1.School of Mechanical Engineering, Anhui University of Technology, Maanshan 243032, China;
2.MOE Engineering Research Center of Hydraulic Vibration and Control, Anhui University of Technology, Maanshan 243032, China
摘要直接快速迭代滤波（direct fast iterative filtering ,DFIF）是最近提出的一种非线性和非平稳信号分析方法。针对DFIF方法需人为设定滤波区间调整参数，且该参数在迭代计算过程中缺乏自适应性等问题，提出了自适应直接快速迭代滤波（adaptive direct fast iterative filtering ,ADFIF）方法，该方法基于瞬时频率波动能量差准则，自适应确定DFIF算法外循环每层迭代筛分过程中最优滤波区间调整参数。ADFIF方法能够自适应地将任意非线性和非平稳信号分解为若干个瞬时频率具有物理意义的近似窄带信号和一个趋势项之和。通过仿真信号和滚动轴承故障信号分析，将所提ADFIF方法与原DFIF，自适应局部迭代滤波、变分模态分解、经验模态分解等方法进行对比，结果表明，所提ADFF方法在抑制模态混叠，抗噪性方面具有一定的优势，且能提取出滚动轴承更多故障特征信息。
Abstract：Direct fast iterative filtering (DFIF) is a recently proposed nonlinear and non-stationary signal analysis method. Aiming at the problems that the DFIF method needs to preset the adjustment parameter of filtering interval, which lacks adaptability in the process of iterative calculation. In this paper, adaptive direct fast iterative filtering method is proposed based on the instantaneous frequency fluctuation energy difference criterion, which can adaptively determine the optimal filter interval adjustment parameters in the iterative screening process of each layer in the outer loop of DFIF algorithm. The ADFIF method can adaptively decompose a given nonlinear and non-stationary signal into the sum of several approximately narrow band signals whose instantaneous frequency has physical significance and a trend term. Through the simulated and measured signal analysis of rolling bearings, the proposed ADFIF method is compared with original DFIF, the adaptive local iterative filtering, variational mode decomposition, and empirical mode decomposition and the results show that the proposed ADFF method has certain advantages in suppressing mode mixing and noise resistance, and can extract more fault characteristic information of rolling bearing.
丁文海1,2，郑近德1,2，潘海洋1,2，孟瑞1,2，牛礼民1,2. 基于自适应直接快速迭代滤波的滚动轴承故障诊断方法[J]. 振动与冲击, 2023, 42(14): 20-29.
DING Wenhai1,2，ZHENG Jinde1,2，PAN Haiyang1,2，MENG Rui1,2，NIU Limin1,2. Adaptive direct fast iterative filtering based rolling bearing fault diagnosis. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(14): 20-29.
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