基于自适应集成补丁变换的齿轮故障诊断方法

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振动与冲击 ›› 2023, Vol. 42 ›› Issue (11) : 19-26.

论文

潘海洋,殷学林,郑近德,童靳于

作者信息 +

Gear fault diagnosis method based on adaptive ensemble patch transformation

PAN Haiyang, YIN Xuelin, ZHENG Jinde, TONG Jinyu

Author information +

文章历史 +

摘要

针对集成补丁变换（Ensemble Patch Transformation, EPT）进行信号分解时易出现模态混淆和参数无法自适应的问题，论文提出一种基于自适应集成补丁变换（Adaptive Ensemble Patch Transformation, AEPT）的齿轮故障诊断方法。在AEPT分解过程中，首先通过极值约束获得若干个采样点，并以此完成信号局部划分，实现信号降噪；然后，结合极值点周期设置补丁参数，搭建集成补丁结构；最后，通过迭代和筛分将任意一个非线性非平稳信号自适应地分解为若干个瞬时频率具有物理意义的集成补丁分量（Ensemble Patch Component, EPC）。通过调幅仿真信号、齿轮故障仿真信号和实际齿轮裂纹信号进行实验验证，结果表明，AEPT方法在抑制模态混淆、鲁棒性等方面拥有明显的优势，可以有效的完成齿轮故障诊断。

Abstract

Signal decomposition for ensemble patch transformation(EPT) is prone to modal confusion and parameter inability to adapt, the paper proposes a gear fault diagnosis method based on adaptive ensemble patch transformation (AEPT). In the AEPT process, a number of sampling points are obtained through the extreme value constraint, and the signal is divided locally to achieve signal noise reduction; then, the patch parameters are set in combination with the extreme point period to build an integrated patch structure; finally, through iteration and screening, any nonlinear non-stationary signal is adaptively decomposed into several instantaneous frequency ensemble patch components (EPC) with physical significance. Through the amplitude modulation simulation signal, gear fault simulation signal and gear crack signal, the results show that the AEPT method has obvious advantages in suppressing modal aliasing and robustness, and can effectively diagnose gear fault.

导出引用

潘海洋,殷学林,郑近德,童靳于. 基于自适应集成补丁变换的齿轮故障诊断方法[J]. 振动与冲击, 2023, 42(11): 19-26

PAN Haiyang, YIN Xuelin, ZHENG Jinde, TONG Jinyu. Gear fault diagnosis method based on adaptive ensemble patch transformation[J]. Journal of Vibration and Shock, 2023, 42(11): 19-26

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