Gear tooth root fatigue test monitoring with continuous acoustic emission: Advanced signal processing techniques for detection of incipient failure
Gear tooth root fatigue test monitoring with continuous acoustic emission: Advanced signal processing techniques for detection of incipient failure
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DOI：
10.1177/1475921717700567
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发表时间：
2018-05
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影响因子：
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通讯作者：
D. Crivelli;J. McCrory;S. Miccoli;R. Pullin;A. Clarke
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文献类型：
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作者：
D. Crivelli;J. McCrory;S. Miccoli;R. Pullin;A. Clarke
齿轮在齿根处的疲劳现象如果不及时检测，可能是灾难性故障的原因。传统的低频振动可以帮助检测充分发展的裂纹或完全失效的齿，用于早期检测疲劳裂纹的成核和初始传播的系统可以在状态监测中非常有用。声发射是一种潜在的合适技术，因为它对裂纹扩展产生的较高频率敏感，并且不受低频噪声的影响。在这篇文章中，一个静态齿轮副进行了测试，裂纹在齿根处开始。在整个测试过程中定期记录连续声发射。以多种方式处理数据，以支持裂纹萌生的早期检测。最初，采用传统的基于特征的声发射。这显示了定性结果，表明在约8000次循环时发生断裂。滚动互相关，然后比较两个给定的系统状态，显示出对裂纹扩展的最终阶段的大的变化的敏感性。带状快速傅立叶变换方法表明，110- 120 kHz频段对8000次循环时观察到的裂纹萌生敏感，对22,000次循环时的后期较大扩展事件敏感。两个先进的数据处理技术，然后使用，以进一步支持这些意见。首先，使用基于切比雪夫多项式分解的技术将每个波流数据减少到25个描述符的向量;这些描述符用于跟踪系统与基线状态的偏差，并以更高的灵敏度确认先前观察到的偏差。通过对波流熵含量的分析，进一步证实了利用连续声发射进行系统状态跟踪的可行性。
The phenomenon of fatigue in gears at the tooth root can be a cause of catastrophic failure if not detected in time. Where traditional low-frequency vibration may help in detecting a well-developed crack or a completely failed tooth, a system for early detection of the nucleation and initial propagation of a fatigue crack can be of great use in condition monitoring. Acoustic emission is a potentially suitable technique, as it is sensitive to the higher frequencies generated by crack propagation and is not affected by low-frequency noise. In this article, a static gear pair is tested where a crack was initiated at a tooth root. Continuous acoustic emission was periodically recorded throughout the test. Data were processed in multiple ways to support the early detection of crack initiation. Initially, traditional feature–based acoustic emission was employed. This showed qualitative results indicating fracture initiation around 8000 cycles. A rolling cross-correlation was then employed to compare two given system states, showing a sensitivity to large changes towards the final phases of crack propagation. A banded fast Fourier transform approach showed that the 110- to 120-kHz band was sensitive to the observed crack initiation at 8000 cycles, and to the later larger propagation events at 22,000 cycles. Two advanced data processing techniques were then used to further support these observations. First, a technique based on Chebyshev polynomial decomposition was used to reduce each wavestream data to a vector of 25 descriptors; these were used to track the system deviation from a baseline state and confirmed the previously observed deviations with a higher sensitivity. Further confirmation came from the analysis of wavestream entropy content, providing support from multiple data analysis techniques on the feasibility of system state tracking using continuous acoustic emission.