An Enhanced Transient Extraction Transform Algorithm and Its Application in Fault Diagnosis

In industrial rotating machinery, it is very difficult to extract the characteristics of transient signals because of the complex operating environment and the huge noise interference. Transient extraction transform (TET) is a time-frequency analysis method to characterize and extract transient features of signals. However, the transient feature extraction effect of TET strong background noise is not good. Therefore, an enhanced transient feature extraction algorithm (ETET) is proposed in this paper. ETET uses a potential energy function improvement operator to improve the differentiation of transient functions extracted from the TFW, making it easier to extract fault functions. The simulation signals and actual experimental results show that the proposed method can indeed improve the signal characteristics and has good sound robustness.