Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
An Adjusted CUSUM-Based Method for Change-Point Detection in Two-Phase Inverse Gaussian Degradation Processes
by
Li, Qian
, Li, Mei
, Fu, Tian
in
adjusted CUSUM statistic
/ Batteries
/ change-point detection
/ Condition monitoring
/ Crack propagation
/ Degradation
/ degradation model
/ Electronic data processing
/ Failure analysis
/ Gallium arsenide
/ Gaussian process
/ Implements, utensils, etc
/ Inverse Gaussian process
/ Likelihood ratio
/ Maintenance and repair
/ Methods
/ Normal distribution
/ Parameter estimation
/ Product reliability
/ Reliability analysis
/ Statistical methods
/ Stochastic models
/ Useful life
2025
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
An Adjusted CUSUM-Based Method for Change-Point Detection in Two-Phase Inverse Gaussian Degradation Processes
by
Li, Qian
, Li, Mei
, Fu, Tian
in
adjusted CUSUM statistic
/ Batteries
/ change-point detection
/ Condition monitoring
/ Crack propagation
/ Degradation
/ degradation model
/ Electronic data processing
/ Failure analysis
/ Gallium arsenide
/ Gaussian process
/ Implements, utensils, etc
/ Inverse Gaussian process
/ Likelihood ratio
/ Maintenance and repair
/ Methods
/ Normal distribution
/ Parameter estimation
/ Product reliability
/ Reliability analysis
/ Statistical methods
/ Stochastic models
/ Useful life
2025
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
An Adjusted CUSUM-Based Method for Change-Point Detection in Two-Phase Inverse Gaussian Degradation Processes
by
Li, Qian
, Li, Mei
, Fu, Tian
in
adjusted CUSUM statistic
/ Batteries
/ change-point detection
/ Condition monitoring
/ Crack propagation
/ Degradation
/ degradation model
/ Electronic data processing
/ Failure analysis
/ Gallium arsenide
/ Gaussian process
/ Implements, utensils, etc
/ Inverse Gaussian process
/ Likelihood ratio
/ Maintenance and repair
/ Methods
/ Normal distribution
/ Parameter estimation
/ Product reliability
/ Reliability analysis
/ Statistical methods
/ Stochastic models
/ Useful life
2025
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
An Adjusted CUSUM-Based Method for Change-Point Detection in Two-Phase Inverse Gaussian Degradation Processes
Journal Article
An Adjusted CUSUM-Based Method for Change-Point Detection in Two-Phase Inverse Gaussian Degradation Processes
2025
Request Book From Autostore
and Choose the Collection Method
Overview
Degradation data plays a crucial role in the reliability assessment and condition monitoring of engineering systems. The stage-wise changes in degradation rates often signal turning points in system performance or potential fault risks. To address the issue of structural changes during the degradation process, this paper constructs a degradation modeling framework based on a two-stage Inverse Gaussian (IG) process and proposes a change-point detection method based on an adjusted CUSUM (cumulative sum) statistic to identify potential stage changes in the degradation path. This method does not rely on complex prior information and constructs statistics by accumulating deviations, utilizing a binary search approach to achieve accurate change-point localization. In simulation experiments, the proposed method demonstrated superior detection performance compared to the classical likelihood ratio method and modified information criterion, verified through a combination of experiments with different change-point positions and degradation rates. Finally, the method was applied to real degradation data of a hydraulic piston pump, successfully identifying two structural change points during the degradation process. Based on these change points, the degradation stages were delineated, thereby enhancing the model’s ability to characterize the true degradation path of the equipment.
Publisher
MDPI AG
Subject
/ Methods
This website uses cookies to ensure you get the best experience on our website.