S. Devendiran

Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis

Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study

Recent advancements in nano-lubrication strategies for machining processes considering their health and environmental impacts

Deep learning for smart manufacturing: Methods and applications

A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery

Exploring the potential of nanofertilizers for a sustainable agriculture

Diagnosis of combined faults in Rotary Machinery by Non-Naive Bayesian approach

Multi-Stage Feature Selection by Using Genetic Algorithms for Fault Diagnosis in Gearboxes Based on Vibration Signal

Early fault diagnosis of bearing and stator faults of the single-phase induction motor using acoustic signals

Applications of machine learning to machine fault diagnosis: A review and roadmap

Diagnostics of gear faults using ensemble empirical mode decomposition, hybrid binary bat algorithm and machine learning algorithms

A Gear Fault Identification using Wavelet Transform, Rough set Based GA, ANN and C4.5 Algorithm

Optimization of Cutting Parameters on turning of Incoloy 800H using Al2O3 Nanofluid in Coconut oil