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In this research, a combination of the physical model based on Paris law and probability method is proposed for remaining useful life prediction of rolling element bearings. Level crossing is used as a feature that represents a linear relationship with defect size. Considering this linear relationship and using Paris law, a new model has been developed for bearings that follow degradation pattern...
Empirical mode decomposition (EMD) is powerful in analyzing the vibration signals of bearings. However, the accuracy of its decomposition result is heavily dependent on the choice of envelope interpolation algorithms. In this paper, we propose a bandwidth method to select the envelope in EMD called bandwidth based EMD (BEMD). Since there is an optimization process in envelope selection, the scale...
Time-frequency distribution (TFD) methods have been widely used for planetary gearbox fault detection. The aim of TFD is to represent a signal by a joint energy distribution in the time-frequency domain. Positivity is one of the most important properties for TFDs. Copula-based positive TFD construction methods utilize the time marginal, the frequency marginal and the dependence structure between the...
This paper investigates the vibration properties of a planetary gear set. A two-dimensional lumped mass model is developed to simulate the vibration signals of a planetary gear set in the perfect and crack situations. Through dynamic simulation, the vibration signals of each individual component can be simulated, including the vibration signals of the sun gear, each planet gear, and the ring gear...
Bearing is the most frequently and easily failed component in any rotating machine. The extraction of the bearing feature signal is critical for signal analysis and fault diagnosis of bearings. In this paper, an adaptive signal processing method is proposed to extract a weak bearing signal from a raw vibration signal. To provide sufficient extremes for signal decomposition using the ensemble empirical...
Planetary gears are widely used in aeronautic and industrial applications because of the properties of compactness and high torque-to-weight ratios. Due to high service load, harsh operating conditions or simply fatigue, faults may develop in gears. If the faults cannot be detected early, the health condition will continue to degrade, even the consequence of big economic loss or catastrophic accident...
Linear discriminant analysis (LDA) is a method of feature extraction that has demonstrated successful applications. The selection of the number of discriminant directions (r) is important to LDA, yet little attention is paid in the reported literature. In this paper a method is proposed for determining the optimal r in terms of the classification accuracy of support vector machine. The method is applied...
With regard to the AMFM characteristics, and especially the cyclostationarity of gear vibrations, cyclic spectral analysis is used to extract the modulation features of gearbox vibration signals to detect and assess localized gear damage. The explicit equation for the cyclic spectral density in a closed form for AMFM signals is deduced, and its properties in the joint cyclic frequency-frequency domain...
Matching pursuit is effective in matching the characteristic structure of signals and extracting the time-frequency features directly. It is employed to analyze the vibration signals of a gearbox under healthy and faulty statuses. Based on a compound dictionary, the periodic impulses characterizing the vibration of localized damaged gears are extracted in joint time-frequency domain, and the localized...
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