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基于CEEMDAN-HT的永磁同步电机匝间短路振动信号故障特征提取研究 被引量:3
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作者 夏焰坤 李欣洋 +1 位作者 任俊杰 寇坚强 《振动与冲击》 EI CSCD 北大核心 2024年第5期72-81,共10页
由于长时间处于高负荷运行状态,永磁同步电机(permanent magnet synchronous motor, PMSM)定子绕组线圈匝与匝之间的绝缘性能容易降低,导致出现匝间短路,此时电机的振动强度会发生改变。针对此现象,提出将自适应噪声完备经验模态分解(co... 由于长时间处于高负荷运行状态,永磁同步电机(permanent magnet synchronous motor, PMSM)定子绕组线圈匝与匝之间的绝缘性能容易降低,导致出现匝间短路,此时电机的振动强度会发生改变。针对此现象,提出将自适应噪声完备经验模态分解(complete ensemble empirical mode decomposition with adaptive noise, CEEMDAN)与希尔伯特变换(Hilbert transform, HT)结合,构成一种CEEMDAN-HT非线性信号分析方法,并将其应用于提取振动信号故障特征。首先,利用CEEMDAN算法分解振动信号,得到一系列本征模态函数(intrinsic mode function, IMF),并将主元分析中的方差贡献率用于识别包含故障特征信息的IMF。其次,使用HT对方差贡献率较高的IMF进行分析,并以三维联合时频图呈现时间、瞬时频率与幅值,得到了主要故障特征。最后,使用ANSYS有限元软件建立了电机短路故障模型,并搭建了短路故障试验平台,通过对比有限元仿真结果与试验结果,对提出的方法进行了有效性和准确性验证。 展开更多
关键词 永磁同步电机(permanent magnet synchronous motor PMSM) 振动信号 自适应噪声完备经验模态分解(complete ensemble empirical mode decomposition with adaptive noise CEEMDAN) 特征提取 希尔伯特变换(Hilbert transform HT)
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A novel feature extraction method for ship-radiated noise 被引量:6
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作者 Hong Yang Lu-lu Li +1 位作者 Guo-hui Li Qian-ru Guan 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2022年第4期604-617,共14页
To improve the feature extraction of ship-radiated noise in a complex ocean environment,a novel feature extraction method for ship-radiated noise based on complete ensemble empirical mode decomposition with adaptive s... To improve the feature extraction of ship-radiated noise in a complex ocean environment,a novel feature extraction method for ship-radiated noise based on complete ensemble empirical mode decomposition with adaptive selective noise(CEEMDASN) and refined composite multiscale fluctuation-based dispersion entropy(RCMFDE) is proposed.CEEMDASN is proposed in this paper which takes into account the high frequency intermittent components when decomposing the signal.In addition,RCMFDE is also proposed in this paper which refines the preprocessing process of the original signal based on composite multi-scale theory.Firstly,the original signal is decomposed into several intrinsic mode functions(IMFs)by CEEMDASN.Energy distribution ratio(EDR) and average energy distribution ratio(AEDR) of all IMF components are calculated.Then,the IMF with the minimum difference between EDR and AEDR(MEDR)is selected as characteristic IMF.The RCMFDE of characteristic IMF is estimated as the feature vectors of ship-radiated noise.Finally,these feature vectors are sent to self-organizing map(SOM) for classifying and identifying.The proposed method is applied to the feature extraction of ship-radiated noise.The result shows its effectiveness and universality. 展开更多
关键词 complete ensemble empirical mode decomposition with adaptive noise Ship-radiated noise Feature extraction Classification and recognition
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