Fan Bearing Fault Diagnosis Algorithm Based on Improved VMD and LLe

In order to enhance the precision of fan bearing fault diagnosis, this study presents a model for fan bearing fault diagnosis based on an improved VMD and LLE. Firstly, the fast Fourier transform (FFT) is utilized to extract the time-frequency graph of vibration signals, and the enhanced VMD algorithm is applied for denoising vibration signals and constructing high-frequency multi-domain feature vectors. Secondly, the improved LLE algorithm is employed to reduce data dimensionality, followed by classification using an SVM model. Finally, compared with three other feature reduction methods, Fisher's measure is used to assess the classification accuracy of all four algorithms, confirming a significant improvement in accuracy for our proposed method.