具有模块化多电平结构的串联开关直流变压器(direct current transformer, DCT)在使用传统单移相控制时,存在中压侧全桥换流时阀串支路产生电流尖峰的问题,器件承受额外的电流应力。基于该新型DCT的工作原理与电流波形,提出一种基于中...具有模块化多电平结构的串联开关直流变压器(direct current transformer, DCT)在使用传统单移相控制时,存在中压侧全桥换流时阀串支路产生电流尖峰的问题,器件承受额外的电流应力。基于该新型DCT的工作原理与电流波形,提出一种基于中压侧全桥换流移相的阀串支路电流优化调制方法。文中对阀串支路的电流应力进行详细分析,结合电路可靠工作移相角范围,确定中压侧全桥换流移相角最优值的计算方法,从而确立优化控制策略。该优化控制策略独立于原有的功率控制环路运行,不改变DCT功率传输状态,不影响功率的调节控制,易于投入实际应用。仿真与样机实验的结果验证了该优化控制策略降低电流应力的有效性,同时样机实验结果显示效率得到提升。综合原理分析与效果验证可知,该优化控制策略对设备的安全运行与器件选型具有借鉴意义。展开更多
在车辆起步过程中,发动机输出转矩波动会导致离合器接合不稳定,从而影响整车动力传动系统的平顺性。双质量飞轮(dual mass flywheel,DMF)可减小发动机转矩波动对离合器及整车动力传动系统的影响。针对起步过程离合器接合不稳定影响整车...在车辆起步过程中,发动机输出转矩波动会导致离合器接合不稳定,从而影响整车动力传动系统的平顺性。双质量飞轮(dual mass flywheel,DMF)可减小发动机转矩波动对离合器及整车动力传动系统的影响。针对起步过程离合器接合不稳定影响整车平顺性的问题,以双离合器自动变速器(dual clutch automatic transmission,DCT)车辆为研究对象,研究了DMF的刚度、阻尼和初级与次级飞轮惯量比对DCT车辆起步过程离合器接合稳定性的影响,并建立了以离合器黏滑比和整车冲击度为目标函数的多目标优化模型,利用遗传算法对模型进行优化,得到了使离合器接合稳定性提高且整车冲击度明显降低的DMF最优参数组合。展开更多
Medical images are a critical component of the diagnostic process for clinicians.Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis,they must be encrypted due to the c...Medical images are a critical component of the diagnostic process for clinicians.Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis,they must be encrypted due to the characteristics of digital storage and information leakage associated with medical images.Traditional watermark embedding algorithm embeds the watermark information into the medical image,which reduces the quality of the medical image and affects the physicians’judgment of patient diagnosis.In addition,watermarks in this method have weak robustness under high-intensity geometric attacks when the medical image is attacked and the watermarks are destroyed.This paper proposes a novel watermarking algorithm using the convolutional neural networks(CNN)Inception V3 and the discrete cosine transform(DCT)to address above mentioned problems.First,the medical image is input into the Inception V3 network,which has been structured by adjusting parameters,such as the size of the convolution kernels and the typical architecture of the convolution modules.Second,the coefficients extracted from the fully connected layer of the network are transformed by DCT to obtain the feature vector of the medical image.At last,the watermarks are encrypted using the logistic map system and hash function,and the keys are stored by a third party.The encrypted watermarks and the original image features are performed logical operations to realize the embedding of zero-watermark.In the experimental section,multiple watermarking schemes using three different types of watermarks were implemented to verify the effectiveness of the three proposed algorithms.Our NC values for all the images are more than 90%accurate which shows the robustness of the algorithm.Extensive experimental results demonstrate the robustness under both conventional and high-intensity geometric attacks of the proposed algorithm.展开更多
文摘具有模块化多电平结构的串联开关直流变压器(direct current transformer, DCT)在使用传统单移相控制时,存在中压侧全桥换流时阀串支路产生电流尖峰的问题,器件承受额外的电流应力。基于该新型DCT的工作原理与电流波形,提出一种基于中压侧全桥换流移相的阀串支路电流优化调制方法。文中对阀串支路的电流应力进行详细分析,结合电路可靠工作移相角范围,确定中压侧全桥换流移相角最优值的计算方法,从而确立优化控制策略。该优化控制策略独立于原有的功率控制环路运行,不改变DCT功率传输状态,不影响功率的调节控制,易于投入实际应用。仿真与样机实验的结果验证了该优化控制策略降低电流应力的有效性,同时样机实验结果显示效率得到提升。综合原理分析与效果验证可知,该优化控制策略对设备的安全运行与器件选型具有借鉴意义。
基金supported in part by Key Research Project of Hainan Province under Grant ZDYF2021SHFZ093the Natural Science Foundation of China under Grants 62063004 and 62162022+2 种基金the Hainan Provincial Natural Science Foundation of China under Grants 2019RC018,521QN206 and 619QN249the Major Scientific Project of Zhejiang Lab 2020ND8AD01the Scientific Research Foundation for Hainan University(No.KYQD(ZR)-21013).
文摘Medical images are a critical component of the diagnostic process for clinicians.Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis,they must be encrypted due to the characteristics of digital storage and information leakage associated with medical images.Traditional watermark embedding algorithm embeds the watermark information into the medical image,which reduces the quality of the medical image and affects the physicians’judgment of patient diagnosis.In addition,watermarks in this method have weak robustness under high-intensity geometric attacks when the medical image is attacked and the watermarks are destroyed.This paper proposes a novel watermarking algorithm using the convolutional neural networks(CNN)Inception V3 and the discrete cosine transform(DCT)to address above mentioned problems.First,the medical image is input into the Inception V3 network,which has been structured by adjusting parameters,such as the size of the convolution kernels and the typical architecture of the convolution modules.Second,the coefficients extracted from the fully connected layer of the network are transformed by DCT to obtain the feature vector of the medical image.At last,the watermarks are encrypted using the logistic map system and hash function,and the keys are stored by a third party.The encrypted watermarks and the original image features are performed logical operations to realize the embedding of zero-watermark.In the experimental section,multiple watermarking schemes using three different types of watermarks were implemented to verify the effectiveness of the three proposed algorithms.Our NC values for all the images are more than 90%accurate which shows the robustness of the algorithm.Extensive experimental results demonstrate the robustness under both conventional and high-intensity geometric attacks of the proposed algorithm.
