Work

Local Entropy Optimization–Adaptive Demodulation Reassignment Transform for Advanced Analysis of Non-Stationary Mechanical Signals

Year: 2025

Type: article

Abstract: 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.

Source: Entropy

DOI: 10.3390/e27070660

Authors: Yuli Niu, Zhongchao Liang, Hengshan Wu, Jianxin Tan, Tianyang Wang, Fulei Chu

Institutions: Tsinghua University, Beijing Jiaotong University

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funder: National Natural Science Foundation of China