A novel unbalanced signal extraction method based on quadratic SSA-VMD for micro-motor rotor

Vibration signal processing is the key to the dynamic balance of micro-motor rotors. Aiming at the extraction accuracy of the amplitude and phase of the unbalanced vibration signal of micro-motor rotors, a feature extraction method based on variational mode decomposition is developed. Taking the convergence of sample entropy as the optimization objective, the modal decomposition number K and penalty factor a are optimized by sparrow search algorithm, and the threshold of reference permutation entropy of unbalanced signal is used as a filter to select the required modal components. After VMD decomposition and reconstruction of effective signals, the rotor’s vibration signal in working frequency can be obtained. In the simulation case study, the proposed method is applied in several sets of generated low SNR signals, and the extraction results are compared with those obtained by the least squares method. The experimental study is conducted to extract the unbalanced signal of micro-motor rotors for dynamic balance. The residual unbalance of the balanced rotor is relatively small, with a repeated accuracy of less than 2 mg and a measurement accuracy of G0.4. Results indicate the effectiveness of the proposed quadratic SSA-VMD method in the unbalanced feature extraction for micro-motor rotors.