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Detection method based on Kalman filter for high speed rail defect AE signal on wheel-rail rolling rig

机译:基于Kalman滤波器在轮轨滚动钻机上高速轨缺陷AE信号的检测方法

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摘要

Nondestructive test (NDT) of rails has been carried out intermittently in traditional approaches, which highly restricts the detection efficiency under rapid development of high speed railway nowadays. It is necessary to put forward a dynamic rail defect detection method for rail health monitoring. Acoustic emission (AE) as a practical real-time detection technology takes advantage of dynamic AE signal emitted from plastic deformation of material. Detection capacities of AE on rail defects have been verified due to its sensitivity and dynamic merits. Whereas the application under normal train service circumstance has been impeded by synchronous background noises, which are directly linked to the wheel speed. In this paper, surveys on a wheel-rail rolling rig are performed to investigate defect AE signals with varying speed. A dynamic denoising method based on Kalman filter is proposed and its detection effectiveness and flexibility are demonstrated by theory and computational results. Moreover, after comparative analysis of modelling precision at different speeds, it is predicted that the method is also applicable for high speed condition beyond experiments.
机译:铁路的非破坏性测试(NDT)在传统方法中间歇地进行,这在现在高速铁路的快速发展中高度限制了检测效率。有必要提出轨道健康监测的动态轨道缺陷检测方法。声发射(AE)作为实际的实时检测技术利用塑性变形发射的动态AE信号。由于其灵敏度和动态优点,已经验证了AE对轨道缺陷的检测能力。虽然在正常列车服务环境下的应用已经被同步背景噪声阻碍,其直接连接到车轮速度。在本文中,执行轮轨轧制钻机上的调查,以研究具有不同速度的缺陷AE信号。提出了一种基于卡尔曼滤波器的动态去噪方法,并通过理论和计算结果证明了其检测效果和灵活性。此外,在不同速度下对建模精度进行比较分析之后,预测该方法也适用于超出实验的高速条件。

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