大型储罐声发射技术下的安全评价方法

doi:10.16265/j.cnki.issn1003-3033.2020.03.010

中国安全科学学报 ›› 2020, Vol. 30 ›› Issue (3): 60-66.doi: 10.16265/j.cnki.issn1003-3033.2020.03.010

大型储罐声发射技术下的安全评价方法

宋高峰¹ 高级工程师, 张延兵¹ 高级工程师, 孙培培², 沈硕勋², 王志荣^**2 教授

1.江苏省特种设备安全监督检验研究院南通分院,江苏南通 226011;
2.南京工业大学安全科学与工程学院,江苏南京 211816

收稿日期:2019-12-14 修回日期:2020-02-09 出版日期:2020-03-28 发布日期:2021-01-26
通讯作者: **王志荣(1977—),男,江苏南京人,博士,教授,主要从事火灾爆炸、腐蚀安全防护、锂电子电池安全等方面的研究。wangzhirong@njtech.edu.cn。
作者简介:宋高峰(1978—),男,江苏南京人,硕士,高级工程师,主要从事特种设备(承压类)方面的检测分析工作。E-mail:sgaofeng@163.com。
基金资助:
国家安全生产重大事故防治关键技术科技项目(jiangsu-0013-2017AQ)。

Safety evaluation method based on acoustic emission technology for large-scale storage tanks

SONG Gaofeng¹, ZHANG Yanbing¹, SUN Peipei², SHEN Shuoxun², WANG Zhirong²

1. Branch of Nantong, Jiangsu Institute of Safety Supervision and Inspection of Special Equipment, Nantong Jiangsu 226011, China;
2. College of Safety Science and Engineering, Nanjing Tech University, Nanjing Jiangsu 211816, China

Received:2019-12-14 Revised:2020-02-09 Online:2020-03-28 Published:2021-01-26

摘要/Abstract

摘要： 为探究腐蚀声发射信号相关参数的变化特征,以常见的立式金属储罐为对象开展试验,研究储罐腐蚀声发射源特性,建立基于反向传播(BP)神经网络的安全评价模型,并开展应用实例研究。结果表明:声发射活性和强度会随着腐蚀反应的剧烈程度发生变化,且在腐蚀活性不同时期腐蚀信号的波形表现出连续型、突发型和混合型3种特征,频率主要集中在20～60 kHz;BP神经网络模型输出结果与实际评价结果一致,证明该方法具有一定的有效性。

关键词: 大型储罐, 腐蚀信号, 声发射活性及强度, 声发射检测, 反向传播(BP)神经网络模型

Abstract: In order to explore variation characteristics of related parameters of corrosion acoustic emission signals, experiment was carried out with a common vertical metal storage tank as research object to study characteristics of its acoustic emission source for corrosion. Then, a safety evaluation model based on BP neural network was established, and case study of its application was carried out. The results show that acoustic emission activity and intensity will change along with severity of corrosion reaction, and wave forms of corrosion signals in different periods of corrosion activity will exhibit three types, continuous, abrupt and hybrid types with its frequencies mainly concentrating between 20-60 kHz. The output of BP neural network model is consistent with actual evaluation results, which proves its feasibility and effectiveness.

Key words: large storage tank, corrosion signal, acoustic emission activity and intensity, acoustic emission monitoring, back propagation (BP) neural network model

中图分类号:

X944.4

宋高峰, 张延兵, 孙培培, 沈硕勋, 王志荣. 大型储罐声发射技术下的安全评价方法[J]. 中国安全科学学报, 2020, 30(3): 60-66.

SONG Gaofeng, ZHANG Yanbing, SUN Peipei, SHEN Shuoxun, WANG Zhirong. Safety evaluation method based on acoustic emission technology for large-scale storage tanks[J]. China Safety Science Journal, 2020, 30(3): 60-66.

参考文献

[1] YUYAMA S, YAMADA M, SEKINE K, et al. Verification of acoustic emission testing of floor conditions in aboveground tanks by comparison of acoustic emission data and floor scan testing[J]. Materials Evaluation, 2007, 65(9): 929-934.
[2] 姚舜刚. 立式储罐声发射在线检测技术的试验研究和应用[D]. 杭州: 浙江工业大学, 2006.
YAO Shungang. Experimental research and application of on-line detection technology for vertical storage tank acoustic emission[D]. Hangzhou: Zhejiang University of Technology, 2006.
[3] MAZILLE H, ROTHEA R, TRONEL C. An acoustic emission technique for monitoring pitting corrosion of austenitic stainless steels[J]. Corrosion Science, 1995, 37(9): 1 365-1 375.
[4] KASAI N, UTATSU K, PARK S, et al. Correlation between corrosion rate and AE signal in an acidic environment for mild steel[J]. Corrosion Science, 2009, 51(8): 1 679-1 684.
[5] MARTIN G. Acoustic emission for tank bottom monitoring[J]. Key Engineering Materials, 2013, 558: 445-455.
[6] JIRARUNGSATIAN C, PRATEEPASEN A. Pitting and uniform corrosion source recognition using acoustic emission parameters[J]. Corrosion Science, 2010, 52(1): 187-197.
[7] 李伟. 低碳钢点蚀声学检测与信号处理技术研究[D]. 大庆: 东北石油大学, 2006.
LI Wei. Research on acoustic detection and signal processing technology of low carbon steel pitting[D]. Daqing: Northeast Petroleum University, 2012.
[8] 陈钢, 沈功田, 李邦宪. 金属压力容器声发射源特性的研究[J]. 中国安全科学学报, 2005, 15(1): 98-103.
CHEN Gang, SHEN Gongtian, LI Bangxian. Study on characteristics of acoustic emission sources of metal pressure vessels[J]. China Safety Science Journal, 2005, 15(1): 98-103.
[9] 吴占稳. 起重机的声发射源特性及识别方法研究[D]. 武汉: 武汉理工大学, 2008.
WU Zhanwen. Research on acoustic emission source characteristics and identification method of crane[D]. Wuhan: Wuhan University of Technology, 2008.
[10] 耿荣生, 傅刚强. 金属点蚀过程声发射源机制研究[J]. 声学学报, 2002,27(4): 369-372.
GENG Rongsheng, FU Gangqiang. Study on the source mechanism of metal pitting acoustic emission source[J]. Chinese Journal of Acoustics, 2002,27(4): 369-372.
[11] JB/T 10764—2007,无损检测常压金属储罐声发射检测及评价方法[S].
JB/T 10764-2007,Non-destructive testing-acoustic emission testing and evaluation of atmospheric pressure metal storage tanks[S].

大型储罐声发射技术下的安全评价方法

Safety evaluation method based on acoustic emission technology for large-scale storage tanks

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 3

编辑推荐

Metrics

本文评价

[1]	张颖, 高俊伟, 朱子东, 刘识, 张潇. 大型储罐底板浸入式声学检测方法及样机设计[J]. 中国安全科学学报, 2020, 30(8): 31-36.
[2]	张颖, 张潇, 朱子东, 党娜, 陈小龙. 大型储罐底板腐蚀浸入式声学定位方法[J]. 中国安全科学学报, 2020, 30(3): 35-40.
[3]	葛晓霞，董希琳，郭其云，唐凯. 大型石油储罐消防设计研究[J]. 中国安全科学学报, 2008, 18(9): 79-.