In rotordynamic simulations, rolling element bearing waviness is often accounted using nonlinear models that are solved with a numerical integration scheme in time domain. This approach generates accurate system response, but the method limited terms of computational efficiency. study proposes two novel methods for solution responses caused by excitation frequency domain, and compares result pr...

This paper presents a rolling bearing fault diagnosis approach by integrating wavelet packet decomposition (WPD) with multi-scale permutation entropy (MPE). The approach uses MPE values of the sub-frequency band signals to identify faults appearing in rolling bearings. Specifically, vibration signals measured from a rolling bearing test system with different defect conditions are decomposed int...

austenite is a semi-stable phase in most stainless steels that deforms to martensite under md30 and forms martensitetype ά and ε due to the deformation in the steels. since the distribution of strain induced martensite plays animportant role in achieving desired properties, the main objective of the present work is to model martensitedistribution of ά during cold rolling using finite element me...

A rolling bearing fault diagnosis method based on the Volterra series and kernel principal component analysis (KPCA) is proposed. In proposed method, first, improved genetic algorithm (IGA) used to identify model of in four states: normal, element fault, inner ring outer fault. The time-domain as feature vector for classify faults. feasibility level verified by experimental results.

Small piezoelectric transducers bonded to the outer raceway of a rolling element bearing can be used to send ultrasonic pulses to the element-raceway contact and receive reflections. Interpretation of the magnitude and time of flight (ToF) of the reflections can be used to deduce amount of load imparted between roller and raceway. The approach is most successful when the sensor is smaller than ...

A methodology based on multi-weights neural network (MWNN) is presented to identify faults of rolling bearing. With considerations of difficulties in analyzing rolling bearing vibration data, we analyzed how to extract time domain feature parameters of faults. Further, the time domain feature parameters extracted from fault signals are utilized to train multi-weights neural network for achievin...

Rolling contact fatigue tests on 100Cr6 steel were carried out with a ballon-rod tester. Microstructural damage was manifested by gradual hardness changes under the subsurface, and microcracks formed adjacent to inclusions; both being evidence of plastic deformation. The hardness increase appears to be due to the development of residual stress, while the microcracks form as a result of the conc...