Residual life prediction method for two-stage degraded product

A life prediction and stage technology, applied in prediction, design optimization/simulation, data processing applications, etc., can solve the problems of derivation of analytical solutions ignoring degradation nonlinearity and life, low prediction accuracy of life prediction methods, etc.

Pending Publication Date: 2020-04-21
CHONGQING UNIV
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Problems solved by technology

For such two-stage degradation products, traditional life prediction methods are not accurate enough
[0004] In order to improve the prediction accuracy, many researchers have proposed a two-stage degradation model, but t

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  • Residual life prediction method for two-stage degraded product
  • Residual life prediction method for two-stage degraded product
  • Residual life prediction method for two-stage degraded product

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Embodiment Construction

[0061] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the preferred embodiments are only for illustrating the present invention, but not for limiting the protection scope of the present invention.

[0062] The implementation process of this embodiment specifically includes: modeling of the degradation process, estimation of model parameters and prediction of remaining life. Based on MATLAB tools, numerical simulations are used for illustration, and the effects of the present invention are shown in conjunction with the accompanying drawings. figure 1 It is a flow chart of life prediction of two-stage degraded products, as shown in the figure, this method specifically includes the following steps:

[0063] Step 1: Modeling the degradation process. figure 2 It is a schematic diagram of the degradation of a two-stage degradation product. It can be seen from the figure ...

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Abstract

The invention discloses a residual life prediction method for a two-stage degraded product, which belongs to the field of residual life prediction in prediction and health management, and mainly comprises the steps of degradation process modeling, model parameter estimation and residual life prediction, wherein the degradation process modeling is to establish a two-stage degradation model by usinga nonlinear Wiener process; the model parameter estimation comprises the following steps: collecting historical degradation data; estimating model parameters based on a unit maximum likelihood estimation method; statistical analysis of random parameter distribution; the residual life prediction comprises the following steps: obtaining first arrival time distribution; deriving a state transition probability function; and predicting the residual life of the product based on the estimated parameters. The residual life of the two-stage degraded product can be effectively predicted, the operationreliability of the product is ensured, the maintenance cost is reduced, and safety accidents are avoided.

Description

technical field [0001] The invention belongs to the field of prediction and health management, and relates to a method for predicting the remaining life of a two-stage degraded product. Background technique [0002] Remaining life prediction is the core content of prediction and health management technology. It refers to the effective time interval for the product to lose the specified function at the current moment. It is an important indicator reflecting product reliability. important to economics. [0003] In the past ten years, residual life prediction has received extensive attention and in-depth research. Among them, the Wiener process has been greatly developed because it can describe non-monotonic degenerate trajectories and has good mathematical properties. But it is worth noting that in most life prediction methods based on the Wiener process, the degradation rate is usually fixed and does not change with time. However, in actual engineering, due to changes in e...

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Application Information

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IPC IPC(8): G06F30/20G06Q10/04G06F119/04
CPCG06Q10/04
Inventor 林景栋陈敏林正王静静
Owner CHONGQING UNIV
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