Liu Jinjun, Leng Yonggang, Lai Zhihui, Fan Shengbo
School of Mechanical Engineering, Tianjin University, Tianjin 300350, China.
School of Mechatronics Engineering, Nanchang University, Nanchang 330031, China.
Sensors (Basel). 2018 Apr 25;18(5):1325. doi: 10.3390/s18051325.
Mechanical fault diagnosis usually requires not only identification of the fault characteristic frequency, but also detection of its second and/or higher harmonics. However, it is difficult to detect a multi-frequency fault signal through the existing Stochastic Resonance (SR) methods, because the characteristic frequency of the fault signal as well as its second and higher harmonics frequencies tend to be large parameters. To solve the problem, this paper proposes a multi-frequency signal detection method based on Frequency Exchange and Re-scaling Stochastic Resonance (FERSR). In the method, frequency exchange is implemented using filtering technique and Single SideBand (SSB) modulation. This new method can overcome the limitation of "sampling ratio" which is the ratio of the sampling frequency to the frequency of target signal. It also ensures that the multi-frequency target signals can be processed to meet the small-parameter conditions. Simulation results demonstrate that the method shows good performance for detecting a multi-frequency signal with low sampling ratio. Two practical cases are employed to further validate the effectiveness and applicability of this method.
机械故障诊断通常不仅需要识别故障特征频率，还需要检测其二次和/或更高次谐波。然而，通过现有的随机共振（SR）方法很难检测多频故障信号，因为故障信号的特征频率及其二次和更高次谐波频率往往是大参数。为了解决这个问题，本文提出了一种基于频率交换和重新缩放随机共振（FERSR）的多频信号检测方法。在该方法中，使用滤波技术和单边带（SSB）调制来实现频率交换。这种新方法可以克服“采样率”（即采样频率与目标信号频率之比）的限制。它还确保可以对多频目标信号进行处理以满足小参数条件。仿真结果表明，该方法在检测低采样率的多频信号方面表现出良好的性能。通过两个实际案例进一步验证了该方法的有效性和适用性。
