Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Remaining Life Prediction Method Based on Two-Stochastic Degradation Modeling

A technology of life prediction and degradation model, applied in design optimization/simulation, computer-aided design, instrument, etc., can solve problems such as analytical life probability density function, difficult remaining life prediction, etc.

Active Publication Date: 2020-01-21
SHANDONG UNIV OF SCI & TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing two-order Wiener process degradation model has not given the probability density function of analytical life and the probability density function of remaining life in the sense of the first arrival, so that it is difficult to predict the remaining life online

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Remaining Life Prediction Method Based on Two-Stochastic Degradation Modeling
  • A Remaining Life Prediction Method Based on Two-Stochastic Degradation Modeling
  • A Remaining Life Prediction Method Based on Two-Stochastic Degradation Modeling

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0063] In order to help understand the present invention and demonstrate its effect on fault detection, an example will be described in detail below. This example is based on the MATLAB tool, using actual battery degradation data to illustrate the present invention, and demonstrates the effect of the present invention in conjunction with the accompanying drawings.

[0064] 1. The flow of the offline modeling process is as follows: figure 1 As shown, specific to this example, the specific steps are as follows:

[0065] Step 1.1: Collect four sets of battery degradation data such as image 3 As shown, select three groups (CS2-35, CS2-37, CS2-38) for offline model identification;

[0066] Step 1.2: Define the two-stage degradation model as follows:

[0067]

[0068] Among them, in order to describe the difference between different samples, l...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a remaining life prediction method based on two-stage stochastic degradation modeling, which belongs to the field of industrial monitoring and fault diagnosis. The invention mainly includes: offline modeling and online parameter update and remaining life prediction; wherein the offline modeling process includes : Collection of historical degradation data; using maximum likelihood estimation to obtain the estimated value of each set of degradation change points, and using statistical analysis to obtain the distribution characteristics of the change points; based on the expectation maximization algorithm, the parameters of the two-stage degradation model are identified offline; The parameter estimates obtained offline and the statistical characteristics of the change point distribution are used as prior information for online parameter updates; online parameter estimation and remaining life prediction include: online collection of degradation data; online update of model parameters based on Bayesian theory; update based on The latter parameters estimate the remaining life of the currently operating equipment. The invention can model the degradation data with two-stage characteristics, and can accurately predict its remaining life.

Description

technical field [0001] The invention belongs to the field of industrial monitoring and fault diagnosis, in particular to a method for predicting remaining life based on two-stage stochastic degradation modeling. Background technique [0002] The remaining life prediction method refers to the estimation and prediction of the remaining operating time of equipment by using historical and current operating data. Because this method can provide a theoretical basis for maintenance decisions and ensure safe and reliable operation of equipment, it is a key issue in prediction and health management technology, and has received extensive attention and in-depth research in recent years. [0003] Due to the switching of external environmental stress and the change of internal degradation mechanism, it is difficult to keep consistent the degradation rate and fluctuation range of equipment during operation. Therefore, the existing single-stage method is no longer applicable, and it is ne...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20G06F119/04
CPCG16Z99/00
Inventor 周东华张峻峰何潇张建勋张海峰卢晓
Owner SHANDONG UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com