Iterative generalized time-frequency reassignment for planetary gearbox fault diagnosis under nonstationary conditions

摘要

Planetary gearboxes are widely used in many sorts of machinery, for its large transmission ratio and high load bearing capacity in a compact structure. Their fault diagnosis relies on effective identification of fault characteristic frequencies. However, in addition to the vibration complexity caused by intricate mechanical kinematics, volatile external conditions result in time-varying running speed and/or load, and therefore nonstationary vibration signals. This usually leads to time-varying complex fault characteristics, and adds difficulty to planetary gearbox fault diagnosis. Time-frequency analysis is an effective approach to extracting the frequency components and their time variation of nonstationary signals. Nevertheless, the commonly used time-frequency analysis methods suffer from poor time-frequency resolution as well as outer and inner interferences, which hinder accurate identification of time-varying fault characteristic frequencies. Although time-frequency reassignment improves the time-frequency readability, it is essentially subject to the constraints of mono-component and symmetric time-frequency distribution about true instantaneous frequency. Hence, it is still susceptible to erroneous energy reallocation or even generates pseudo interferences, particularly for multi-component signals of highly nonlinear instantaneous frequency. In this paper, to overcome the limitations of time-frequency reassignment we propose an improvement with fine time-frequency resolution and free from interferences for highly nonstationary multi-component signals, by exploiting the merits of iterative generalized demodulation. The signal is firstly decomposed into mono-components of constant frequency by iterative generalized demodulation. Time-frequency reassignment is then applied to each generalized demodulated mono-component, obtaining a fine time-frequency distribution. Finally, the time-frequency distribution of each signal component is restored and superposed to get the time-frequency distribution of original signal. The proposed method is validated using both numerical simulated and lab experimental planetary gearbox vibration signals. The time-varying gear fault symptoms are successfully extracted, showing effectiveness of the proposed iterative generalized time-frequency reassignment method in planetary gearbox fault diagnosis under nonstationary conditions.