Corrosion Prediction Based on Probability Weighted Gray Markov Model
Accurately predicting the corrosion development trend of pipelines is one of the main ways to reduce the loss of leakage accidents and ensure their safe production and transportation.In this paper,a gray Markov model based on probability weights is proposed to predict the corrosion of oil and gas pipelines.Firstly,the gray model was used to make a preliminary prediction of the corrosion state of the pipeline.Then,the fuzzy C-means clustering was used to cluster the prediction error data,and a Markov model based on probability weight was proposed to improve the prediction accuracy in the case of equal transition probability.Finally,the effectiveness and correctness of the above model were verified through two examples,and compared with the gray Markov model based on the cluster center.
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