城市燃气PE管道热氧老化程度的超声波智能无损检测  

Ultrasonic Intelligent Nondestructive Test of Thermal-oxidative Aging Degree of City Gas PE Pipeline

作　　者：张琦 汪树民 程炜 程林 方雨婷 戴梦娟 ZHANG Qi;WANG Shumin;CHENG Wei;CHENG Lin;FANG Yuting;DAI Mengjuan(Testing and Certification-Institute of Special Equipment Inspection and Testing,Jiangxi Provincial Academy of Inspection,Nanchang 330200,China;Jingdezhen Branch,Testing and Certification-Institute of Special Equipment Inspection and Testing,Jiangxi Provincial Academy of Inspection,Jingdezhen 333000,China;Guangxi Xinchen special equipment testing Co.,LTD,Nanning 530001,China)

机构地区：[1]江西省检验检测认证总院特种设备检验检测研究院,江西南昌330200 [2]江西省检验检测认证总院特种设备检验检测研究院景德镇分院,江西景德镇333000 [3]广西鑫晨特种设备检测有限公司,广西南宁530001

出　　处：《塑料科技》2025年第2期163-167,共5页Plastics Science and Technology

基　　金：国家市场监督管理总局科技计划项目(2022Mk065);江西省检验检测认证总院科研项目(ZYK202203)。

摘　　要：为预防因热氧老化异常引发的燃气聚乙烯(PE)管道泄漏事故,提出管道热氧老化程度的超声波智能检测方法。提取PE管的线性和非线性超声检测特征参数,并分析其与管道热氧老化程度的关系;构建并优化BP神经网络,将超声检测特征向量和老化时间作为网络输入和输出;扩展检测特征参数并用于网络训练,训练能够评估PE管老化程度的神经网络模型。研究结果表明:由声速、声衰减、非线性系数可构成用于智能评估老化程度的超声检测特征向量,经优化并训练后的神经网络可评估PE管老化时间,老化时间评估值的平均相对误差低于6.9%。In order to prevent gas polyethylene(PE)pipeline leakage accident caused by abnormal thermal oxidative aging,an ultrasonic intelligent detection method for thermal oxidative aging degree of pipeline was proposed.The linear and nonlinear ultrasonic testing characteristic parameters of PE pipe wereextracted,and the relationship between the characteristic parameters and the aging degree of PE pipe was analyzed.The BP neural network was constructed and optimized,and the ultrasonic testing characteristic vector and aging time were respectively used as the input and output of the network.The testing characteristic parameters were expanded and used for network training,and the neural network model that could evaluate the aging degree of PE pipe was obtained.The results show that the acoustic velocity,acoustic attenuation and nonlinear coefficient can be used to form the characteristic vector of ultrasonic testing for intelligent evaluation of aging degree.The optimized and trained neural network can be used to evaluate the aging time of PE pipe,and the average relative error of the evaluation value of aging time is less than 6.9%.

关 键 词：燃气PE管道 超声特征参数 热氧老化 BP神经网络 

分 类 号：TQ32[化学工程—合成树脂塑料工业]