Health state and reliability evaluation method for strong noise and aperiodic state monitoring

A health state, non-periodic technology, applied in the field of health state estimation and remaining life prediction, system reliability evaluation, can solve the problem of non-monotonic degradation model

Active Publication Date: 2020-05-15
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

Aiming at the non-monotonic problem of the degradation model under non-periodic monitoring time and noise environment, the present invention comb...

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  • Health state and reliability evaluation method for strong noise and aperiodic state monitoring
  • Health state and reliability evaluation method for strong noise and aperiodic state monitoring
  • Health state and reliability evaluation method for strong noise and aperiodic state monitoring

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Embodiment Construction

[0094] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0095] The realization frame of the present invention is as figure 1 As shown, it consists of two parts, namely offline model training and online estimation.

[0096] 1) Offline model training: Quantify the information and knowledge shared by a group of systems to form a training set. The unknown parameter set is then estimated by a model parameter estimation method, and a set of equipment systems are characterized by the model parameter set.

[0097] 2) Online estimation: Personalize the model for a specific individual system. When the model parameters take a specific value, the Gamma state space model can adaptively predict the future degradation state, so that the newly obtained state monitoring signal can be used for health state estimation and remaining service life prediction

[0098] The detailed steps of the technical solution adopted by the ...

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Abstract

The invention provides a health state and reliability evaluation method for strong noise and aperiodic state monitoring. The problem of heterogeneity between systems is solved. The heterogeneity between systems is described by relaxing a model parameter into a random variable in Gamma distribution, and the problem that a degradation model is non-monotonous in a non-periodic and noisy environment at a monitoring moment is solved. In combination with a measurement equation, a Gamma state space model is proposed to track the real degradation path of the system and estimate the remaining service life of the system, an unscented particle filter smoothing method is constructed to estimate the real degradation state from noisy measurement values, and a random expectation maximization method is adopted to estimate model parameters. According to the method, the problem of difference between systems is effectively solved, the real degradation path of the system is tracked, the real degradation state is estimated from noisy measurement values, and model parameters are estimated.

Description

technical field [0001] The invention relates to the field of system reliability evaluation, more specifically to the field of health state estimation and remaining life prediction. Background technique [0002] In electronic equipment systems, due to complex electromagnetic interference, limitations of sensor technology, and possible failure of state monitoring instructions, the obtained health state monitoring signals are usually polluted by noise and have non-equal intervals. In addition, due to the existence of manufacturing tolerances and changes in working conditions, equipment systems produced in the same batch may also show a high level of heterogeneity. Accurate remaining life prediction is of great engineering significance. [0003] Through the current literature search, it is found that most of the existing technologies analyze and solve one of the problems, and seldom consider all the above problems at the same time. For example, direct use of noisy monitoring s...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06F30/20
CPCG06Q10/04G06Q10/0639
Inventor 赵帅陈绍炜温鹏飞高萌黄登山
Owner NORTHWESTERN POLYTECHNICAL UNIV
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