COMPARATIVE STUDY OF QUANTITATIVE PREDICTIVE METHOD OF CORROSION DAMAGE FOR ENGINEERING COMPONENTS

J Chin Soc Corr Pro

2003, Vol. 23

Issue (1): 52-55 DOI:

Research Report

Current Issue | Archive | Adv Search

COMPARATIVE STUDY OF QUANTITATIVE PREDICTIVE METHOD OF CORROSION DAMAGE FOR ENGINEERING COMPONENTS

Yueliang Chen;Xiaohua Yang;Guozhi Lv

海军航空工程学院青岛分院飞机教研室

Download:

PDF(134KB)
Export: BibTeX | EndNote (RIS)

Abstract A prediction model of corrosion damage for aircraft structure and 1Cr17 stainless steel under a varied corrosion environment based on artificial neural net was developed and the nonlinear relationship between a verage corrosion rate,average corrosion loss weight,corrosion depth,corrosion te mperature,immersion duration,concentration was established based on BP learning algorithm.The corrosion characteristic quantity (CCQ) such as surface area,depth and so on can be predicted by means of the trained neural net from the data.The results show that,the model has relative good prediction accuracy and flexibili ty than the gray theory GM(1,1) model and the Logistic model.The prediction mode l based on BP learning algorithm of corrosion damage for aircraft structure is f easible and effective.Thus,by virtue of the prediction model,the future corrosio n status and service duration of engineering structure can be evaluated.

Key words: neural net corrosion aircraft mathematical model service duration

Received: 06 August 2001

Corresponding Authors: Yueliang Chen

	Service

	E-mail this article
	Add to citation manager
	E-mail Alert
	RSS
	（）
	Articles by authors
	Yueliang Chen
	Xiaohua Yang
	Guozhi Lv

Cite this article:

Yueliang Chen; Xiaohua Yang; Guozhi Lv. COMPARATIVE STUDY OF QUANTITATIVE PREDICTIVE METHOD OF CORROSION DAMAGE FOR ENGINEERING COMPONENTS. J Chin Soc Corr Pro, 2003, 23(1): 52-55 .

URL:

https://www.jcscp.org/EN/ OR https://www.jcscp.org/EN/Y2003/V23/I1/52

[1]YuanCengren.ArtificialNeuralNetandItApplied[M ].Beijing:TsinghuaUniversityPress,1999,10(袁曾任编著.人工神经网络及其应用[M ].北京:清华大学出版社,1999,10)
[2]LouShuntian,ShiYang.AnalyzeandDesignofSystemBasedonMATLAB—ArtificialNeuralNet[M ].Xi’an:Xi’anElectronicSci enceandTechnologyUniversityPress,1999,4(楼顺天,施阳编著.基于MATLAB的系统分析与设计———神经网络[M ].西安:西安电子科技大学出版社,1999,4)
[3]ZhangJiuyuan,HongMinggeng,LuJianshu,etal.Comparativestudyofstatisticlawofpitting[J].J.ChineseSocietyforCorrosionandProtection,1994,8(2):161-166(张九渊,洪明庚,卢建树.孔蚀统计规律的对比研究[J].中国腐蚀与防护学报,1994,8(2):161-166)
[4]ChenJiwei,ZhangQi.Studyofmathematicalmodelsinmaterialcor rosionprediction[J].ActaAeronauticaetAstronauticaSinica,2000,21(2):183-186(程基伟,张琦.材料腐蚀预测数学模型的研究[J].航空学报,2000,21(2):183-186)
[5]LiuYanli,ZhongQuanpeng,ZhangZheng.Predictivemodelbasedonartificialneuralnetforfatigueperformancesofprior-corrodedaluminumalloys[J].ActaAeronauticaetAstronauticaSinica,2001,22(2):135-139(刘延理,钟群鹏,张峥.基于人工神经网络的预腐蚀铝合金疲劳性能预测[J].航空学报,2001,22(2):135-139)
[6]LeiferJ,MickalonisJ .I .Predictionofaluminumpittinginnaturalviaartificialneuralnetworkanalysis[J].Corrosion,2000,56(6):563-571
[7]LawlessJF .Statisticalmodelsandmethodsforlifetimedata[J].IS BN 7-5037-2446-3,1982

[1]	HUANG Peng, GAO Rongjie, LIU Wenbin, YIN Xubao. Fabrication of Superamphiphobic Surface for Nickel-plate on Pipeline Steel by Salt Solution Etching and Its Anti-corrosion Properties[J]. 中国腐蚀与防护学报, 2021, 41(1): 96-100.
[2]	DONG Xucheng, GUAN Fang, XU Liting, DUAN Jizhou, HOU Baorong. Progress on the Corrosion Mechanism of Sulfate-reducing Bacteria in Marine Environment on Metal Materials[J]. 中国腐蚀与防护学报, 2021, 41(1): 1-12.
[3]	TANG Rongmao, ZHU Yichen, LIU Guangming, LIU Yongqiang, LIU Xin, PEI Feng. Gray Correlative Degree Analysis of Q235 Steel/conductive Concrete Corrosion in Three Typical Soil Environments[J]. 中国腐蚀与防护学报, 2021, 41(1): 110-116.
[4]	HAN Yuetong, ZHANG Pengchao, SHI Jiefu, LI Ting, SUN Juncai. Surface Modification of TA1 Bipolar Plate for Proton Exchange Membrane Fuel Cell[J]. 中国腐蚀与防护学报, 2021, 41(1): 125-130.
[5]	ZHANG Yuxuan, CHEN Cuiying, LIU Hongwei, LI Weihua. Research Progress on Mildew Induced Corrosion of Al-alloy[J]. 中国腐蚀与防护学报, 2021, 41(1): 13-21.
[6]	RAN Dou, MENG Huimin, LIU Xing, LI Quande, GONG Xiufang, NI Rong, JIANG Ying, GONG Xianlong, DAI Jun, LONG Bin. Effect of pH on Corrosion Behavior of 14Cr12Ni3WMoV Stainless Steel in Chlorine-containing Solutions[J]. 中国腐蚀与防护学报, 2021, 41(1): 51-59.
[7]	BAI Yunlong, SHEN Guoliang, QIN Qingyu, WEI Boxin, YU Changkun, XU Jin, SUN Cheng. Effect of Thiourea Imidazoline Quaternary Ammonium Salt Corrosion Inhibitor on Corrosion of X80 Pipeline Steel[J]. 中国腐蚀与防护学报, 2021, 41(1): 60-70.
[8]	ZUO Yong, CAO Mingpeng, SHEN Miao, YANG Xinmei. Effect of Mg on Corrosion of 316H Stainless Steel in Molten Salts MgCl₂-NaCl-KCl[J]. 中国腐蚀与防护学报, 2021, 41(1): 80-86.
[9]	WANG Yating, WANG Kexu, GAO Pengxiang, LIU Ran, ZHAO Dishun, ZHAI Jianhua, QU Guanwei. Inhibition for Zn Corrosion by Starch Grafted Copolymer[J]. 中国腐蚀与防护学报, 2021, 41(1): 131-138.
[10]	WANG Xintong, CHEN Xu, HAN Zhenze, LI Chengyuan, WANG Qishan. Stress Corrosion Cracking Behavior of 2205 Duplex Stainless Steel in 3.5%NaCl Solution with Sulfate Reducing Bacteria[J]. 中国腐蚀与防护学报, 2021, 41(1): 43-50.
[11]	SHI Kunyu, WU Weijin, ZHANG Yi, WAN Yi, YU Chuanhao. Electrochemical Properties of Nb Coating on TC4 Substrate in Simulated Body Solution[J]. 中国腐蚀与防护学报, 2021, 41(1): 71-79.
[12]	ZHENG Li, WANG Meiting, YU Baoyi. Research Progress of Cold Spraying Coating Technology for Mg-alloy[J]. 中国腐蚀与防护学报, 2021, 41(1): 22-28.
[13]	WEI Zheng, MA Baoji, LI Long, LIU Xiaofeng, LI Hui. Effect of Ultrasonic Rolling Pretreatment on Corrosion Resistance of Micro-arc Oxidation Coating of Mg-alloy[J]. 中国腐蚀与防护学报, 2021, 41(1): 117-124.
[14]	YU Hongfei, SHAO Bo, ZHANG Yue, YANG Yange. Preparation and Properties of Zr-based Conversion Coating on 2A12 Al-alloy[J]. 中国腐蚀与防护学报, 2021, 41(1): 101-109.
[15]	ZHANG Hao, DU Nan, ZHOU Wenjie, WANG Shuaixing, ZHAO Qing. Effect of Fe³⁺ on Pitting Corrosion of Stainless Steel in Simulated Seawater[J]. 中国腐蚀与防护学报, 2020, 40(6): 517-522.

No Suggested Reading articles found!

Viewed

Full text

Abstract

Cited

Shared

Discussed