Remaining life prediction method based on two-stage random degradation modeling

A life prediction and degradation model technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as difficult remaining life prediction, and analytical life probability density function has not been given

Active Publication Date: 2017-12-15
SHANDONG UNIV OF SCI & TECH
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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

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  • Remaining life prediction method based on two-stage random degradation modeling
  • Remaining life prediction method based on two-stage random degradation modeling
  • Remaining life prediction method based on two-stage random degradation modeling

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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...

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Abstract

The invention discloses a remaining life prediction method based on two-stage random degradation modeling, and belongs to the field of industrial monitoring and fault diagnosis. The method mainly comprises the step of off-line modeling and the step of on-line parameter updating and remaining life prediction; wherein the step of off-line modeling comprises the substeps that historical degradation data is collected; maximum likelihood estimation is used for obtaining a change-point estimation value of each group of degradation, and the distribution characteristics of change-points are obtained through statistic analysis; two-stage degradation model parameters are identified offline on the basis of an expectation maximization algorithm; the offline obtained parameter estimation values and statistical characteristics of the change-point distribution serve as prior information of online parameter updating; the step of on-line parameter estimation and remaining life prediction includes the substeps that degradation data is collected online; online updating based on Bayesian theory model parameters is conducted; the remaining life of currently running equipment is estimated based on the updated parameters. According to the method, the degradation data with two-stage characteristics can be modeled, and the remaining life of the degradation data can be accurately predicted.

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...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
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
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