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Flexural cracking-induced acoustic emission peak frequency shift in railway prestressed concrete sleepers

机译:铁路预应力混凝土轨枕弯曲裂纹诱发声发射峰值频移

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摘要

A novel technique for acoustic emission-based condition monitoring of railway prestressed concrete sleepers under flexural loading is established. The evolution of peak frequency of emissions under increasing loads is studied using data from four emission sensors. It is found that the bulk of emitted peak frequencies are clustered in three bands - [150–300] kHz, [300–460] kHz and [500–800] kHz in all cases of full-scale sleepers tested. Only slight variations of band ranges are observed. A correspondence of acoustic emission counts to a particular peak frequency is established. Not all emissions are damage-induced – most of them have relatively small number of counts, suggesting that those are due to random noise. Thus, it is proposed to filter out the non-significant peak frequencies with the least number of counts by applying a universal threshold rule. The largest proportion of emission counts corresponds to mid-span of the sleepers. It is shown that other acoustic emission sources exhibit a nearly linear shift in maximum values of peak frequency with increasing distance from this largest concentration of acoustic emission events. This novel insight into condition-based acoustic emissions is critical to develop a suitable and efficient technique for monitoring safety-critical railway sleepers and bearers located in a discreet and remote area. It will truly enable preventative, predictive and condition-based track maintenance for railway industry, minimizing cost and environmental impacts.
机译:建立了基于声发射的弯曲预应力混凝土轨枕状态监测的新技术。使用来自四个排放传感器的数据研究了负荷增加时排放峰值频率的演变。发现在所有测试的全尺寸轨枕情况下,大部分发射的峰值频率都聚集在三个频带中-[150–300] kHz,[300–460] kHz和[500–800] kHz。仅观察到频带范围的微小变化。建立了声发射计数与特定峰值频率的对应关系。并非所有的排放都是由损坏引起的-大多数排放的计数相对较少,表明这些计数是由于随机噪声引起的。因此,提出了通过应用通用阈值规则以最少数量的计数滤除不重要的峰值频率。排放计数的最大比例对应于轨枕的中跨。结果表明,随着距此最大声发射事件的距离增加,其他声发射源的峰值频率最大值呈现出近乎线性的位移。这种对基于状态的声发射的新颖见解对于开发一种合适而有效的技术以监测位于谨慎和偏远地区的安全关键的铁路枕木和承载者至关重要。它将真正实现铁路行业预防性,预测性和基于条件的轨道维护,从而最大程度地降低成本和环境影响。

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