System instability and chaotic response are the failure modes that could significantly impact the reliability and operating safety of high-speed rotor-dynamical machines. Initiation and propagation of surface cracks in rotary shafts are common causes for such failure modes. To be able to detect the onset and progression of these faults will considerably extend the lifetime and improve the reliability of the mechanical system. A wavelet-based algorithm effective in identifying mechanical chaotic response has been applied to determine the nonlinear dynamical characteristics of a model-based, cracked rotor. This investigation confirms reported correlation of surface crack breathing with rotor chaotic motions. The effectiveness of the algorithm in detecting rotor-dynamic instability induced by mechanical faults as contrast to algorithms that are based on nonlinear dynamics is discussed. The results show not just the feasibility of the algorithm in mechanical fault diagnosis but also suggest its applicability to in-line, real-time condition monitoring at both the system and component levels.
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