults diagnosis with the earlier CS relied …

In an earlier study, the poly-coherent composite higher order spectra (ie poly-coherent
composite bispectrum and trispectrum) frequency domain data fusion technique was …

The key to fault diagnosis of rotating machinery is to extract fault features effectively and
select the appropriate classification algorithm. As a common signal decomposition method …

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 …

Condition monitoring systems are increasingly being employed in industrial applications to
improve the availability of equipment and to increase the overall equipment efficiency …

Predictive maintenance is one of the major tasks in today's modern industries. All rotating
machines consisting of rotating elements such as gears, bearings etc are considered as the …