氧化锆内涂层腐蚀裂纹的超声检测  

Ultrasonic detection of corrosion crack of internal ZrO_(2) coating

作　　者：赵通 张峰 冀国俊[1] ZHAO Tong;ZHANG Feng;JI Guojun(School of Chemical Engineering,Inner Mongolia University of Technology,Hohhot 010051,China;Institute for the Inspection and Research of Inner Mongolia Special Equipment,Hohhot 010013,China)

机构地区：[1]内蒙古工业大学化工学院,呼和浩特010051 [2]内蒙古自治区特种设备检验研究院,呼和浩特010013

出　　处：《无损检测》2024年第12期77-85,共9页Nondestructive Testing

基　　金：国家自然科学基金(12062020);内蒙古自治区“草原英才”工程项目(CYYC9024)。

摘　　要：氧化锆材料因其优异的性能被广泛应用于各个领域,然而其作为涂层材料与金属基体结合使用时,易产生腐蚀裂纹。首先通过有限元软件构建氧化锆涂层腐蚀裂纹的超声检测模型,分析超声检测氧化锆涂层腐蚀裂纹的可行性,其中氧化锆涂层作为内涂层设置在金属基体内侧。然后根据仿真结果采集不同深度腐蚀裂纹的超声信号,分析其裂纹深度与缺陷信号之间的关系,并采用SPWVD时频分析法对裂纹信号进行分析,提取信号中能够表征腐蚀裂纹的特征量。最后采样200组裂纹信号,构造信号特征量与裂纹深度数据集,并使用卷积神经网络算法对其裂纹深度进行识别分类。试验结果表明,通过卷积神经网络算法对采集到的裂纹信号进行识别和训练,识别准确率为96.7%。试验为氧化锆内涂层腐蚀裂纹的检测与识别提供了一些参考。ZrO_(2)materials are widely used in various fields due to their excellent properties.However,when used as coating materials in combination with metal substrates,corrosion cracks are prone to occur.Constructing a model for ultrasonic guided wave detection of corrosion cracks in ZrO_(2)coatings using finite element software,and analyzing the feasibility of ultrasonic guided wave detection of corrosion cracks in ZrO_(2)coatings,where the ZrO_(2)coating is set as an inner coating on the inner side of the metal substrate.Collect ultrasonic signals of corrosion cracks at different depths based on simulation results,analyze the corresponding relationship between the depth of corrosion cracks and defect signals,and use SPWVD time-frequency analysis method to analyze the corrosion crack signals,extracting characteristic quantities that can characterize corrosion cracks from the signals.Sample 200 sets of crack signals,construct a dataset of signal feature quantities and corrosion crack depth,and use convolutional neural network algorithm to identify and classify the corrosion crack depth.The experimental results show that the recognition and training of the collected crack ultrasonic guided wave signals using convolutional neural network algorithm achieved a recognition rate of 96.7%,providing some reference for the detection and recognition of corrosion cracks in ZrO_(2)inner coatings.

关 键 词：氧化锆涂层 腐蚀裂纹 超声 时频分析 卷积神经网络 

分 类 号：TB553[理学—物理] TG115.28[理学—声学]