Research on feature extraction method for different levels of cracks and pitting in spur gear based on dynamic characteristic templates

Health monitoring and fault diagnosis play a pivotal role in ensuring the safety of helicopter flights. Dynamic analysis has proven to be effective in accurately capturing the characteristics of crack and pitting signals. However, its application in fault diagnosis has limitations. This study introduces a feature extraction method based on the dynamic characteristic templates (DCTs) for different levels of cracks and pitting in spur gears. This method serves as a bridge between dynamic analysis and fault diagnosis, facilitating a comprehensive assessment of gear health. The integration of improved sparrow search algorithm (ISSA) and variational mode decomposition matching (VMDM) techniques enhances the search and matching capabilities of target signal based on DCTs. Based on above research, this study reveals distinctive morphological characteristics in the signals associated with crack and pitting under different levels and these characteristics serve as valuable index for fault diagnosis.