基于材料参数的管道防腐层粘接状态识别研究

Research on identification of adhesion state of pipeline coating based on material parameters

附着防腐层管道的粘接状态识别是管道状态预诊断的热门研究方向。将弯曲的管道划分为多个紧密相连的微体元平板结构,建立非线性超声导波在微体元结构中的传播模型,分析导波在微体元中以及相邻微体元之间传播的频散特性及能量传递特性,采用SPWVD时频分析与小波包分解算法对回波信号进行分析,以提取能够表征管道不同粘接状态的特征量。以与附着防腐层管道性能接近的有机玻璃-铝双层粘接结构为实验对象,分别采集其粘接完好状态、基于密度变化的弱粘接状态和基于厚度变化的部分脱粘状态下的超声回波信号,分析其材料参数与粘接状态之间的对应关系,并采用特征量间具有独立性的朴素贝叶斯分类器对其粘接状态进行识别分类,得到识别率为92.31%。

The identification of adhesion state of pipeline with anti-corrosion coating is a hot research direction of pipeline state pre diagnosis.The curved pipe is divided into several closely connected micro body element plate structures,the propagation model of nonlinear ultrasonic guided wave in micro body element structure is established,the dispersion characteristics and energy transfer characteristics of guided wave in micro body element and between adjacent micro body elements are analyzed,and the echo signal is analyzed by spwvd time-frequency analysis and wavelet packet decomposition algorithm,In order to extract the characteristic quantity which can represent the different bonding state of pipeline.In this paper,the PMMA aluminum double-layer bonding structure with similar performance to the pipeline with anti-corrosion coating is taken as the experimental object.The ultrasonic echo signals of the intact bonding state,the weak bonding state based on the density change and the partial debonding state based on the thickness change are collected respectively,and the corresponding relationship between the material parameters and the bonding state is analyzed,The recognition rate is 92.31%.