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Detection and Quantification of Fatigue Cracks in Rail Steel Using Acoustic Emission Technique

机译:利用声发射技术检测和量化钢轨中的疲劳裂纹

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Acoustic emission (AE) technique has a promising application for crack detection in rail tracks. However, it is still a challenging task to identify the size of fatigue cracks from AE signals. This paper proposes an index based on wavelet coefficients to accurately distinguish AE waves induced by crack propagation and crack closure, and a novel method of crack quantification based on crack closure induced AE waves. A higher count rate of crack closure induced AE waves indicates a larger crack size. The performance of the proposed method was validated by a three-point bending fatigue test on the rail steel specimen. In contrast with the traditional method, which is based on crack propagation induced AE waves and good at detecting crack growth rate, this method estimates the crack size without using the cumulative AE information, and is thus applicable to crack quantification of both new and existing structures. These two methods can be used to complement each other leading to a more efficient approach for crack detection, which has the potential for condition monitoring of rail tracks in the field.
机译:声发射(AE)技术在铁轨裂纹检测方面具有广阔的应用前景。但是,从AE信号中识别疲劳裂纹的大小仍然是一项艰巨的任务。提出了一种基于小波系数的指数,以准确地区分由裂纹扩展和闭合引起的声波,并提出了一种基于裂纹闭合引起的声波的量化方法。裂纹闭合诱发的AE波计数率越高,表明裂纹尺寸越大。通过对钢轨试样进行三点弯曲疲劳试验验证了该方法的性能。与基于裂纹扩展引起的AE波且擅长检测裂纹扩展速率的传统方法相反,该方法无需使用累积的AE信息即可估算裂纹尺寸,因此适用于新结构和现有结构的裂纹量化。这两种方法可以相互补充,从而导致更有效的裂纹检测方法,这可能在现场监测铁轨的状况。

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