Fault diagnosis in rotors using adaptive neuro-fuzzy inference systems

Condition monitoring of rotor dynamic systems is emerging research in recent years. The proposed research is a condition monitoring methodology based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to detect the open cracks in the single disk rotor-bearing system. Condition monitoring systems generally requires a large amount of processed data for a specific output. The proposed methodology uses the same input data to train two different ANFIS without compromising on the accuracy of the results. The response of rotor-bearing system is generated by using finite element model analysis and harmonic balance method. All simulations are programed in MATLAB programing software. The effects of open groove or wedge cracks (notch crack) on natural frequency and resultant operational response (nodal deflections) of rotor-bearing systems are analyzed. Response orbit at 3× resonance of first natural frequency is analyzed to diagnose the crack in rotor shaft. Resultant operational response (Absolute response due to crack) is recorded for various crack locations and crack depths. Continuous Wavelet Transforms (CWT) are used, to extract the features from operational deflection shape (from operat