Rolling Bearing Fault Detection of Civil Aircraft Engine Based on Adaptive Estimation of Instantaneous Angular Speed

Diagnosis of a civil aircraft engine, which is operating under speed variation conditions, is a representative problem encountered in aeronautic industry. It is still very challenging to estimate the instantaneous angular speed (IAS) through the aircraft engine vibration signal when no encoder or tachometer is available due to cost or technological reasons. However, for the currently available tacholess order tracking algorithms, many vital parameters must be initialized manually in advance, which lead to user-friendliness, even false diagnosis. To address this issue, a novel method is proposed and the merits of nonlinear mode decomposition are inherited, so the IAS can be estimated adaptively without prior knowledge. The vibration signal collected from a civil aircraft engine is used for validation; the experimental results exhibit that the proposed method is more accurate and flexible when compared with the conventional methods.