A novel satellite fault diagnosis scheme is presented based on the predictive filter and empirical mode composition（EMD）.First,the predictive filter is utilized to obtain the fault estimation,which is corrupted by n...A novel satellite fault diagnosis scheme is presented based on the predictive filter and empirical mode composition（EMD）.First,the predictive filter is utilized to obtain the fault estimation,which is corrupted by noise.Then the EMD method is introduced to decompose the fault estimation into a finite number of intrinsic mode functions and extract the trend of faults for fault diagnosis.The proposed scheme has the ability of diagnosing both abrupt and incipient faults of the actuator in a satellite attitude control subsystem.A mathematical simulation is given to illustrate the effectiveness of the proposed scheme.展开更多
Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity ...Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.展开更多
Aiming at the problem of gliding near space hypersonic vehicle(NSHV)trajectory prediction,a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition(EMD)is proposed.The method analyz...Aiming at the problem of gliding near space hypersonic vehicle(NSHV)trajectory prediction,a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition(EMD)is proposed.The method analyzes the motion characteristics of the skipping gliding NSHV and verifies that the aerodynamic acceleration of the target has a relatively stable rule.On this basis,EMD is used to extract the trend of aerodynamic acceleration into multiple sub-items,and aggregate sub-items with similar attributes.Then,a prior basis function is set according to the aerodynamic acceleration stability rule,and the aggregated data are fitted by the basis function to predict its future state.After that,the prediction data of the aerodynamic acceleration are used to drive the system to predict the target trajectory.Finally,experiments verify the effectiveness of the method.In addition,the distribution of prediction errors in space is discussed,and the reasons are analyzed.展开更多
为解决风力发电直接并网所产生的功率波动问题,提出了一种基于改进阿基米德优化算法融合自适应噪声完全集合经验模态分解(complete ensemble EMD with adaptive noise,CEEMDAN)的容量配置方法。采用由限幅与滑动平均结合的加权滤波算法...为解决风力发电直接并网所产生的功率波动问题,提出了一种基于改进阿基米德优化算法融合自适应噪声完全集合经验模态分解(complete ensemble EMD with adaptive noise,CEEMDAN)的容量配置方法。采用由限幅与滑动平均结合的加权滤波算法平滑风电出力,同时减小平滑结果的滞后性,得到风电并网功率和混合储能系统(hybrid energy storage system,HESS)参考功率。为了合理分配HESS的内部功率,借助CEEMDAN分解HESS的参考功率,得到高低频分量。综合考虑HESS功率和容量、荷电状态(state of charge,SOC)与负荷缺点率等因素,构建以年综合成本最小为目标的容量优化配置模型并采用改进阿基米德优化算法求解。基于实际算例进行仿真分析,结果表明,与原始风电并网相比,HESS配置方案将波动率减少了13.538%,平滑度提高了16.057%。相较于传统单一储能平抑效果更加明显,减少了容量配置。同时,对比传统阿基米德优化算法节省了15.325%的投资成本。展开更多
基金supported by the National Natural Science Foundation of China (60874054)
文摘A novel satellite fault diagnosis scheme is presented based on the predictive filter and empirical mode composition（EMD）.First,the predictive filter is utilized to obtain the fault estimation,which is corrupted by noise.Then the EMD method is introduced to decompose the fault estimation into a finite number of intrinsic mode functions and extract the trend of faults for fault diagnosis.The proposed scheme has the ability of diagnosing both abrupt and incipient faults of the actuator in a satellite attitude control subsystem.A mathematical simulation is given to illustrate the effectiveness of the proposed scheme.
基金The authors gratefully acknowledge the support of the National Natural Science Foundation of China(No.11574250).
文摘Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.
基金supported by the National High-Tech R&D Program of China(2015AA70560452015AA8017032P)the Postgraduate Funding Project(JW2018A039)。
文摘Aiming at the problem of gliding near space hypersonic vehicle(NSHV)trajectory prediction,a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition(EMD)is proposed.The method analyzes the motion characteristics of the skipping gliding NSHV and verifies that the aerodynamic acceleration of the target has a relatively stable rule.On this basis,EMD is used to extract the trend of aerodynamic acceleration into multiple sub-items,and aggregate sub-items with similar attributes.Then,a prior basis function is set according to the aerodynamic acceleration stability rule,and the aggregated data are fitted by the basis function to predict its future state.After that,the prediction data of the aerodynamic acceleration are used to drive the system to predict the target trajectory.Finally,experiments verify the effectiveness of the method.In addition,the distribution of prediction errors in space is discussed,and the reasons are analyzed.
文摘为解决风力发电直接并网所产生的功率波动问题,提出了一种基于改进阿基米德优化算法融合自适应噪声完全集合经验模态分解(complete ensemble EMD with adaptive noise,CEEMDAN)的容量配置方法。采用由限幅与滑动平均结合的加权滤波算法平滑风电出力,同时减小平滑结果的滞后性,得到风电并网功率和混合储能系统(hybrid energy storage system,HESS)参考功率。为了合理分配HESS的内部功率,借助CEEMDAN分解HESS的参考功率,得到高低频分量。综合考虑HESS功率和容量、荷电状态(state of charge,SOC)与负荷缺点率等因素,构建以年综合成本最小为目标的容量优化配置模型并采用改进阿基米德优化算法求解。基于实际算例进行仿真分析,结果表明,与原始风电并网相比,HESS配置方案将波动率减少了13.538%,平滑度提高了16.057%。相较于传统单一储能平抑效果更加明显,减少了容量配置。同时,对比传统阿基米德优化算法节省了15.325%的投资成本。
