Remaining useful life prediction of aero-engines based on random-coefficient regression model considering random failure threshold

Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomness of failure threshold.Firstly,a random-coefficient regression(RCR)model is used to model the degradation process of aeroengines.Then,the RUL distribution based on fixed failure threshold is derived.The prior parameters of the degradation model are calculated by a two-step maximum likelihood estimation(MLE)method and the random coefficient is updated in real time under the Bayesian framework.The failure threshold in this paper is defined by the actual degradation process of aeroengines.After that,a expectation maximization(EM)algorithm is proposed to estimate the underlying failure threshold of aeroengines.In addition,the conditional probability is used to satisfy the limitation of failure threshold.Then,based on above results,an analytical expression of RUL distribution of aero-engines based on the RCR model considering random failure threshold(RFT)is derived in a closed-form.Finally,a case study of turbofan engine is used to demonstrate the effectiveness and superiority of the RUL prediction method and the parameters estimation method of failure threshold proposed.

Remaining useful life estimation based on Wiener degradation processes with random failure threshold

Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.

Error Threshold of Fully Random Eigen Model

Species evolution is essentially a random process of interaction between biological populations and their environ- ments. As a result, some physical parameters in evolution models are subject to statistical fluctuations. In this work, two important parameters in the Eigen model, the fitness and mutation rate, are treated as Gaassian dis- tributed random variables simultaneously to examine the property of the error threshold. Numerical simulation results show that the error threshold in the fully random model appears as a crossover region instead of a phase transition point, and ＆s the fluctuation strength increases the crossover region becomes smoother and smoother. Furthermore, it is shown that the randomization of the mutation rate plays a dominant role in changing the error threshold in the fully random model, which is consistent with the existing experimental data. The implication of the threshold change due to the randomization for antiviral strategies is discussed.

NEW METHOD FOR MEASURING RANDOM THRESHOLDS OF LONG FATIGUE CRACK PROPAGATION

A so-called 'local probabilistic Paris relation method' was presented for measuring the random thresholds of long fatigue crack propagation. A check was made to the conventional method, in which the thresholds were measured statistically and directly by the test data. It was revealed that this method was not reasonable because the test data have seldom a unified level of crack growth rates. Differently,in the presented method the Paris-Erdogan equation was applied to model the local test data around the thresholds. Local probabilistic relations with both the survival probability and the confidence were established on a lognormal distribution of the stress density factors. And then, the probabilistic thresholds were derived from the probabilistic factors with a given critical level of growth rate. An analysis on the test data of LZ50 axle steel for the Chinese railway vehicles verifies that the present method is feasible and available.

Random lasing from dye-doped negative liquid crystals using ZnO nanoparticles as tunable scatters

This work demonstrates the realization of a lasing in scattering media,which contains dispersive solution of Zn O nanoparticles（NPs） and laser dye 4-dicyanomethylene-2-methyle-6-（p-dimethylaminostyryl）-4H-pyran（DCM） in negative liquid crystals（LCs） that was injected into a cell.The lasing intensity of the dye-doped negative LC laser can be tuned from low to high if the NPs concentration is increased.The tunability of the laser is attributable to the clusters-sensitive feature in effective refractive index of the negative LCs.Such a tunable negative liquid crystal laser can be used in the fabrication of new optical sources,optical communication,and liquid crystal laser displays.