Effective health monitoring and fault diagnosis technologies are crucial to timely grasping the operation status of the planetary gear train (PGT). In this study, the mechanism for global dynamic transmission error (GDTE)-based crack diagnosis of PGT is revealed from dynamic responses and validated through experiments, and the advantages of this new technique are compared with the commonly used vibration-based technology. Initially, a dynamic model of the PGT considering various crack degrees and transfer path effects is established, and the effectiveness of the model response is verified through experiment. Subsequently, GDTE and vibration signals under different crack conditions are statistically analyzed in time domain and frequency domain to evaluate the differences in the ability to reveal gear failure information. Ultimately, the reasons for the different distribution of fault characterization information in the two signals are explained from a dynamic perspective. The results show that GDTE-based fault diagnosis exhibits greater sensitivity to gear crack degree compared to vibration-based monitoring technology, with both time and frequency domain responses containing richer fault characteristic information, particularly in low-frequency regions. The fault characteristics concentrated in higher-frequency regions in the vibration signal are mainly caused by the modulation between gear crack shock and the gear single and double tooth alternating meshing shock. Conversely, fault frequencies in GDTE signals are mainly found in low-frequency regions, as fault shocks in GDTE signals directly correlate with the rotational frequency of the cracked gear. Modulation effects and attenuation on the transfer path are identified as the main reasons for the weaker representation of gear fault information in vibration signals compared to GDTE signals.

中文翻译：

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基于 GDTE 的行星齿轮裂纹诊断：机制、验证和与基于振动的技术相比的优势


有效的健康监测和故障诊断技术对于及时掌握行星齿轮系 （PGT） 的运行状态至关重要。本文从动态响应中揭示了基于全局动态传输误差 （GDTE） 的 PGT 裂纹诊断机制，并通过实验验证了该技术的优点，并将该技术的优势与常用的基于振动的技术进行了比较。首先，建立了考虑各种裂纹程度和传递路径效应的PGT动力学模型，并通过实验验证了模型响应的有效性。随后，在时域和频域对不同裂纹条件下的 GDTE 和振动信号进行统计分析，以评估揭示齿轮失效信息能力的差异。最终，从动力学角度解释了两个信号中故障特征信息分布不同的原因。结果表明，与基于振动的监测技术相比，基于 GDTE 的故障诊断对齿轮裂纹程度表现出更高的敏感性，时域和频域响应都包含更丰富的故障特征信息，尤其是在低频区域。振动信号中集中在高频区域的故障特性主要是由齿轮裂纹冲击与齿轮单双齿交替啮合冲击之间的调制引起的。相反，GDTE 信号中的故障频率主要出现在低频区域，因为 GDTE 信号中的故障冲击与裂纹齿轮的旋转频率直接相关。 与 GDTE 信号相比，传输路径上的调制效应和衰减是振动信号中齿轮故障信息表示较弱的主要原因。