A time-discrete and zero-adjusted gamma process model with application to degradation analysis

2020 ◽  
Vol 560 ◽  
pp. 125180 ◽  
Author(s):  
Kai Song ◽  
Jian Shi ◽  
Xiaojian Yi
Keyword(s):  
Process Model ◽  
Gamma Process ◽  
Degradation Analysis

Bayesian information fusion for degradation analysis of deteriorating products with individual heterogeneity

2018 ◽  
Vol 233 (4) ◽  
pp. 615-622 ◽  
Author(s):  
Junyu Guo ◽  
Hong-Zhong Huang ◽  
Weiwen Peng ◽  
Jie Zhou
Keyword(s):  
Reliability Analysis ◽  
Information Fusion ◽  
Process Model ◽  
High Reliability ◽  
Small Sample Size ◽  
Small Sample ◽  
Gamma Process ◽  
Individual Heterogeneity ◽  
Multiple Sources ◽  
Degradation Analysis

Degradation analysis is a popular and effective method for reliability analysis of long-life and high-reliability products. However, for newly developed products, especially for highly customized products with small sample size, the challenge of sparse degradation observations with product heterogeneity is still an open issue deserving further research. In this article, Bayesian degradation analysis is presented for reliability analysis of products with heterogeneity. The degradation process is modeled by a Gamma process. Random effects are incorporated in the Gamma process model for characterizing the individual heterogeneity. To improve the precision of parameter estimation and degradation analysis, a Bayesian information fusion is presented to leverage degradation information from multiple sources. The proposed model is demonstrated through degradation-based reliability analysis of heavy-duty machine tool’s spindle system, which is characterized as degradation analysis with individual heterogeneity and information fusion.

scholarly journals Degradation analysis on high-cycle bending fatigue for woven SiC/SiC composites based on Wiener process model

2021 ◽  
Vol 198 ◽  
pp. 109295
Author(s):  
Xi Liu ◽  
Rongqiao Wang ◽  
Dianyin Hu ◽  
Long Zhang ◽  
Gaoxiang Chen
Keyword(s):  
Wiener Process ◽  
Process Model ◽  
Bending Fatigue ◽  
Degradation Analysis ◽  
Sic Composites

Lifetime estimation of LED lamp using gamma process model

2016 ◽  
Vol 57 ◽  
pp. 71-78 ◽  
Author(s):  
Sung Ho Park ◽  
Jae Hoon Kim
Keyword(s):  
Process Model ◽  
Gamma Process ◽  
Lifetime Estimation

scholarly journals Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

2021 ◽  
Author(s):  
Adetola Adegbola ◽  
Arnold Yuan
Keyword(s):  
Decision Making ◽  
Random Field ◽  
Process Model ◽  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Gamma Process ◽  
Model Parameters ◽  
Two Dimensional ◽  
Practical Application

Deterioration is a major problem facing engineering structures, systems and components (SSCs). To maintain the structural integrity and safe operation of such SSCs all through their service life, it is important to understand how degradation phenomena progress over time and space. Hence degradation modelling has been increasingly used to model existing deterioration, predict future deterioration as well as provide input for infrastructure management in terms of inspection and maintenance decision making. As deterioration is known to be random, modelling of spatial and temporal uncertainty remains a crucial challenge for infrastructure asset professionals. The main objective of the thesis is to develop sophisticated models for characterizing spatial and temporal uncertainties in deterioration modelling with a view to enhancing decision making under uncertainty. The thesis proposes a two-dimensional copula-based gamma distributed random field for the spatial uncertainties, and a copula-based multivariate gamma process model to characterize stochastic dependence of multiple degradation phenomena. Techniques for estimating the model parameters and simulating the field or process, prediction of the remaining lifetime distribution as well as condition-based maintenance optimization are also presented. To study the extreme value distribution of the random field, the thesis also presents a numerical method based on the Karhunen-Loève expansion for evaluating extrema of both one- and two-dimensional homogeneous random fields. The simulation results are benchmarked against existing analytical models for special cases. In addition, the study also investigates the effect of parameter (epistemic) uncertainty on the extreme value distribution of the field. Finally, the thesis presents a practical application of the proposed copula-based gamma field by treating the wall profile of a feeder pipe as one- and twodimensional gamma fields. The thesis demonstrates a practical application of the multivariate gamma process model to rutting, cracking, and surface roughness of highway pavements. In summary, the proposed models have advanced the knowledge and techniques of stochastic deterioration modelling in the engineering field.

A Wiener process model for accelerated degradation analysis considering measurement errors

2016 ◽  
Vol 65 ◽  
pp. 8-15 ◽  
Author(s):  
Junxing Li ◽  
Zhihua Wang ◽  
Xia Liu ◽  
Yongbo Zhang ◽  
Huimin Fu ◽  
...  
Keyword(s):  
Wiener Process ◽  
Measurement Errors ◽  
Process Model ◽  
Accelerated Degradation ◽  
Degradation Analysis
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