Wavelet-based technique for detection of mechanical chaos
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This paper presents the development of an innovative wavelet-based diagnostic methodology to perform real-time detection of mechanical chaos occurring in high-speed, high-performance rotor-dynamic systems. The objective is to provide an early warning if macroscopic and/or microscopic faults are detected in time to prevent catastrophic mechanical failures that could compromise safety and cause expensive downtime. In this paper, we make use of the popular discrete wavelet transform (DWT) operating in the time-domain that has demonstrated to be superior to Fourier-based methods and is highly effective in identifying small variations of parameters in rapid transient events. In addition, the DWT and its extension to Wavelet Packet Transform (WPT) are real-time implementable in many DSP chips. We present a comparison between the wavelet approach and the traditional technique to identify, chaotic signals using synthetic and laboratory-generated data.
