'Automatic Segmentation of Time-Of-Flight-Diffraction Images Using Time-Frequency Techniques ¿ Application to Rail Track Defect Detection'
'Automatic Segmentation of Time-Of-Flight-Diffraction Images Using Time-Frequency Techniques ¿ Application to Rail Track Defect Detection'
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DOI：
10.1784/insi.46.6.338.55661
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发表时间：
2004-06
期刊：
影响因子：
1.1
通讯作者：
O. Zahran;W. Al-Nuaimy
中科院分区：
文献类型：
--
作者：
O. Zahran;W. Al-Nuaimy
超声飞行时间衍射法(TOFD)现在是一项成熟的技术，与其他超声波检测技术一起，可以准确地确定缺陷大小。目前在铁路行业对钢轨焊缝和鱼尾板区域进行检查的做法包括在轨道周围的不同位置使用多个不同的探头进行精细而艰苦的人工检查。另一方面，TOFD允许该过程自动化，提供检测、大小调整和分类。在TOFD检查中，只有一小部分收集的数据实际表示缺陷，而大多数数据被认为是冗余的。当前处理阶段中的第一个阶段严重依赖于熟练的操作员，包括指出包含缺陷区域的图像区域并抑制其他区域。因此，这一过程耗费了相当多的时间和精力，此外，在这个关键阶段，人为因素的存在总是会给解释带来不一致和错误。新的时频分析技术已经与人工神经网络相结合，以表征TOFD信号，并提取可区分的特征，用于检测、分类和确定轨道缺陷的大小。预计，结合必要的处理算法，TOFD可用于轨道的全面自动检测，特别是鱼尾板和焊接区(图1)，具有令人满意的精度和可靠性。
Ultrasonic time-of-flight diffraction (TOFD) is now a well- established technique alongside other ultrasonic testing techniques for accurate defect sizing. The current practice in the rail industry for the inspection of the rail welds and fishplate areas involves elaborate and painstaking manual inspection using a number of different probes at different positions around the track. TOFD, on the other hand, allows this procedure to be automated, providing detection, sizing and classification. In TOFD inspection, only a small fraction of the collected data actually represents defects, whereas the majority of the data is considered redundant. The first of the current processing stages which relies heavily on a skilled operator, involves pointing out those image areas containing defect areas and suppressing others. Consequently, this process consumes considerable amounts of time and effort, apart from the fact that the existence of the human factor at this critical stage invariably introduces inconsistency and error into the interpretation. Novel time- frequency analysis techniques have been combined with an artificial neural network to characterise TOFD signals and extract distinguishable features to be used for the detection, classification and sizing of rail-track defects. It is anticipated that, coupled with the necessary processing algorithms, TOFD can be used for a comprehensive automatic inspection of the rail-track, particularly fishplate and weld areas (Figure 1) with satisfactory levels of accuracy and reliability.