In this paper, we introduce a new bearing fault detection and diagnosis scheme based on
hidden Markov modeling (HMM) of vibration signals. Features extracted from amplitude …

In the presence of faults, vibrations of rolling element bearings show symptomatic signatures
in the form of repetitive impulses. This can be seen as a non-stationary signal whose …

Due to the importance of rolling bearings as the most widely used machine elements, it is
necessary to establish a suitable condition monitoring procedure to prevent malfunctions …

Due to its practical importance, the diagnosis of rolling element bearing has attracted
constant interest in the scientific community. At the incipient stage of a failure, the measured …

The inevitable simultaneous formation of multiple-faults in bearings generates severe
vibrations, causing premature component failure and unnecessary downtime. For accurate …

Bearings are common and vital elements in rotating machinery. By tracking the condition of
a bearing, unscheduled machinery outages and costly damage caused by a bearing failure …

Bearing is one of the most critical components of rotating machinery. They are employed to
support and rotate the shafts in rotating machinery. Therefore; any fault in the bearings can …

Vibration-based condition monitoring techniques are commonly used to detect and
diagnose failures of rolling bearings. Accuracy and delay in detecting and diagnosing …

A new technique for an automated detection and diagnosis of rolling bearing faults is
presented. The time-domain vibration signals of rolling bearings with different fault …

We present a generic methodology for machinery fault diagnosis through pattern recognition
techniques. The proposed method has the advantage of dealing with complicated …