强脉冲干扰非线性混叠转子故障信号分离

由于旋转机械在运行过程中，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，对设备的状态监测和故障诊断造成了很大的困难。针对这一问题，介绍了盲源分离基本原理和方法，指出源分离算法在脉冲噪声环境下失效。针对强脉冲噪声环境下的混叠振动信号，首先，通过中值滤波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；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故障信号分离。仿真结果验证了提出方法的有效性。

Separation of Nonlinear Mixed Rotor Fault Signals with Violent Pulse Interferences

When rotary machinery runs, vibration signals measured with sensors are mixed with all vibration sources and thus contain very strong noises. Mixed signals are difficult to separate using conventional methods of signal processing, such as in machine health monitoring and fault diagnosis. The principle and methods of blind source separation are introduced, and the blind source separation algorithm is indicated to be invalid in strong pulse noise environments. In these environments, vibration signals are first de-noised with the median filter method, and the de-noised signal is separated using the blind source separation algorithm. The results of the simulation verify the effectiveness of the proposed method. Finally, some mixed rotor vibration signals are dealed with using the proposed method. A new separation approach is thus provided for use on vibration signals in strong pulse noise environments.