In this paper, a novel approach is proposed to determine target reliability index based on modeling performance degradation of concrete structures as a stochastic process. First, the Wiener process with drift is used to simulate the degradation process of relative dynamic elastic modulus of concrete, and the drift coefficient and diffusion coefficient of Wiener process are estimated according to the experimental data of degradation of relative dynamic elastic modulus. Then, based on the relations between concrete compressive strength, dynamic elastic modulus, and relative dynamic elastic modulus, the relationship between compressive strength and the amount of degradation of relative dynamic elastic modulus are deduced, and then, the statistical parameters of concrete compressive strength under different service time can be calculated. Finally, based on the established limit state equation of flexural capacity of the weak section and the statistical parameters of compressive strength at different times, the reliability index of a structure under different service life is calculated. On the other hand, according to the drift Wiener process model of relative dynamic elastic modulus degradation of concrete, the time‐varying failure probability of structural durability degradation is calculated based on the first‐passage failure probability formula of drift Wiener process. Taking a concrete plant structure as an example, the time‐varying reliability index calculated based on the limit state equation and the time‐varying failure probability obtained based on the first‐passage failure probability analysis of drift Wiener process are compared, and then the recommended values of target reliability index of structural bearing capacity are comprehensively determined.

A Wiener degradation process with drift‐based approach of determining target reliability index of concrete structures

Coupling plasma plume of a low-power magnetically shielded Hall thruster with a hollow cathode

In this paper, fatigue life of solder joints of the power module and the printed circuit board in a power inverter under directional random vibration using the finite element method (FEM) was evaluated. Five angles of 0°, 30°, 45°, 60°, and 90° were selected for direction of vibration loading. The simulation results showed that the outermost corner of the solder layer undergoes the maximum stress during the vibration frequencies in all the situations. In general, with the increase of input frequency, the solder joints got more susceptible to the catastrophic failure. Moreover, it was found that in lower angles of loading direction, the peeling stress is dramatically increased in the solder layer. This event can be attributed to the considerable portion of shear stress in loading directions with lower angles. The experimental results also proved the FEM simulation and showed that the void growth and coalescence, resulted by fatigue, are intensified in the lower angles of vibration loading. Overall, this paper indicates that the reliability of a power module under a normal loading (90°) is the highest among all other conditions.

Influence of Directional Random Vibration on the Fatigue Life of Solder Joints in a Power Module

Accurate remaining useful life (RUL) prediction has a great significance to improve the reliability and safety for key equipment. However, it often occur imperfect or even no prior degradation information in practical application for the existing RUL prediction methods, which could produce prediction error. To solve this issue, this paper proposes a two-step RUL prediction method based on Wiener processes with reasonably fusing the failure time data and field degradation data. First, we obtain some interesting natures of parameters estimation based on the basic linear Wiener process. These natures explain the relationship between the parameters estimation results and the feature of degradation data, i.e. item sample numbers, detection time and detect frequency, and give the basis regarding how to reasonably fuse the failure time data and field degradation data. Second, under the Bayesian framework, we further propose a two-step method by fusing the failure time data and field degradation data with considering the random effects based on the proposed natures of parameters estimation. In this method, we propose an EM algorithm to estimate the mean and variance drift parameter of Wiener processes by the failure time data. Next, we generalize this two-step RUL prediction method to the nonlinear Wiener process. Last, we use two case studies to demonstrate the usefulness and superiority of the proposed method.

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Remaining Useful Life Prediction With Fusing Failure Time Data and Field Degradation Data With Random Effects

In this work, three different arrangements of circuit board in an electronic device were designed and the effects of random vibration frequencies on the reliability of ball grid arrays (BGA) in the...

Improving the reliability of ball grid arrays under random vibration by optimization of module design

Remaining useful life prediction based on variation coefficient consistency test of a Wiener process

The degradation behavior of the solder joint under constant vibration loading is discussed, the voltage value at both sides of the solder joint is taken as the degradation characteristic. Considering the heteroskedasticity of characteristic signal under the vibration loading, the general time series model cannot describe heteroskedasticity, a Generalized Autoregressive Conditional Heteroskedastic model (GARCH) is proposed. Firstly, the upper and lower quantiles of the voltage signal are extracted. The failure time is determined by using the upper quantile and the degradation process is analyzed by the lower quantile. Secondly, the Auto-Regressive(AR) is built as the regressive basic model. Thirdly, a GARCH(1,1) model is proposed, which is tested by the Autoregressive Conditional Heteroskedastic (ARCH) method, the parameters of the model is estimated by the Maximum Likelihood algorithm. Finally, the performance of the presented GARCH based degradation model is examined by real data from experiment, which is compared with the classical AR model according to Akaike Information Criterion(AIC). The results suggest that GARCH(1,1) is superior to AR model, presented a theoretical foundation for further study about the degradation modeling of solder joint under vibration loading.

GARCH based degradation modeling of solder joint under vibration loading

Remaining useful life prediction is the core of condition-based maintenance under the technology framework of prognostic and health management. But the remaining useful life of airborne fuel pump a...

Hongde Dai

Papers

Remaining useful life prediction based on variation coefficient consistency test of a Wiener process

GARCH based degradation modeling of solder joint under vibration loading

A remaining useful life prediction method for airborne fuel pump after maintenance