Prediction and application of wax thickness on tube wall based on
improved DGM (1,1) model

Changkun Cheng; Menglong Zhao; Hui Shen; Benquan Li; Yanping Liu; Pei Yang

doi:10.1117/12.3032055

6 June 2024 Prediction and application of wax thickness on tube wall based on improved DGM (1,1) model

Changkun Cheng, Menglong Zhao, Hui Shen, Benquan Li, Yanping Liu, Pei Yang

Proceedings Volume 13175, International Conference on Computer Network Security and Software Engineering (CNSSE 2024); 131751E (2024) https://doi.org/10.1117/12.3032055
Event: 4th International Conference on Computer Network Security and Software Engineering (CNSSE 2024), 2024, Sanya, China

Abstract

In order to study the change of wax deposition thickness with time, an improved DGM (1,1) model was established based on the grey theory model. Taking indoor loop experiment and field pipeline data as examples, the weakening buffer operator and translation transform were introduced to improve the smoothness of the original sequence, and the different models were tested and compared. The results show that the average relative error of the traditional DGM (1,1) model is large, and the error of the improved model is greatly reduced after the weakening buffer operator treatment, and the d2 operator is more suitable for predicting the wax thickness of short sequence and wide spacing sequence. Translation transformation of the original sequence can improve the smoothness of the sequence, and different original sequences have selectivity on the offset of translation transformation function. The effect of weakening buffer operator on model improvement is much better than that of translational transformation. It is feasible to use the modified GM (1,1) model to predict the wax thickness of tube wall, and this method has certain popularization value.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Changkun Cheng, Menglong Zhao, Hui Shen, Benquan Li, Yanping Liu, and Pei Yang "Prediction and application of wax thickness on tube wall based on improved DGM (1,1) model", Proc. SPIE 13175, International Conference on Computer Network Security and Software Engineering (CNSSE 2024), 131751E (6 June 2024); https://doi.org/10.1117/12.3032055

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