Reliability Modeling of Aircraft Feel Simulator with Time-Varying Dependent Degradation Processes

2019 ◽  
Author(s):  
Linjie Shen ◽  
Yugang Zhang ◽  
Bifeng Song
Keyword(s):  
Time Varying ◽  
Reliability Modeling ◽  
Degradation Processes

scholarly journals A Copula Entropy Approach to Dependence Measurement for Multiple Degradation Processes

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 724 ◽  
Author(s):  
Fuqiang Sun ◽  
Wendi Zhang ◽  
Ning Wang ◽  
Wei Zhang
Keyword(s):  
Information Entropy ◽  
Complex Structure ◽  
Copula Function ◽  
Dependence Structure ◽  
Entropy Theory ◽  
Multiple Features ◽  
Reliability Modeling ◽  
Degradation Processes ◽  
Degradation Analysis ◽  
Complex Dependence

Degradation analysis has been widely used in reliability modeling problems of complex systems. A system with complex structure and various functions may have multiple degradation features, and any of them may be a cause of product failure. Typically, these features are not independent of each other, and the dependence of multiple degradation processes in a system cannot be ignored. Therefore, the premise of multivariate degradation modeling is to capture and measure the dependence among multiple features. To address this problem, this paper adopts copula entropy, which is a combination of the copula function and information entropy theory, to measure the dependence among different degradation processes. The copula function was employed to identify the complex dependence structure of performance features, and information entropy theory was used to quantify the degree of dependence. An engineering case was utilized to illustrate the effectiveness of the proposed method. The results show that this method is valid for the dependence measurement of multiple degradation processes.

scholarly journals Reliability Modeling for Systems with Multiple Degradation Processes Using Inverse Gaussian Process and Copulas

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenyu Liu ◽  
Xiaobing Ma ◽  
Jun Yang ◽  
Yu Zhao
Keyword(s):  
Degradation Process ◽  
Reliability Estimation ◽  
Scale Transformation ◽  
Distribution Model ◽  
Inverse Gaussian ◽  
Random Drift ◽  
Reliability Modeling ◽  
Degradation Processes ◽  
Inverse Gaussian Process ◽  
Comparison Results

We develop a reliability model for systems with s-dependent degradation processes using copulas. The proposed model accommodates assumptions of s-dependence among degradation processes and allows for different marginal distributions. This flexibility makes the model more attractive compared with the multivariate distribution model, which lay on the limitation of the homogeneous marginal distribution and can only describe linear correlation. Marginal degradation process is modeled by the inverse Gaussian (IG) process with time scale transformation. Furthermore, we incorporate random drift to account for the possible heterogeneity in population. This paper also develops the statistical inference method using EM algorithm with two-stage procedure. The comparison results of the reliability estimation under both s-dependent and s-independent assumptions are illustrated in the illustrative example to demonstrate the applicability of the proposed method.

Remaining Useful Life Estimation for Systems with Time-varying Mean and Variance of Degradation Processes

2014 ◽  
Vol 30 (6) ◽  
pp. 829-841 ◽  
Author(s):  
Jian-xun Zhang ◽  
Chang-hua Hu ◽  
Xiao-sheng Si ◽  
Zhi-jie Zhou ◽  
Dang-bo Du
Keyword(s):  
Remaining Useful Life ◽  
Time Varying ◽  
Life Estimation ◽  
Degradation Processes ◽  
Mean And Variance ◽  
Useful Life

scholarly journals Reliability Modeling of PV Systems Based on Time-Varying Failure Rates

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 14367-14376 ◽  
Author(s):  
Hamza Abunima ◽  
Jiashen Teh
Keyword(s):  
Time Varying ◽  
Failure Rates ◽  
Reliability Modeling ◽  
Pv Systems
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