An adaptive synchroextracting transform for the analysis of noise contaminated multi-component nonstationary signals

The Synchro-Extracting Transform technique (SET) can capture the changing dynamic in a non-stationary signal which be applied for fault diagnosis of rotating machinery operating under varying speed or/and load conditions. However, time frequency representation (TFR) produced by SET affected noise contained signal, largely reduce accuracy diagnosis. This paper addresses this drawback and presents new extraction operator to improve energy concentration TFR contaminated multi-component using an adaptive ridge curve identification process together with SET. is deployed extract components via iterative approach. effectiveness algorithm verified one set simulated noise-added signals two sets experimental bearing gearbox defect signals. result shows that proposed accurately identify from machine