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Local Entropy Optimization-Adaptive Demodulation Reassignment Transform for Advanced Analysis of Non-Stationary
Yuli Niu1, Zhongchao Liang1, Hengshan Wu2
1Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
None:
This research proposes a new method for time-frequency analysis, termed the Local Entropy Optimization-Adaptive Demodulation Reassignment Transform (LEOADRT), which is specifically designed to efficiently analyze complex, non-stationary mechanical vibration signals that exhibit multiple instantaneous frequencies or where the instantaneous frequency ridges are in close proximity to each other. The method introduces a demodulation term to account for the signal's dynamic behavior over time, converting each component into a stationary signal. Based on the local optimal theory of Rényi entropy, the demodulation parameters are precisely determined to optimize the time-frequency analysis. Then, the energy redistribution of the ridges already generated in the time-frequency map is performed using the maximum local energy criterion, significantly improving time-frequency resolution. Experimental results demonstrate that the performance of the LEOADRT algorithm is superior to existing methods such as SBCT, EMCT, VSLCT, and GLCT, especially in processing complex non-stationary signals with non-proportionality and closely spaced frequency intervals. This method provides strong support for mechanical fault diagnosis, condition monitoring, and predictive maintenance, making it particularly suitable for real-time analysis of multi-component and cross-frequency signals.
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