Condition Monitoring of Robust Damage of Cantilever Shaft Using Experimental and Adaptive Neuro-fuzzy Inference System (ANFIS)

A methodology has been developed to predict fatigue crack propagation life of mild steel shaft. It has been assessed by adopting Adaptive Neuro-fuzzy Inference System (ANFIS), a novel soft-computing approach, suitable for non-linear, noisy and complex problems like fatigue. The proposed hybrid neuro-fuzzy system combines the learning capabilities of neural networks with fuzzy inference system for nonlinear function approximation. A single-output Sugeno-type Fuzzy Inference System (FIS) using grid partitioning has been modelled in this work. After comparing the output, it has been found that the proposed model has proved its efficiency quite satisfactorily.