Repetitive transients are typical symptoms of rotating faults and their extraction can be used to indicate early rotating faults. The main issue is to extract the cyclo-stationarity of repetitive transients which is insensitive to impulsive noises. The objective of traditional blind deconvolution methods is to recover impulsive signals from time domain. Considering the cyclo-stationarity of repetitive transients, a novel blind deconvolution (BD) technique, coined as prior-unknown blind deconvolution technique, is proposed to extract the cyclo-stationarity of repetitive transients. The proposed technique finds an inverse filter by minimizing an optimal criterion that is defined based on envelope spectrum (ES). Additionally, the proposed method does not require the prior knowledge of initialization for BD. Based on the proposed method and the generalized Lp/Lq norm, a demonstration about how to design a BD algorithm for extracting the cyclo-stationarity of repetitive transients is introduced. Results showed that the proposed method is superior to traditional time-domain BD algorithms in detection performance and its robustness.

重复的瞬变是旋转故障的典型症状，其提取可用于指示早期旋转故障。主要问题是提取对脉冲噪声不敏感的重复瞬态的循环平稳性。传统盲解卷积方法的目的是从时域中恢复脉冲信号。考虑到重复瞬态的循环平稳性，提出了一种新颖的盲反卷积（BD）技术，称为先验未知盲反卷积技术，用于提取重复瞬态的循环平稳性。所提出的技术通过最小化基于包络谱（ES）定义的最佳准则来找到逆滤波器。另外，所提出的方法不需要用于BD的初始化的先验知识。介绍了Lp / Lq范数，演示了如何设计用于提取重复瞬态的循环平稳性的BD算法。结果表明，该方法在检测性能和鲁棒性方面优于传统的时域BD算法。