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Design of twodimensional digital filters using neural networks

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Journal of Systems Engineering and Electronics 2005年第4期16卷 767-771页

A new approach for the design of two-dimensional （2-D） linear phase FIR digital filters based on a new neural networks algorithm （NNA） is provided. A compact expression for the transfer function of a 2-D linear phase FIR filter is derived based on its frequency response characteristic, and the NNA, based on minimizing the square-error in the frequency-domain, is established according to the compact expression. To illustrate the stability of the NNA, the convergence theorem is presented and proved. Design examples are also given, and the results show that the ripple is considerably small in passband and stopband, and the NNA-based method is of powerful stability and requires quite little amount of computations.

关键词： 2-D linear-phase FIR digital filters neural network convergence theorem stability.

结合数据驱动与物理模型的主动配电网双时间尺度电压协调优化控制

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电工技术学报 2024年第5期39卷 1327-1339页

作者：张剑崔明建何怡刚合肥工业大学电气与自动化工程学院合肥230009 天津大学电气自动化与信息工程学院天津300072 武汉大学电气与自动化学院武汉430072

高比例电动汽车、分布式风电、光伏接入配电网,导致电压频繁地剧烈波动。传统调压设备与逆变器动作速度差异巨大,如何协调是难点问题。该文结合数据驱动与物理建模方法,提出一种配电网双时间尺度电压协调优化控制策略。针对短时间尺度(... 详细信息

高比例电动汽车、分布式风电、光伏接入配电网,导致电压频繁地剧烈波动。传统调压设备与逆变器动作速度差异巨大,如何协调是难点问题。该文结合数据驱动与物理建模方法,提出一种配电网双时间尺度电压协调优化控制策略。针对短时间尺度(min级)电压波动,以静止无功补偿器、分布式电源无功功率为决策变量,以电压二次方偏差最小为目标函数,针对平衡与不平衡配电网,基于支路潮流方程,计及物理约束构建了二次规划模型。针对长时间尺度(h级)电压波动,以电压调节器匝比、可投切电容电抗器挡位、储能系统充放电功率为动作,当前时段配电网节点功率为状态,节点电压二次方偏差为代价,构建了马尔可夫决策过程。为克服连续-离散动作空间维数灾,提出了一种基于松弛-预报-校正的深度确定性策略梯度强化学习求解算法。最后,采用IEEE 33节点平衡与123节点不平衡配电网验证了所提出方法的有效性。

关键词：智能配电网电压控制深度强化学习二次规划双时间尺度

Steganography based on wavelet transform and modulus function

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Journal of Systems Engineering and Electronics 2007年第3期18卷 628-632页

作者： Kang Zhiwei Liu Jing he yigang School of Computer and Communication Hunan Univ. Changsha 410082 P. R. China School of Electrical and Information Engineering Hunan Univ. Changsha 410082 P. R. China

In order to provide larger capacity of the hidden secret data while maintaining a good visual quality of stego-image, in accordance with the visual property that human eyes are less sensitive to strong texture, a novel steganographic method based on wavelet and modulus function is presented. First, an image is divided into blocks of prescribed size, and every block is decomposed into one-level wavelet. Then, the capacity of the hidden secret data is decided with the number of wavelet coefficients of larger magnitude. Finally, secret information is embedded by steganography based on modulus function. From the experimental results, the proposed method hides much more information and maintains a good visual quality of stego-image. Besides, the embedded data can be extracted from the stego-image without referencing the original image.

关键词： steganography capacity wavelet transform modulus function HVS.

An Adaptive SVD Method for Solving the Pass-Region Problem in S-Transform Time-Frequency Filters

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Chinese Journal of Electronics 2015年第1期24卷 115-123页

作者： YIN Baiqiang he yigang LI Bing ZUO Lei YUAN Lifen School of Electrical and Automation Engineering Hefei University of Technology

S-transform(ST) is an excellent tool for time-frequency filter. There are two factors that influence filtering performance: Inverse s-transform(IST) algorithms and the pass-regions in time-frequency domain. A novel matrix IST algorithm is derived and an adaptive Singular value decomposition(SVD) method for solving the pass-region problem is proposed. The former can avoid reconstructing errors in time-frequency filtering; the latter is effective to distinguish the pass-region of signal from noise.Filter can be realized by removing the smaller singular values and keeping the larger singular values. An additive noise perturbation model is built in ST time-frequency domain and the effective rank of noise perturbation model based on matrix IST is analyzed. Simulation results indicate that the proposed SVD method can provide higher precision than the existing ones at low signal-to-noise ratio and does not need to compute the noise statistics property.Illustrative examples verify the effectiveness of proposed method.

关键词： S-transform Matrix inverse S-transform Time frequency filter Singular value decomposition.

部分分布式电源提供辅助服务的主动配电网快速鲁棒优化

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高电压技术 2024年第5期50卷 2107-2116,I0030-I0032页

作者：张剑崔明建何怡刚合肥工业大学电气与自动化工程学院合肥230009 智能电网教育部重点实验室(天津大学) 天津300072 武汉大学电气与自动化学院武汉430072

经逆变器接入配电网的分布式电源提供有功与无功辅助服务是确保配电网安全经济运行的重要手段。该文同时计及了储能系统、可投切电容电抗器、有载调压变压器分接头、静止无功补偿器调节能力,以储能与网络损耗及弃风弃光最小为目标函数,... 详细信息

经逆变器接入配电网的分布式电源提供有功与无功辅助服务是确保配电网安全经济运行的重要手段。该文同时计及了储能系统、可投切电容电抗器、有载调压变压器分接头、静止无功补偿器调节能力,以储能与网络损耗及弃风弃光最小为目标函数,计及运行约束,基于支路潮流方程构建了部分分布式电源提供辅助服务的多时段二阶段混合整数二阶锥鲁棒优化模型,提出了一种新颖的基于割平面的主、次问题二阶段直接交替迭代求解方法。不同于现有列与约束生成(columns and constraints generation,CCG)算法,该方法求解主问题时无需增加新的变量与约束条件,求解次问题时,只需针对每个时段进行求解,因此极大降低了求解复杂度与计算机内存。若求解结果不满足二阶锥精确凸松弛条件,则构建二阶段混合整数序列二阶锥鲁棒优化模型,依然能够快速求解,且可恢复出原问题的精确解。最后,采用2个仿真实例验证了所提出方法的性能。IEEE 123节点配电网的仿真结果表明,该方法计算速度是CCG算法的12~22倍。该方法可为含高比例间歇性分布式电源配电网鲁棒优化运行提供实时快速分析与求解工具,提高新能源就地消纳能力。

关键词：主动配电网分布式电源辅助服务 SOCP 鲁棒优化

基于自适应滑模观测器的中点钳位型三电平并网逆变器开关管和电流传感器故障诊断

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电工技术学报 2024年第13期39卷 4066-4078页

作者：许水清许晓凡何怡刚柴毅合肥工业大学电气与自动化工程学院合肥230009 武汉大学电气与自动化学院武汉430072 输变电装备技术全国重点实验室(重庆大学) 重庆400044

为提高中点钳位型三电平(3L-NPC)并网逆变器故障诊断的准确性和可靠性,针对其开关管开路故障和电流传感器故障,提出一种基于自适应滑模观测器的开关管开路故障和电流传感器故障同时诊断方法。该方法首先针对3L-NPC并网逆变器,设计一种... 详细信息

为提高中点钳位型三电平(3L-NPC)并网逆变器故障诊断的准确性和可靠性,针对其开关管开路故障和电流传感器故障,提出一种基于自适应滑模观测器的开关管开路故障和电流传感器故障同时诊断方法。该方法首先针对3L-NPC并网逆变器,设计一种收敛速度快且能显著抑制抖振的自适应滑模观测器来精确估计正常状态下的三相电流值;其次,利用实际电流和估计电流设计了故障检测变量;同时,利用实际三相电流之和以及估计三相电流之和来区分开关管故障和电流传感器故障;在此基础上,构造开关管故障定位变量和电流传感器故障识别变量,实现开关管开路故障的准确定位以及电流传感器故障类型的快速识别。实验结果验证了该文所提诊断算法的有效性和鲁棒性。

关键词：中点钳位型三电平(3L-NPC)并网逆变器开关管开路故障电流传感器故障自适应滑模观测器

Multi-period Two-stage Robust Optimization of Radial Distribution System with Cables Considering Time-of-use Price

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Journal of Modern Power Systems and Clean Energy 2023年第1期11卷 312-323页

作者： Jian Zhang Mingjian Cui yigang he Fangxing Li School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China University of Tennessee KnoxvilleTN 37996USA School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

In the existing multi-period robust optimization methods for the optimal power flow in radial distribution systems,the capability of distributed generators(DGs)to regulate the reactive power,the operation costs of the regulation equipment,and the current of the shunt capacitor of the cables are not considered.In this paper,a multi-period two-stage robust scheduling strategy that aims to minimize the total cost of the power supply is developed.This strategy considers the time-ofuse price,the capability of the DGs to regulate the active and reactive power,the action costs of the regulation equipment,and the current of the shunt capacitors of the cables in a radial distribution system.Furthermore,the numbers of variables and constraints in the first-stage model remain constant during the iteration to enhance the computation efficiency.To solve the second-stage model,only the model of each period needs to be solved.Then,their objective values are accumulated,revealing that the computation rate using the proposed method is much higher than that of existing methods.The effectiveness of the proposed method is validated by actual 4-bus,IEEE 33-bus,and PG 69-bus distribution systems.

关键词： Distribution system robust optimization mixed-integer second-order cone programming cost of regulation equipment coordinated optimization of active and reactive power

针对大功率三电平逆变器的调幅调相小波调制策略

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武汉大学学报（工学版） 2024年第6期57卷 717-727页

作者：闫光磊张慧葛远喆何怡刚靳展翔蔚腾辉武汉大学电气与自动化学院湖北武汉430072

传统小波调制策略应用于逆变器控制时存在无法准确调节输出电压相位的问题。在介绍传统小波调制策略原理基础上首次提出了改进的调幅调相小波调制策略,阐述了其基本工作原理与流程,采用2种不同的小波尺度因子取值方式解决了逆变器输出... 详细信息

传统小波调制策略应用于逆变器控制时存在无法准确调节输出电压相位的问题。在介绍传统小波调制策略原理基础上首次提出了改进的调幅调相小波调制策略,阐述了其基本工作原理与流程,采用2种不同的小波尺度因子取值方式解决了逆变器输出电压相位的调节问题,进一步讨论了调幅调相小波调制策略对谐波控制的可行性。在700 Hz功率器件开关频率下,将提出的调幅调相小波调制策略与传统小波调制、载波反相层叠调制、断续脉宽调制等几种策略分别应用于三电平中点箝位型逆变电路,进行了输出相电压与中点电位平衡两方面的性能对比。结果表明:尺度因子取非整数方式时,所提出的调幅调相小波调制策略在逆变器输出电压低次谐波抑制和准确控制方面有较好效果;尺度因子取整数方式时,逆变器有较高的基波电压幅值,直流侧中点电位波动同比最小。

关键词：小波调制调幅调相尺度因子三电平逆变器相电压中点电位平衡

A novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder for small negative samples

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High Voltage 2022年第5期7卷 925-935页

作者： Fangming Deng Wei Luo Baoquan Wei Yong Zuo Han Zeng yigang he State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong UniversityNanchangChina School of Electrical and Automation Engineering East China Jiaotong UniversityNanchangChina School of Electrical Engineering and Automation Wuhan UniversityWuhanChina

This paper presents a novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder(DCAE)for small negative samples.The proposed DCAE scheme combines the advantages of supervised learning and unsupervised learning.In order to reduce the high cost of training Deep Neural Networks,this paper pre-trained the Convolutional Neural Networks(CNN)through open labelled datasets.Through transferring learning,the encoder part of the traditional Convolutional Auto-Encoder was replaced by the first three layers of the CNN,and a small number of defect samples were used to fine-tune the parameters.A threshold discrimination scheme was designed to evaluate the model detection,realising the self-explosion detection of insulator by judging the residual result and abnormal score.The experimental results show that compared with the existing insulator self-explosion detection schemes,the proposed scheme can reduce the model training time by up to 40%,and the recognition accuracy can reach 97%.Moreover,this model does not need a large number of insulator labelled data and is especially suitable for small negative sample application.

关键词： scheme insulator defect