首页|基于改进VMD的逆变电路开路故障信号特征提取

基于改进VMD的逆变电路开路故障信号特征提取

Feature extraction of open-circuit fault signals in an inverter based on improved VMD

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基于输出电流分析的方法对逆变电路进行故障诊断时易受噪声干扰,影响故障诊断准确率,提出一种用优化算法对变分模态分解(VMD)进行改进的信号处理方法.通过麻雀搜索算法对传统VMD中的参数进行寻优,依据最优参数对电流信号进行分解,获取最佳的分解去噪效果.与小波变换、经验模态分解等信号处理方法对比,用误差评价指标对去噪效果评估,去噪信号功率谱图像可直观体现频域特征.结果表明,所提方法能有效降低噪声数量且频域细节特征误差不超过4%,验证了其有效性和可行性.
An analysis-based approach to fault diagnosis of an inverter circuit is easily affected by noise interference,and the accuracy of fault diagnosis affected too.An improved signal processing method for variational modal decomposition(VMD)was proposed.Through the sparrow search algorithm to opti-mize the parameters in the traditional VMD and decompose the current signal according to the optimal parameters,the optimal denoising effect could be obtained.Compared with wavelet transform,empirical mode decomposition and other signal processing methods,the error evaluation index was used to eval-uate the denoising effect,and the power spectrum graph image was more intuitively reflected in the fre-quency domain.The experimental results showed that the proposed method could effectively reduce the noise content and the error of frequency detail feature was less than 4%,verifying the effectiveness and feasibility of the method.

fault diagnosisfeature extractionsparrow search algorithmvariational modal decomposition

吴玉虹、贾凯、高英

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昆明理工大学 信息工程与自动化学院,昆明 650500

故障诊断 特征提取 麻雀搜索算法 变分模态分解

2024

兰州大学学报(自然科学版)
兰州大学

兰州大学学报(自然科学版)

CSTPCD北大核心
影响因子:0.855
ISSN:0455-2059
年,卷(期):2024.60(3)