Zhangchun Tang

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In order to extract fault features of large-scale power equipment from strong background noise, a hybrid fault diagnosis method based on the second generation wavelet de-noising (SGWD) and the local mean decomposition (LMD) is proposed in this paper. In this method, a de-noising algorithm of second generation wavelet transform (SGWT) using neighboring(More)
Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault(More)
For structural systems with both epistemic and aleatory uncertainties, the effect of epistemic uncertainty on failure probability is measured by the variance based sensitivity analysis, which generally needs a ‘‘triple-loop’’ crude sampling procedure to solve and is time consuming. Thus, the Kriging method is employed to avoid the complex sampling procedure(More)
SOME degree of variation exists in the output of structure systems for most practical applications due to the presence of the uncertainties, such as variation of material properties, fluctuation of external loads, etc. Deterministic design optimization (DDO) does not consider the uncertainties, and the obtained optimum solutions generally are not robust due(More)
For the structural systems with both epistemic and aleatory uncertainties, in order to analyze the effect of the epistemic uncertainty on the safety of the systems, a variance based importance measure of failure probability is constructed. Due to the large computational cost of the proposed measure, a novel moving least squares (MLS) based method is(More)
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