In order to supply a gap of current resonance vibration and STFT demodulation method applied to rolling bearing fault feature extraction of city rail vehicle, a fault diagnosis method for rolling bearing is presented, which is based on the integration of improved wavelet packet, frequency energy analysis and Hilbert marginal spectrum. When faults occur in rolling bearing, the energy of the roll...

Aiming at the fault diagnosis of rolling element bearings, propose a method for fine bearings based on wavelet transform and one-dimensional convolutional neural network. First use to decompose experimental data; Use resulting low-frequency signal as network input, bearing identification. The experiment uses deep groove ball Case Western Reserve University research object, this identify normal ...

An apparatus to simulate the thermal behavior of a 3/4 inch bore tapered roller bearing was constructed and used to determine tapered roller bearing thermal behavior. Bearing specimens can be loaded axially and/or radially while rotating. Shaft heating is also provided and mechanical losses measured. An infrared scanner and thermocouples allow for temperature measurement. An analytical model of...

Rolling bearing is main part of rotary machine. It is frail section of rotary machine. Its running status affects entire mechanical equipment system performance directly. Vibration acceleration signals of the third finishing mill of Anshan Steel and Iron Group wire plant were collected in this paper. Fourier analysis, power spectrum analysis and wavelet transform were made on collected signals....

This paper focuses on the problem of accurate Fault Characteristic Frequency (FCF) estimation of rolling bearing. Teager-Kaiser Energy Operator (TKEO) demodulation has been applied widely to rolling bearing fault detection. FCF can be extracted from vibration signals, which is pre-treatment by TEKO demodulation method. However, because of strong noise background of fault vibration signal, it is...

Rolling-element bearings are widely used in various mechanical and electrical systems. A reliable online bearing fault diagnostic technique is critically needed in industries to detect the occurrence of a fault so as to prevent system’s performance degradation and malfunction. To improve the fault diagnostic reliability and efficiency, a genetic algorithm based feature optimization technique is...

Rolling element bearing failure is one of the foremost causes of breakdown in rotating machinery. It is not uncommon to replace a defected/used bearing with a new one that has shorter remaining useful life than the defected one. Thus, prognostics of bearing plays critical role for increased availability and reduced cost. Effective prognostics highly depend on the quality of the extracted featur...

The demand for silent bearing applications has resulted in the development of an effective damping layer between the outer ring of a rolling bearing and the surrounding structure. By means of numerical modeling using both FEM and BEM techniques an induction motor for household appliances is analyzed. A hybrid modeling approach combining measured structural velocities with a BEM formulation is u...

This paper introduces a dynamic classification method inspired by DBSCAN clustering method for machine condition monitoring in general and for bearings in particular. This method has been developed for two purposes; first to monitor the health condition of a bearing in real time and second to study the behavior of defected rolling element bearing. To fulfill those purposes, the temporal indicat...

This paper presents a mathematical model to investigate the nonlinear dynamic behavior of a high speed rotor-bearing system due to defects of rolling elements. Two defects have been considered for the study, one defect as off-sized rolling elements and other defect as rolling element waviness. In the formulation, the contacts between rolling elements and inner/outer races are considered as nonl...