高铁钢轨表面缺陷的光声无损检测方法研究

项目名称： 高铁钢轨表面缺陷的光声无损检测方法研究

项目编号： No.61201307

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 孙明健

作者单位： 哈尔滨工业大学

项目金额： 25万元

中文摘要： 该项目提出了高铁钢轨表面缺陷的光声无损检测方法，包括激光检测钢轨表面缺陷产生声表面波的建模、基于阵列探测器的光声成像实时无损检测系统的建立和钢轨表面缺陷光声信号的特征提取及分类三方面的内容。通过光声无损检测技术测量激光激发钢轨表面的光声信号，并对信号进行预处理，利用希尔伯特-黄变换对信号和重建图像进行基本幅频特征分析；然后，结合光声信号的频率、幅值以及不同的测量点组成多维张量，利用非负张量分解进行二次特征提取，得到缺陷特征系数和表征材料差异的特征信息；同时，结合激光检测钢轨表面缺陷产生声表面波的模型，获得在无缺陷以及典型缺陷情况下光声信号的特征系数，利用相关向量机对特征进行分类并建立缺陷识别规则；最后，通过建立的缺陷识别规则，实现对实测信号的缺陷实时检测。该项研究作为一种全新的轨道表面缺陷检测方法，能准确、实时地识别钢轨中的隐含伤损信息，保证高铁安全有效的运行。

中文关键词： 光声成像；无损检测；钢轨缺陷；特征提取和分类；多模态

英文摘要： The research proposed photoacoustic nondestructive detecting methods on high-speed rail surface defects, including three aspects: the modeling of surface acoustic wave producing by the laser detection of rail surface defects, the establishment of photoacoustic imaging of real-time non-destructive testing systems based on array detector, photoacoustic signal feature extration and classification of rail surface defects. By photoacoustic non-destructive testing technique, photoacoustic signal of the rail surface excitated by the pulse laser was measured and preprocessed, and then the signal and the reconstructed image were decomposed by using Hilbert-Huang transform to analyze basic amplitude-frequency characteristics. Multi-dimensional tensor was composed by the photoacoustic signal frequency, amplitude and different measurement points, then second feature was extracted by using non-negative tensor decomposition to get the injury characteristic coefficient and characterization information of material variances. At the same time, photoacoustic signal characteristic coefficients in the case of defectfree and typical defects were obtained by the bulit wave model, the defect recognition rules were established by using the the relevance vector machine classification features. Finally, real-time defect detection of the

英文关键词： Photoacoustic imaging；Nondestructive detection；Rail defects；Feature extraction and classification；Multimode