A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the s...A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.展开更多
Noise interference critically impairs the stability and data accuracy of sensing systems.However,current suppression strategies fail to concurrently mitigate intrinsic system noise and extrinsic environmental noise.Th...Noise interference critically impairs the stability and data accuracy of sensing systems.However,current suppression strategies fail to concurrently mitigate intrinsic system noise and extrinsic environmental noise.This study introduces a composite denoising approach to address this challenge.This method is based on the ameliorated ellipse fitting algorithm(AEFA)and adaptive successive variational mode decomposition(ASVMD).This algorithm employs AEFA to eliminate system noise tightly coupled with direct-current and alternating-current components in the interference signal,thereby obtaining a phase signal containing only environmental noise.The ASVMD technique adaptively extracts environmental noise components predominantly present in the phase signal.To achieve optimal decomposition results automatically,the permutation entropy criterion is employed to refine decomposition parameters.The correlation coefficient is utilized to differentiate effective components from noise components in the decomposition results.Experimental results indicate that the combined AEFA and ASVMD algorithm effectively suppresses both system and environmental noises.When applied to 50 Hz vibration signal processing,the proposed approach achieves a noise reduction of 17.81 dB and a phase resolution of 35.14μrad/√Hz.Given the excellent performance of the noise suppression,the proposed approach holds great application potential in high-performance interferometric sensing systems.展开更多
In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information ...In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional Retinex algorithms in image entropy.展开更多
Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the...Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the rotor vibration in AMBs is to adopt a notch filter or adaptive filter in the AMB controller. However, these methods cannot obtain the precise amplitude and phase of the compensation current. Thus, they are not so effective in terms of suppressing the vibrations of the fundamental and other harmonic orders over the whole speed range. To improve the vibration suppression performance of AMBs,an adaptive filter based on Least Mean Square(LMS) is applied to extract the vibration signals from the rotor displacement signal. An Iterative Search Algorithm(ISA) is proposed in this paper to obtain the corresponding relationship between the compensation current and vibration signals. The ISA is responsible for searching the compensating amplitude and shifting phase online for the LMS filter, enabling the AMB controller to generate the corresponding compensation force for vibration suppression. The results of ISA are recorded to suppress vibration using the Look-Up Table(LUT) in variable speed range. Comprehensive simulations and experimental validations are carried out in fixed and variable speed range, and the results demonstrate that by employing the ISA, vibrations of the fundamental and other harmonic orders are suppressed effectively.展开更多
Vortex induced vibration(VIV)is a challenge in ocean engineering.Several devices including fairings have been designed to suppress VIV.However,how to optimize the design of suppression devices is still a problem to be...Vortex induced vibration(VIV)is a challenge in ocean engineering.Several devices including fairings have been designed to suppress VIV.However,how to optimize the design of suppression devices is still a problem to be solved.In this paper,an optimization design methodology is presented based on data-driven models and genetic algorithm(GA).Data-driven models are introduced to substitute complex physics-based equations.GA is used to rapidly search for the optimal suppression device from all possible solutions.Taking fairings as example,VIV response database for different fairings is established based on parameterized models in which model sections of fairings are controlled by several control points and Bezier curves.Then a data-driven model,which can predict the VIV response of fairings with different sections accurately and efficiently,is trained through BP neural network.Finally,a comprehensive optimization method and process is proposed based on GA and the data-driven model.The proposed method is demonstrated by its application to a case.It turns out that the proposed method can perform the optimization design of fairings effectively.VIV can be reduced obviously through the optimization design.展开更多
针对目前雷达干扰抑制决策智能化程度低的问题,提出了一种基于双深度优先经验回放和可变贪婪算法改进的双重竞争深度Q网络(double dueling deep Q network,D3QN)决策的雷达干扰抑制方法。首先对雷达目标回波和干扰混合信号进行特征提取...针对目前雷达干扰抑制决策智能化程度低的问题,提出了一种基于双深度优先经验回放和可变贪婪算法改进的双重竞争深度Q网络(double dueling deep Q network,D3QN)决策的雷达干扰抑制方法。首先对雷达目标回波和干扰混合信号进行特征提取;然后根据信号特征通过可变贪婪算法选择动作作用于干扰,并将动作前后的信号特征存储于双深度优先经验回放池后,经过学习决策出最优的干扰抑制策略;最后使用该策略抑制干扰后输出。实验结果表明,该方法有效改善了信号的脉压结果,显著提升了信号的信干噪比,相较于基于D3QN的传统干扰抑制方法,在策略准确率和收敛速度上分别提升了7.3%和8.7%。展开更多
针对非整数阶盲移频干扰生成的欺骗干扰效果单一,假目标分布规律等问题,提出了一种基于阶梯波盲移频的线性调频(Linear Frequency Modulation,LFM)雷达干扰。设计了均匀阶梯波和非均匀阶梯波两种移频方法,推导了基于阶梯波盲移频的LFM...针对非整数阶盲移频干扰生成的欺骗干扰效果单一,假目标分布规律等问题,提出了一种基于阶梯波盲移频的线性调频(Linear Frequency Modulation,LFM)雷达干扰。设计了均匀阶梯波和非均匀阶梯波两种移频方法,推导了基于阶梯波盲移频的LFM雷达干扰数学模型。该技术引入阶梯波函数对系统阶数进行调制,在系统延时不变的情况下,可以实现精确位置的欺骗假目标群或固定范围内的随机假目标。通过调整阶梯波函数的各项参数,可以完成对假目标位置、幅度和数量的控制。仿真验证表明,采用均匀阶梯波函数可以实现特定位置的密集假目标,采用非均匀阶梯波函数能够在特定范围内生成随机的假目标。对调频斜率捷变的雷达有着较强的干扰能力,具有较好的工程应用意义。展开更多
The rolling mill vibration not only seriously causes the strip thickness heterogeneity, but also damages the rolling mill equipment and its electrical components. Existing vibration suppression methods are passive and...The rolling mill vibration not only seriously causes the strip thickness heterogeneity, but also damages the rolling mill equipment and its electrical components. Existing vibration suppression methods are passive and mainly tune mechanical, hydraulic, electrical and rolling process parameters. A new active vibration suppression method was thus proposed using the disturbance estimation and compensation algorithm. Firstly, the hydraulic-mechanical coupling model of the rolling mill vibration was established, and an active vibration suppressor was designed based on the extended state observer. Then, through the numerical simulation, it is found that the vibration energy is reduced by 35.3% using the vibration suppressor, and the vibration suppressor is valid when the vibration frequency is lower than 60 Hz Finally, the vibration suppressor was applied to the in-site manufacturing, and the expected vibration suppression was obtained. The method makes the produced steel strip have more uniform thickness and further significantly increases the finished product ratio.展开更多
Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorit...Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorithm had been studied by many researchers and applied in many fields. In the algorithm, how to select the suppressed rate is a key step. In this paper, we give a method to select the fixed suppressed rate by the structure of the data itself. The experimental results show that the proposed method is a suitable way to select the suppressed rate in suppressed fuzzy c-means clustering algorithm.展开更多
基金The National Natural Science Foundation of China(No.U19B2031).
文摘A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.
文摘Noise interference critically impairs the stability and data accuracy of sensing systems.However,current suppression strategies fail to concurrently mitigate intrinsic system noise and extrinsic environmental noise.This study introduces a composite denoising approach to address this challenge.This method is based on the ameliorated ellipse fitting algorithm(AEFA)and adaptive successive variational mode decomposition(ASVMD).This algorithm employs AEFA to eliminate system noise tightly coupled with direct-current and alternating-current components in the interference signal,thereby obtaining a phase signal containing only environmental noise.The ASVMD technique adaptively extracts environmental noise components predominantly present in the phase signal.To achieve optimal decomposition results automatically,the permutation entropy criterion is employed to refine decomposition parameters.The correlation coefficient is utilized to differentiate effective components from noise components in the decomposition results.Experimental results indicate that the combined AEFA and ASVMD algorithm effectively suppresses both system and environmental noises.When applied to 50 Hz vibration signal processing,the proposed approach achieves a noise reduction of 17.81 dB and a phase resolution of 35.14μrad/√Hz.Given the excellent performance of the noise suppression,the proposed approach holds great application potential in high-performance interferometric sensing systems.
基金Project(61071162) supported by the National Natural Science Foundation of China
文摘In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional Retinex algorithms in image entropy.
基金supported by the Natural Science Foundation of China (U22A20214)。
文摘Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the rotor vibration in AMBs is to adopt a notch filter or adaptive filter in the AMB controller. However, these methods cannot obtain the precise amplitude and phase of the compensation current. Thus, they are not so effective in terms of suppressing the vibrations of the fundamental and other harmonic orders over the whole speed range. To improve the vibration suppression performance of AMBs,an adaptive filter based on Least Mean Square(LMS) is applied to extract the vibration signals from the rotor displacement signal. An Iterative Search Algorithm(ISA) is proposed in this paper to obtain the corresponding relationship between the compensation current and vibration signals. The ISA is responsible for searching the compensating amplitude and shifting phase online for the LMS filter, enabling the AMB controller to generate the corresponding compensation force for vibration suppression. The results of ISA are recorded to suppress vibration using the Look-Up Table(LUT) in variable speed range. Comprehensive simulations and experimental validations are carried out in fixed and variable speed range, and the results demonstrate that by employing the ISA, vibrations of the fundamental and other harmonic orders are suppressed effectively.
基金supported by the National Natural Science Foundation of China(Grant No.51809279)the Major National Science and Technology Program(Grant No.2016ZX05028-001-05)+1 种基金Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT14R58)the Fundamental Research Funds for the Central Universities,that is,the Opening Fund of National Engineering Laboratory of Offshore Geophysical and Exploration Equipment(Grant No.20CX02302A).
文摘Vortex induced vibration(VIV)is a challenge in ocean engineering.Several devices including fairings have been designed to suppress VIV.However,how to optimize the design of suppression devices is still a problem to be solved.In this paper,an optimization design methodology is presented based on data-driven models and genetic algorithm(GA).Data-driven models are introduced to substitute complex physics-based equations.GA is used to rapidly search for the optimal suppression device from all possible solutions.Taking fairings as example,VIV response database for different fairings is established based on parameterized models in which model sections of fairings are controlled by several control points and Bezier curves.Then a data-driven model,which can predict the VIV response of fairings with different sections accurately and efficiently,is trained through BP neural network.Finally,a comprehensive optimization method and process is proposed based on GA and the data-driven model.The proposed method is demonstrated by its application to a case.It turns out that the proposed method can perform the optimization design of fairings effectively.VIV can be reduced obviously through the optimization design.
文摘针对目前雷达干扰抑制决策智能化程度低的问题,提出了一种基于双深度优先经验回放和可变贪婪算法改进的双重竞争深度Q网络(double dueling deep Q network,D3QN)决策的雷达干扰抑制方法。首先对雷达目标回波和干扰混合信号进行特征提取;然后根据信号特征通过可变贪婪算法选择动作作用于干扰,并将动作前后的信号特征存储于双深度优先经验回放池后,经过学习决策出最优的干扰抑制策略;最后使用该策略抑制干扰后输出。实验结果表明,该方法有效改善了信号的脉压结果,显著提升了信号的信干噪比,相较于基于D3QN的传统干扰抑制方法,在策略准确率和收敛速度上分别提升了7.3%和8.7%。
文摘针对非整数阶盲移频干扰生成的欺骗干扰效果单一,假目标分布规律等问题,提出了一种基于阶梯波盲移频的线性调频(Linear Frequency Modulation,LFM)雷达干扰。设计了均匀阶梯波和非均匀阶梯波两种移频方法,推导了基于阶梯波盲移频的LFM雷达干扰数学模型。该技术引入阶梯波函数对系统阶数进行调制,在系统延时不变的情况下,可以实现精确位置的欺骗假目标群或固定范围内的随机假目标。通过调整阶梯波函数的各项参数,可以完成对假目标位置、幅度和数量的控制。仿真验证表明,采用均匀阶梯波函数可以实现特定位置的密集假目标,采用非均匀阶梯波函数能够在特定范围内生成随机的假目标。对调频斜率捷变的雷达有着较强的干扰能力,具有较好的工程应用意义。
文摘The rolling mill vibration not only seriously causes the strip thickness heterogeneity, but also damages the rolling mill equipment and its electrical components. Existing vibration suppression methods are passive and mainly tune mechanical, hydraulic, electrical and rolling process parameters. A new active vibration suppression method was thus proposed using the disturbance estimation and compensation algorithm. Firstly, the hydraulic-mechanical coupling model of the rolling mill vibration was established, and an active vibration suppressor was designed based on the extended state observer. Then, through the numerical simulation, it is found that the vibration energy is reduced by 35.3% using the vibration suppressor, and the vibration suppressor is valid when the vibration frequency is lower than 60 Hz Finally, the vibration suppressor was applied to the in-site manufacturing, and the expected vibration suppression was obtained. The method makes the produced steel strip have more uniform thickness and further significantly increases the finished product ratio.
文摘Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorithm had been studied by many researchers and applied in many fields. In the algorithm, how to select the suppressed rate is a key step. In this paper, we give a method to select the fixed suppressed rate by the structure of the data itself. The experimental results show that the proposed method is a suitable way to select the suppressed rate in suppressed fuzzy c-means clustering algorithm.
