Application of ABC-VMD and Envelope Spectrum Analysis in Gear Fault Diagnosis - Wangping Zhou; Rong Wang; Shenrong Xu (Jixie chuandong)
Aiming at the nonlinear and unsteady characteristics of gearbox fault， a parameter-optimized Variational mode decomposition （VMD） is proposed to extract the characteristic frequency. Firstly， the Artificial bee colony algorithm （ABC） is used to adaptively select the number of layers and the penalty factor for VMD. Then， according to the mutual information method， the optimal finite Intrinsic mode function （IMF） is selected after VMD. Finally， the envelope spectrum analysis of the best IMF is performed to extract the characteristic signal of the gear fault. Comparing with Empirical mode decomposition （EMD） and VMD based on Particle swarm optimization （PSO）， simulation and experimental results show that the ABC-VMD method has strong adaptability， which can effectively avoid problems of mode mixing， signal loss and excessive decomposition. It can accurately perform early fault diagnosis on the gearbox and at the same time avoid the disadvantages of PSO-VMD falling into local optimum.