Abstract
Planetary gearbox is widely used in large and complex mechanical equipment such as wind power generation, helicopters and petrochemical industry. Gear failures occur frequently in working conditions at low speeds, high service load and harsh operating environments. Incipient fault diagnosis can avoid the occurrence of major accidents and loss of personnel property. Aiming at the problems that the incipient fault of planetary gearbox is difficult to recognize and the number of intrinsic mode functions (IMFs) decomposed by variational mode decomposition (VMD) must be set in advance and can not be adaptively selected, a improved VMD algorithm based on energy difference as an evaluation parameter to automatically determine the decomposition level k is proposed. On this basis, a new method for early fault feature extraction of planetary gearbox based on the improved VMD and frequency-weighted energy operator is proposed. Firstly, the vibration signal is pre-decomposed by VMD, and the energy difference between the component signal and the original signal under different K-values is calculated respectively. The optimal decomposition level k is determined according to the energy difference curve. Then, according to kurtosis criterion, sensitive components are selected from the k modal components obtained by the decomposition to reconstruct. Finally, a new frequency-weighted energy operator is used to demodulate the reconstructed signal. The fault characteristic frequency information of the planetary gearbox can be accurately extracted from the energy spectrum. The method is applied to the simulation fault data and actual data of planetary gearbox, and the weak fault characteristics of planetary gearbox are extracted effectively, and the early fault characteristics are distinguished. The results show that the new method has certain application value and practical significance.
An incipient fault diagnosis method for rotating machinery based on bilateral spectrum and precession energy difference density spectrum
