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ANALOG SIGNAL PROCESSING TO IMPROVE ACOUSTIC EMISSIONS SENSING

机译:模拟信号处理可改善声发射传感

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摘要

Acoustic Emissions (AE) are stress waves produced by the sudden internal stress redistribution of material caused by changes in the internal structure of the material. Possible causes of these changes are crack initiation and growth, crack opening/closure, or pitting in monolithic materials (gear/ bearing material). Whereas vibration can measure the effect of damage, AE is a direct measure of damage. Unfortunately, AE methodologies suffer from the need of high sample rates (4 to 10 Msps) and relatively immature algorithms for condition indictors (CI). This paper hypothesizes that the AE signature is the result of some forcing function (e.g. periodic motion in the case of rotating machinery). As such, by demodulating the AE signature, one can reconstruct the information carried by the AE signature and provide improved diagnostics. As most on-line condition monitoring systems are embedded system, analog signal processing techniques are proposed which reduce the effective sample rate needed to operate on the AE signal to those similarly found in traditional vibration processing systems. This hypothesis is tested on a split torque gearbox and results are presented.
机译:声发射(AE)是由材料内部结构变化引起的材料突然内部应力重新分布而产生的应力波。这些变化的可能原因是裂纹的发生和扩展,裂纹的开/闭或整体材料(齿轮/轴承材料)的点蚀。振动可以衡量损害的影响,而AE是损害的直接衡量。不幸的是,AE方法需要高采样率(4到10 Msps)和条件指示符(CI)相对不成熟的算法。本文假设AE签名是某些强制功能(例如旋转机械情况下的周期性运动)的结果。这样,通过解调AE签名,可以重构AE签名携带的信息并提供改进的诊断。由于大多数在线状态监测系统是嵌入式系统,因此提出了模拟信号处理技术,该技术将对AE信号进行操作所需的有效采样率降低到了传统振动处理系统中类似的水平。该假设在分离式扭矩变速箱上进行了测试,并给出了结果。

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