Use BP Neural Network Set up the Corrosion Prediction Model of Low Temperature Parts of Atmospheric Pressure Device

Abstract:

Article Preview

In research of the low temperature parts of atmospheric pressure device, by using BP neural network, the connection of PH value, Cl-, H2S and Fe+2 was setup which can predict Fe+2 content accurately, and obtain the requirement accuracy, hence more accurate corrosion can be predicted and providing more suggests for corrosion protection.

Info:

Periodical:

Edited by:

Wen Jin

Pages:

1138-1142

DOI:

10.4028/www.scientific.net/AMM.152-154.1138

Citation:

Y. G. Fan et al., "Use BP Neural Network Set up the Corrosion Prediction Model of Low Temperature Parts of Atmospheric Pressure Device", Applied Mechanics and Materials, Vols. 152-154, pp. 1138-1142, 2012

Online since:

January 2012

Export:

Price:

$38.00

[1] China Petrochemical Equipment Management Association Equipment Corrosion Major. Petrochemical Equipment Corrosion and Protection Manual Equipment Corrosion Major (China Petrochemical Press, China 1994)(In Chinese).

DOI: 10.1002/(sici)1521-4176(200003)51:3<152::aid-maco152>3.0.co;2-f

[2] E.H. Cheng. The Research of Atmospheric Pressure and Pressure-Relief Device Low Temperature Parts Corrosion Evaluation Expert System (MS., Xi'an Shiyou University, China 2008), p.16. (In Chinese).

[3] Y. Yang. The research of atmospheric tower corrosion information fusion technology (MS., Xi'an Shiyou University, China 2011), p.22. (In Chinese).

In order to see related information, you need to Login.