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Corrosion pipeline Bayesian degradation analysis method considering random effect

An analysis method and random effect technology, applied in special data processing applications, instruments, calculations, etc., can solve problems such as complex pipeline operating environment, low precision, and large error in model prediction results, achieving strong flexibility, improving accuracy, Avoid the effect of large forecast errors

Active Publication Date: 2019-08-02
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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Problems solved by technology

[0006] The above methods have achieved certain results through the application of different stochastic processes, but there are many problems in these applications. Due to the complexity of the pipeline operating environment and the influence of various factors, there are many uncertainties in the degradation process. Effect model prediction results have large errors and low precision

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  • Corrosion pipeline Bayesian degradation analysis method considering random effect
  • Corrosion pipeline Bayesian degradation analysis method considering random effect
  • Corrosion pipeline Bayesian degradation analysis method considering random effect

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Embodiment Construction

[0037] The present invention will be described in further detail below in conjunction with the accompanying drawings:

[0038] The Bayesian degradation analysis method of corroded pipelines considering random effects of the present invention includes the following steps:

[0039] 1) Describe the corrosion degradation process of the pipeline through the IG process, and establish a Bayesian analysis framework for model analysis, where the Bayesian analysis framework includes the derivation of the prior distribution, the construction of the likelihood function, the acquisition of the posterior distribution, and Analysis process;

[0040] 2) Analyze the inverse Gaussian process model, random drift inverse Gaussian model, random fluctuation inverse Gaussian model, and random drift-fluctuation inverse Gaussian model respectively by using Bayesian method;

[0041] The likelihood function of degenerate data under the inverse Gaussian process model is Get t m+1 Reliability function at time T...

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Abstract

The invention discloses a corrosion pipeline Bayesian degradation analysis method considering a random effect. The method comprises the following steps: 1) describing a corrosion degradation process of a pipeline through an IG process; 2) analyzing each model, a random drift inverse Gaussian model, a random fluctuation inverse Gaussian model and a random drift- fluctuation inverse Gaussian model by using a Bayesian method; 3) checking the applicability of each model by utilizing Bayesian x2 fitting goodness; 4) utilizing each model to simulate and generate random degradation data, and then utilizing a Bayesian analysis method to carry out priori analysis and sample size comprehensive sensitivity analysis; 5) substituting random degradation data generated by simulation in the step 4) into each model, performing parameter estimation through Monte Carlo simulation, and selecting an optimal model; and 6) estimating a relation function of the residual life of the pipeline, the probability density function and the service time by using the optimal model obtained in the step 5). The method considers a random effect to realize high-precision prediction of the corroded pipeline.

Description

Technical field [0001] The invention belongs to the technical field of oil and gas pipeline transportation, and relates to a Bayesian degradation analysis method for corroded pipelines considering random effects. Background technique [0002] With the continuous improvement of the reliability and safety requirements of key equipment, the continuous advancement of condition monitoring technology, accurately assessing and predicting the probability of equipment failure in the future, has become a hot issue in recent years. Pipelines have many advantages such as long life and high reliability. However, their high cost, small batch size, and complex failure modes and failure mechanisms have made it possible for us to conduct reliability modeling and remaining useful life (RUL) predictions in China. Technical problems that have been widely concerned and researched abroad. [0003] The development of China's pipeline industry has experienced three construction climaxes, namely the 1970s...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20Y02P90/30
Inventor 张新生吕品品张平裘瑾叶晓燕
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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