Blind source separation of rolling element bearing’ single channel compound fault based on shift invariant sparse coding

Abstract

The mechanical vibration source signal collected by sensor often includes a variety of internal vibration source of contributions such as gears, bearings, shaft and so on. It is often hoped to achieve effective separation of the source signal in order to obtain better fault diagnosis result. Blind source separation of the failure signal of rolling element bearing is a challenging task due to the above reasons, especially in the case of single channel compound fault. A method of blind source separation of rolling element bearing’s single channel compound fault based on Shift-Invariant Sparse Coding (SISC) is proposed in the paper. The waveform characteristic of different fault signal has some difference in the structure even that the same impulse characteristics of signals are produced by different parts, and the difference can be captured by the SISC method with the following reasons: Firstly, a set of basis functions is trained and obtained by SISC feature self-study method (The number of the basis functions is big necessarily). Then the potential components are constructed using the corresponding obtained basis functions. At last, the clustering operation is carried out using the structural similarity of the potential components, and the clustering signals represent the different vibration source signals. Apply the traditional vibration signal handling method such as envelope demodulation to the obtained clustering signals respectively and better fault diagnosis results are obtained at last.