In the era of the so called 4th industrial revolution, the Factory of the Future and the Industrial
Internet of Things, the industrial mechanical systems become continuously more intelligent …

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

Fault diagnosis of rotating machinery serves an important role in informing system operation
and predictive maintenance decisions. To quantify the fault information from vibrational …

For rotating machinery, the sudden failure of roller bearing would lead to the downtime of the
whole system and even catastrophic accidents. Therefore, multiple accelerometers are …

Rotating machinery are widely used in industry, and vibration analysis is one of the most
common methods to monitor health condition of rotating machinery. However, due to the …

Gearboxes and bearings play an important role in industries for motion and torque
transmission machines. Therefore, early diagnoses are sought to avoid unplanned …

Because multi-fault vibration signals in rotating machinery are often more complicated than
single faults, human-designed fault feature sets are not yet able to respond adequately to …

This paper proposes a hybrid intelligent method for multi-fault detection of rotating
machinery, in which three methods, ie including the redundant second generation wavelet …

Fault detection of rotating machinery by the complex and non-stationary vibration signals
with noise is very difficult, especially at the early stages. Also, many failure mechanisms and …

Rotating machinery fault diagnosis is vital to enhance the reliability and safety of modern
equipment. Recently, deep learning (DL) models have achieved breakthrough …