Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating
machinery (RM) has a vital role in the modern industrial world. However, the remaining …

The fault diagnosis of rotating electrical machines has received an intense amount of
research interest during the last 30 years. Reducing maintenance costs and preventing …

Preventing induction motors (IMs) from failure and shutdown is important to maintain
functionality of many critical loads in industry and commerce. This paper provides a …

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The
proposed approach first extracts wavelet-based fault features that represent diverse …

Electrical machines are prone to faults and failures and demand incessant monitoring for
their confined and reliable operations. A failure in electrical machines may cause …

In order to fault diagnosis of ball bearing that is one of the most critical components of
rotating machinery, this paper presents a time–frequency procedure incorporating a new …

Condition monitoring and fault diagnosis are important for maintaining the system
performance and guaranteeing the operational safety. The traditional data‐driven …

This paper reports on a new back propagation (BP) neural network based on an improved
shuffled frog leaping algorithm (ISFLA) and its application in bearing fault diagnosis. The …

An improved algorithm with feature selection and neural network classification is proposed
in this paper to investigate the fault diagnosis problem of rotating machinery. The feature …

Diesel engines have a wide range of functions in the industrial and military fields. An urgent
problem to be solved is how to diagnose and identify their faults effectively and timely. In this …