This work presents the analysis of vibration signals a ball bearing, available on platform Case Western Reserve University in form MATLAB files. By proposing an approach for diagnosis any rotating machine and detects failed components simple way, proposed consists several methods steps each complementary to other. First decomposing signal by feature mode decomposition (FMD) method then, accordi...

Abstract: The proposed method allows determining the level of wear of the bearings of electric machines by means of rotor radial displacement during operation. Measurement is effected by non-contact method and optoelectronic sensor which converts the rotor mechanical motion into electric signal. Received informational signal is recorded and processed by computer system. Based on the processed i...

The paper introduces the concept of fault diagnosis using an observer bank of autoregressive time series models. The concept was applied experimentally to diagnose a number of induced faults in a rolling element bearing using the measured time series vibration signal. Three distinct techniques of autoregressive modeling were compared for their performance and reliability under conditions of var...

Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, multiscale permutation entropy (MPE) was introduced for feature extraction from faulty bearing vibration signals. After extracting feature vectors by MPE, the support vec...