As a crucial component in servo motors, rolling bearings are susceptible to malfunctioning, and the diagnosis of bearing faults is imperative to guarantee the dependable operation of equipment. In this innovative alternative, the article proposes a bearing fault diagnosis algorithm based only on the speed signal, which enables automatic alarm functions under variable-speed conditions. First, the algorithm converts the unfiltered speed signal into the equal-angle interval speed signal based on the cubic spline interpolation algorithm. Second, the optimized maximum correlation kurtosis deconvolution algorithm suitable for variable-speed conditions is proposed to extract bearing fault features. Finally, an automatic alarm strategy (AAS) is proposed based on the order spectrum characteristics of bearing failures. The experimental results demonstrate the effectiveness of the proposed method in mechanical fault diagnosis under variable-speed conditions, which highlights the potential applications in the field of safety monitoring for servo motors.

中文翻译：

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变速工况下基于速度信号的伺服电机轴承故障检测

滚动轴承作为伺服电机的关键部件，容易发生故障，轴承故障的诊断对于保证设备的可靠运行至关重要。在这一创新方案中，文章提出了一种仅基于速度信号的轴承故障诊断算法，可实现变速条件下的自动报警功能。首先，该算法基于三次样条插值算法将未经滤波的速度信号转换为等角区间速度信号。其次，提出了适用于变速工况的优化最大相关峰度反卷积算法来提取轴承故障特征。最后，提出了一种基于轴承故障阶次谱特征的自动报警策略（AAS）。实验结果证明了该方法在变速条件下机械故障诊断中的有效性，凸显了在伺服电机安全监测领域的潜在应用。