Bejarano-Rodríguez, Fernando A.

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Crack identification of a rotating shaft with integrated wireless sensors
(2007) Bejarano-Rodríguez, Fernando A.; Jia, Yi; College of Engineering; Just, Frederick; Serrano, David; Department of Mechanical Engineering; Resto, Pedro
This study developed a novel real-time monitoring diagnostic method of determining the position and depth of a transverse open crack on a rotating shaft, which vibrates in bending due to the harmonic excitation force induced by an unbalanced disk coupled at the midspan. The development of a new wireless sensor capable of being mounted directly on the shaft allowed modeling of the dynamic system using the data obtained at different points of interest of the structure in the rotating coordinate system. Vibration parameters were obtained first from a simulation employing the Finite Element Method and then experimentally using Modal Analysis for different crack positions and depths. The unique relation between the vibration parameters and crack characteristics found was employed to solve the inverse problem; relate failure patterns of acceleration at different points of the shaft with the crack size and location by means of Artificial Neural Networks Method working as function approximator. The predictive neural networks were selected experimentally and then validated showing that the damage detection sensitivity parameters used depended on the acceleration signals at different points of the shaft.