Underdetermined blind source separation method of rotating machinery faults based on local characteristic-scale decomposition
Zheng Cha · Journal of Yanshan University · 2014
The traditional blind source separation is restricted that source signals should be non-gaussian, stationary and mutually independent and that the number of observations is assumed to be not less than the number of sources. Aiming at this problem,underdetermined blind source separation method of rotating machinery faults based on local characteristic-scale decomposition(LCD) is put forward. In the method, all the mechanical fault signals are decomposed into several intrinsic scale components(ISC) by LCD, so the number of observations become more. Then all the ISCs are composed into new observations, which were blindly separated. This method not only decompose non-linear and non-stationary signals of mechanical fault but also can solve the underdetermined problem that the number of observations is less than the number of sources. While combining that method with the traditional blind source separation, the analysis of simulation and experimental results of the rotor of unbalance-rubbing-looseness coupled faults show that this method is effective.