基于声发射的常压储罐罐底腐蚀特征识别研究

发布时间：2018-01-10 07:35

本文关键词：基于声发射的常压储罐罐底腐蚀特征识别研究　出处：《中国石油大学(华东)》2015年博士论文　论文类型：学位论文

【摘要】：常压金属储罐罐底腐蚀过程相当复杂,通常表现为底板大面积均匀腐蚀、局部点蚀、特殊部位的应力腐蚀甚至多种腐蚀类型之间的耦合,底板的腐蚀乃至穿孔泄漏严重威胁着储罐的运行安全。储罐底板腐蚀声发射在线检测虽然能够实现对储罐腐蚀程度“好”与“坏”的分级,但是对腐蚀声发射源的定性识别和判断仍然是声发射检测技术中的难点和瓶颈,提高腐蚀检测判断的准确性和确定最佳开罐检修周期仍存在诸多困难。因此,基于声发射技术,对储罐罐底腐蚀特征识别研究显得尤为重要。本文通过对储罐底板钢试样进行电化学和声发射联合监测试验,分别研究了底板钢均匀腐蚀、点蚀和应力腐蚀过程中声发射源机制,采用声发射特性参数分析、频谱分析、小波分析等分析方法对信号进行了处理,提取不同腐蚀源的声发射信号特征,并采用腐蚀类型判别图和提高型BP神经网络对腐蚀类型进行识别。主要研究工作和结果如下:1、研究了底板钢试样均匀腐蚀过程中声发射信号特征,结果表明均匀腐蚀过程中均匀腐蚀自身和腐蚀产物活动是主要声发射源,且都产生较低频声发射信号,信号频率主要集中在20~70kHz范围内,均匀腐蚀本身主要产生的是低幅值低持续时间的声发射信号,而腐蚀产物活动主要产生相对高幅值高持续时间的声发射信号。2、研究了底板钢试样点蚀过程中声发射信号特征,发现氢气泡的振荡和破碎、氧化膜破裂及腐蚀产物间摩擦和蚀坑的生长与扩展是主要的声发射源,产生较高频率的声发射信号。氢气泡破裂信号的低频截止频率约为130kHz,用Minnaert公式推导得到验证,而氧化膜破裂和点蚀坑生长信号的频率主要集中在80~130kHz。占绝对主导的点蚀坑生长信号持续时间基本低于80μs,而氧化膜破裂信号的持续时间一般大于100μs。3、研究了底板钢应力腐蚀过程中声发射信号特征,证实微裂纹开裂、宏观裂纹扩展和附属点蚀是主要的声发射源,产生高频的声发射信号。占明显优势微裂纹开裂信号基本贯穿于整个采集时间,持续时间相对发散且基本大于80μs,频率集中在110~190kHz,而裂纹扩展信号集中出现在实验后期,具有高振铃数、高能量和持续时间相对集中的特征,持续时间集中分布在200~420μs区间,且频率主要集中在260~400kHz高频段。4、通过提取各类腐蚀声发射源信号特征,建立了基于信号频率-持续时间鉴别法和频率-振铃数鉴别法的腐蚀类型判别图,初步直观地实现了对罐底腐蚀特征的识别。同时将声发射特性参数和小波包特征能谱系数相结合,构造从时域、频域和能量域描述罐底腐蚀特征的24维特征向量,并创建BP神经网络,通过对识别结果的混淆矩阵分析,证实了提高型BP网络对均匀腐蚀、点蚀和应力腐蚀特征模式识别的具有较高的准确性和良好的稳定性。
[Abstract]:Atmospheric pressure metal tank bottom corrosion process is quite complex, usually the bottom of large area uniform corrosion, pitting corrosion, stress corrosion and special parts of the various types of corrosion and corrosion of the bottom of the coupling, perforation and leakage of a serious threat to the safe operation of the storage tank. The tank bottom corrosion acoustic emission detection can realize the classification of storage tank the corrosion degree of "good" and "bad", but for the qualitative identification and judgment of Corrosion Acoustic emission source is still the bottleneck and difficulty of acoustic emission testing technology, to improve the accuracy of corrosion detection judgment and to determine the best tank maintenance cycle still exist many difficulties. Therefore, based on the acoustic emission technique, is particularly important for tank the bottom of the tank. This paper is to study the corrosion feature recognition by the tank bottom steel specimen and acoustic emission monitoring combined with electrochemical test, the uniform corrosion of steel plate Corrosion, pitting and stress corrosion mechanism of acoustic emission source in the process, the AE characteristic parameters analysis, spectrum analysis, wavelet analysis method to process the signal, extracted from different sources of Corrosion Acoustic emission characteristics, and the corrosion type discrimination diagram and improve the BP neural network to identify the main corrosion types. The research work and results are as follows: 1, research the characteristics of acoustic emission signals of floor steel specimens uniform corrosion process, the result shows that the uniform corrosion and uniform corrosion process and corrosion products of its activity is the main acoustic emission source, and produce low frequency acoustic emission signal, the signal frequency is mainly concentrated in the range of 20~70kHz, the main corrosion itself the low low amplitude duration of the acoustic emission signals and corrosion products mainly produce relatively high high amplitude duration of the acoustic emission signal of.2, on the bottom plate of steel specimens The characteristics of acoustic emission signals in the process of pitting, found and broken hydrogen bubble oscillation, the growth and expansion of film rupture and corrosion products between friction and corrosion pits are the main sources of acoustic emission, high frequency acoustic emission signal. Hydrogen bubble burst signal low cut-off frequency is about 130kHz, verified with Minnaert formula. The oxide film rupture and pitting growth signal frequency mainly accounted for pit growth signals dominated the duration of less than 80 mu s in 80~130kHz., and the oxide film rupture duration signal is generally greater than 100 mu s.3, study the characteristics of acoustic emission signals in the process of stress corrosion of the bottom plate steel, confirmed that micro cracks, crack expansion is the main and subsidiary Corrosion Acoustic emission source, to generate high-frequency acoustic emission signals. Dominant micro crack signals throughout the acquisition time and duration The relative divergence and more than 80 s, the frequency at 110~190kHz, and the crack propagation signal appeared in the later stage of the experiment, with a high number of features of the relative concentration of ringing, high energy and duration, duration of concentration distribution in the range of 200~420 s, and the frequency is mainly concentrated in the 260~400kHz high frequency.4, by extracting the source signal characteristics all kinds of Corrosion Acoustic emission, establishes discriminant diagrams of corrosion type signal frequency - duration identification method and frequency identification method based on the number of rings, the preliminary visually realized identification of tank bottom corrosion characteristics. At the same time the acoustic emission characteristic parameters and characteristics of wavelet packet energy spectrum coefficient combination structure in time domain and frequency domain. The energy domain description of 24 dimensional feature vectors of tank bottom corrosion characteristics, and create a BP neural network, the recognition results by confusion matrix analysis, confirmed the improved BP network of uniform corrosion, pitting corrosion and stress corrosion Characteristic pattern recognition has high accuracy and good stability.

【学位授予单位】：中国石油大学(华东)
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TE988

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