基于自相关降噪的混叠转子振动信号分离

Separating mixed rotor vibration signals based on auto-correlation de-noising

航空发动机在运行过程中,传感器测得的振动信号是各振源的混叠信号,且含有很强的噪声。常规的信号处理方法难以分离混叠信号,对机器的健康监测和故障诊断造成了很大的困难。介绍了盲源分离基本原理和方法,指出盲源分离算法在强噪声环境下失效。针对强噪声环境下的混叠振动信号,提出首先通过时延自相关降噪方法对振动信号进行降噪,然后通过盲源分离算法对降噪后的信号分离。仿真结果验证了提出方法的有效性。最后,利用该方法对实测混叠转子振动信号成功实现了降噪和盲分离,为噪声环境下的混叠信号分离提供了一种新的方法。

When an areo-engine is running, the vibration signals measured with sensors are mixed with all vibration sources and contain very strong noises. It＇s diflicult to separate mixed signals with conventional methods of signal processing, so there are difficulties in machine health monitoring and fault diagnosis. The principle and method of blind source separation were introduced here, and it was pointed out that the blind source separation algorithm was invalid in strong noise environment. For the vibration signals in strong noise environment, they were de-noised with the time-delayed auto-correlation method firstly, and then the de-noised signals were separted with the blind source separation algorithm. The simulation results verified the effectiveness of the proposed method. Finally, some mixed rotor vibration signals were separated successfully using the proposed method. Thus, a new separation approach for mixed vibration signals in strong noise environment was provided.