Long Junbo, Deng Changshou, Wang Haibin
College of Electronic Information Engineering, Jiujiang University, Jiujiang, China.
College of Computer and Big Data Science, Jiujiang University, Jiujiang, China.
Sci Rep. 2024 Sep 3;14(1):20456. doi: 10.1038/s41598-024-70347-0.
Post-processing synchrosqueezing transform and synchroextracting transform methods can improve TFR resolution for fault diagnosis. The normal and fault signal can be described by infinite variance process, and 1 < α ≤ 2, even the background noise belongs to the process under complex conditions. The effect of traditional SST and SET methods is greatly reduced and even lost in infinite variance process environment. Several robust post-processing methods are proposed including FSET, FSSET, FSOSET and FMSST technology employing infinite variance process statistical model and FLOS, and their mathematical derivation are completed in this paper. The proposed methods are compared with the conventional methods, and the results show that the proposed methods achieve better results than the existing methods. In addition, the new methods are applied to diagnose the bearing outer race DE signals polluted by infinite variance process, the result demonstrates that they have performance advantages. Finally, the characteristics, shortcomings and application scenarios of the improved algorithms are summarized.
后处理同步挤压变换和同步提取变换方法可提高用于故障诊断的时频分辨率。正常信号和故障信号可由无限方差过程描述，且1 < α ≤ 2，甚至在复杂条件下背景噪声也属于该过程。在无限方差过程环境中，传统的同步挤压变换（SST）和同步提取变换（SET）方法的效果会大大降低甚至失效。本文提出了几种鲁棒的后处理方法，包括采用无限方差过程统计模型的FSET、FSSET、FSOSET和FMSST技术以及FLOS，并完成了它们的数学推导。将所提出的方法与传统方法进行比较，结果表明所提出的方法比现有方法取得了更好的效果。此外，将新方法应用于诊断受无限方差过程污染的轴承外圈驱动端（DE）信号，结果表明它们具有性能优势。最后，总结了改进算法的特点、缺点和应用场景。
