Phoneme-inspired acoustic frame embedded lightweight transformer for rolling bearing fault diagnosis

Acoustic-based fault diagnosis has gained increasing attention due to its flexibility and applicability under diverse operating conditions. Recent studies have demonstrated that Transformer-based architectures exhibit remarkable capability in modeling long-range temporal dependencies, so they are particularly effective for complex time series representation and analysis. However, applying Transformers to acoustic fault diagnosis faces the following critical challenges. The primary hurdle lies in discriminating short-duration nonstationary acoustic features amidst complex environmental interference, Simultaneously, how to ensure model diagnostic performance under limited computing resources is a challenge.…

• NN
  National Natural Science Foundation of China