A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings

A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings

Cyclic spectral analysis of rolling-element bearing signals : Facts and fictions

Induction machine drive condition monitoring and diagnostic research—a survey

A new concept referred to as progression-based prediction of remaining life (PPRL) is proposed in the present paper in order to solve the problem of accurately predicting the remaining bearing life. The basic concept behind PPRL is to apply different prediction methods to different bearing running stages. A new prediction procedure which predicts precisely the remaining bearing life is developed on the basis of variables characterizing the state of a deterioration mechanism which are determined from on-line measurements and the application of PPRL via a compound model of neural computation. The procedure consists of on-line modelling of the bearing running state via neural networks and logic rules and not only can solve the boundary problem of remaining life but also can automatically adapt to changes in environmental factors. In addition, multi-step prediction is possible. The proposed technique enhances the traditional prediction methods of remaining bearing life.

Prognosis of remaining bearing life using neural networks

A brief review on techniques of machine condition monitoring is presented followed by a description and results of a study involving the monitoring of vibration signatures of several rolling element bearings with a view to detecting incipient failure. The vibration data were analyzed and several parameters were assessed with regard to their effectiveness in the detection of bearing condition. It was found that all the parameters were of some value depending on the type of bearing failure encountered. Generally, frequency domain parameters were more consistent in the detection of damage than time domain parameters. However, sufficient evidence is produced to show that it would be unreliable to depend exclusively on any one technique to detect bearing damage.

J. Mathew

Papers

The condition monitoring of rolling element bearings using vibration analysis