crossrefApplied Sciences2024-11-12Cited by 40
Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization
Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim
This paper presents a fault diagnosis technique for milling machines based on acoustic emission (AE) signals and a hybrid deep learning model optimized with a genetic algorithm. Mechanical failures in milling machines, particularly in critical components like cutting tools, gears…