Blind Source Separation Method for Bearing Vibration Signals

A new method for blind source separation of nonstationary signals

Many algorithms for blind source separation have been introduced in the past few years, most of which assume statistically stationary sources. In many applications, such as separation of speech or fading communications signals, the sources are nonstationary. We present a new adaptive algorithm for blind source separation of nonstationary signals which relies only on the nonstationary nature of ...

Blind Source Separation Based Vibration Mode Identification

In this paper, a novel method for linear normal mode identification based on Blind Source Separation (BSS) is introduced. Modal coordinates are considered as a specific case of sources that have certain time structure. This structure can be identified by many BSS algorithms. However, algorithms based on second order statistics are particularly suited for the linear normal mode identification. T...

Underdetermined Blind Source Separation with Variational Mode Decomposition for Compound Roller Bearing Fault Signals

In the condition monitoring of roller bearings, the measured signals are often compounded due to the unknown multi-vibration sources and complex transfer paths. Moreover, the sensors are limited in particular locations and numbers. Thus, this is a problem of underdetermined blind source separation for the vibration sources estimation, which makes it difficult to extract fault features exactly b...

Blind Source Separation: Application to biomedical signals

Blind Source Separation (BSS) is a prominent problem in signal processing. In the past few decades, it was applied to many fields, in which separation of compound signals, simultaneously observed by different sensors, is of interest. The problem can be considered as built-up of three physical elements: sources (also called transmitters), sensors (also called receivers) and communication channel...

Blind Source Separation: Recovering Signals from Mixtures