基于极限学习机和b值法的罐底声发射检测腐蚀信号识别方法#br#

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摘要声发射储罐罐底腐蚀检测过程中，采集到的腐蚀信号里不可避免地混有干扰。针对该问题，提出了基于极限学习机(ELM)的石油储罐罐底腐蚀信号识别方法。为验证该方法的有效性，在秦皇岛输油站的消防水罐里，进行模拟罐底腐蚀检测实验，并应用ELM对采集到的声发射信号进行分类识别，用b值法对ELM的分类效果进行评估。实验结果表明：ELM识别正确率高于90%。ELM识别出的腐蚀信号的b值变化规律与实验室条件下腐蚀信号的b值变化规律一致，并能够反映磷酸腐蚀碳钢板的过程。

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	李一博
	祝慧宇
	张玉祥
	周纯瑶
	刘双赛
	王伟魁
	靳世久

关键词 ：罐底检测, 极限学习机, b值法, 声发射, 腐蚀信号识别

Abstract：The collected corrosion signals are mixed with interference inevitably in the acoustic emission (AE) detection process. To solve the problem，a novel and promising method, extreme learning machine (ELM) -based recognition for corrosion signals in AE testing of storage tank bottom is proposed. In order to test the validity of the method, the simulated experiments of petroleum storage tank bottom corrosion were carried out in the fire protection water tank of oil transportation station in Qinhuangdao. ELM was applied in the classification of the collected corrosion signals, and b-value method was used to evaluate the classification effect of ELM. The experimental results indicate that the classification accuracy of ELM is above 90%. The b-value distribution of corrosion signals identified by ELM is in accordance with that of corrosion signals in the laboratory. Furthermore, the statistical distribution of b-value reflects the process of carbon steel sheet corroded by phosphoric acid.

Key words： tank bottom testing extreme learning machine b-value acoustic emission corrosion signals recognition

收稿日期: 2014-03-10 出版日期: 2015-06-15

引用本文:

李一博，祝慧宇，张玉祥，周纯瑶，刘双赛，王伟魁，靳世久. 基于极限学习机和b值法的罐底声发射检测腐蚀信号识别方法#br#[J]. 振动与冲击, 2015, 34(11): 35-40.
LI Yi-bo, ZHU Hui-yu, ZHANG Yu-xiang, ZHOU Chun-yao, LIU Shuang-sai, WANG Wei-kui, Jin Shi-jiu. Corrosion signals recognition for acoustic emission testing of tank bottom based on ELM and b-value. JOURNAL OF VIBRATION AND SHOCK, 2015, 34(11): 35-40.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2015/V34/I11/35

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