… rate of rotating machinery fault identification based on imbalanced samples [30,31,32,33].
In the classification and identification tasks based on deep learning, the two problems that …

… Lastly, the fault identification model of rotating machinery with rotor lateral early crack based
on BP … get the signal feature to diagnose the occurrence of early fault of rotating machinery. …

… rotating machinery fault diagnosis method used in this paper also achieves the final fault
diagnosis … In this paper, the problem of fault detection and isolation is considered as a multi-…

… Fault detection and its diagnosis is therefore essential for maintaining the efficiency of
machinery… FO-SVM, for detection and diagnosis of machinery faults. The experimental scenario for …

… Beard [6], known as fault detection filter approach. The fault detection filter does not require
the knowledge of the fault mode, hence a fault is detected when one or more of the residual …

… [23] studied the progress of DL in PHM and concluded that the nature of fault detection,
fault diagnosis and RUL prediction tasks include binary classification, multi-classification and …

… In this work, we employed audio signals to detect and classify faults in rotating machinery
that use bearings. The sounds of machinery with and without faults were recorded using a …

… involved in the measured vibration signals and extract features that would facilitate fault
identification and, therefore, are essential for effective fault diagnosis of the rotating machines. …

… transform in fault diagnosis of rotary machines, widely used equipment in manufacturing, with
… 3 shows an example of bearing defect identification by applying the MuSEnS technique to …

… phases of analysis and diagnosis, according to the procedure proposed by Harris (1993).The
difference is the feature selection that is quite difficult for rotating machinery; we defined a …