基于蝙蝠算法优化的变分模态分解的转子裂纹检测方法

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振动与冲击 ›› 2020, Vol. 39 ›› Issue (6) : 98-103.

论文

焦博隆1,2，钟志贤1,2，刘翊馨1,2，王家园1,2，祝长生3

作者信息 +

Rotor crack detection method based on variational mode decomposition based on optimization parameters of bat algorithm

JIAO Bolong1,2，ZHONG Zhixian1,2，LIU Yixin1,2，WANG Jiayuan1,2，ZHU Changsheng3

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文章历史 +

摘要

针对转子裂纹故障特征难于提取,提出了一种基于蝙蝠算法(BA)优化参数的变分模态分解(VMD)诊断转子裂纹故障的方法。将蝙蝠算法应用于变分模态分解，对变分模态分解中参数K和惩罚因子α进行全局寻优，用BA搜索VMD的最优(α, K)组合，迭代过程采用局部极小包络熵为适应度值。仿真分析的结果表明，BA-VMD方法能很好的完成VMD参数K和α的自适应获取，且在抗模态混叠和抗噪声干扰方面的具有明显优势，最后采用BA-VMD方法对裂纹转子的位移信号进行了实验分析，分析结果表明，采用BA-VMD方法处理后的频谱能充分反映出信号的频率特征，且通过频率结构特征很容易识别出转子裂纹的故障特征。
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Abstract

A method for rotor crack fault diagnosis based on variational mode decomposition(VMD) with bat algorithm (BA) optimization parameters was proposed, aiming at overcoming the difficulty in identifying rotor crack fault features.The global optimization of parameter K and penalty factor α in variational mode decomposition was carried out by applying the bat algorithm.The optimal (α, K) combination of VMD was searched by using the BA and the local minimum envelope entropy was used as a fitness function in the iteration process.The simulation results show that the BA-VMD method can achieve the adaptive acquisition of VMD parameters (α, K), and has obvious advantages in anti-modal aliasing and anti-noise interference.Finally, the displacement signal of a cracked rotor was analyzed by the BA-VMD method.The results show that the frequency spectrum processed by the BA-VMD method can fully describe the frequency characteristics of the signal, and the fault characteristics of the cracked rotor can be easily identified by the frequency structure characteristics.

导出引用

焦博隆1,2，钟志贤1,2，刘翊馨1,2，王家园1,2，祝长生3. 基于蝙蝠算法优化的变分模态分解的转子裂纹检测方法[J]. 振动与冲击, 2020, 39(6): 98-103

JIAO Bolong1,2，ZHONG Zhixian1,2，LIU Yixin1,2，WANG Jiayuan1,2，ZHU Changsheng3. Rotor crack detection method based on variational mode decomposition based on optimization parameters of bat algorithm[J]. Journal of Vibration and Shock, 2020, 39(6): 98-103

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