旋转机械系统故障信号优化诊断方法研究

Fault Diagnosis Method Based on Rotating Machinery Vibration Singal

在旋转机械轴心轨迹故障诊断研究中,由于转子振动信号为多分量信号,合成的轴心轨迹复杂,不容易获取清晰的故障特征。为解决上述问题,提出一种得到不同频率的提纯的轴心轨迹的新方法。在信号上进行固定频率的采样,求得样本数据的平均值,由信号的极值点特性得到采样频率的范围,在上述范围内求不同采样频率下样本数据平均值的最大值,从而最大值对应的采样频率即为分量信号的频率。再通过改变采样点的初始位置以及采样长度,分解出分量信号对应的波形形态和时域分布。将转子振动信号进行分解得到具备完整信息的各分量信号,合成得到不同频率的提纯的轴心轨迹。通过仿真验证了改进方法对故障检测的有效性。

In the fault diagnosis of rotating machinery vibration, shaft centerline orbit of multi-component vibra- tion signals is complex. In order to gain fault information, a new method of shaft centedine orbit purification is presented in the paper. Firstly, a sampling frequency range was gained according to the extreme points of the signal. Secondly, samples at a frequency on the signal were taken to gain sampling mean, and the maximum sampling mean was found out in the sampling frequency range. The maximum sampling mean was the amplitude of a single-component and its sampling frequency was the frequency of single-component. Lastly, by changing the first sampling point and sampling length, the time domain wave of the single-component signal in the original signal and its distribution can be obtained. By decomposing the rotating machinery vibration, some single-component signals can be obtained to gain shaft centerline orbit in different frequencies. Simulation calculation and actual practice have proved the effectiveness of the method.