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The superior ballistic performance of highly stretchable and flexible double-face knitted fabrics(DFKF):An experimental investigation
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作者 Yi Zhou Xiangpeng Xin +3 位作者 Yang Li Yang Zhou Rui Zhang Lizhi Xu 《Defence Technology(防务技术)》 2025年第3期119-136,共18页
When the protective and protected systems are detached,the former can be allowed to absorb the kinetic energy of the impacting projectile through large deformation without considering the back face signature of the la... When the protective and protected systems are detached,the former can be allowed to absorb the kinetic energy of the impacting projectile through large deformation without considering the back face signature of the latter.This paper presents a novel double-face knitted fabric(DFKF)designed for this very impacting scenario.Shooting tests equipped with high-speed camera were used to characterize the ballistic performance with the impact velocities ranging from 100 m/s to 450 m/s.The results showed that the ballistic limits(V_(bl))of DFKF are approximately triple and double that of its counterpart UD and plain fabrics,respectively.For mass-normalized metrics,the specific energy absorption(SEA)is 250%and 350%greater than the UD and plain fabrics at their corresponding V_(bl)s.The quasi-static tests showed that the DFKF displayed greater resilience,crease recovery properties,and flexibility,which also made it an especially better candidate than UD and plain weaves for the design of umbrella surface cloth.It was also found that DFKF is dependent on yarn count and the incorporation of spandex.A prototype anti-ballistic umbrella is manufactured using DFKF made of 200D multi-filament yarn.The ballistic performance is also sensitive to the impact site when the umbrella is subjected to impact. 展开更多
关键词 dfkf Ballistic performance SEA RESILIENCE Energy absorption Anti-ballistic umbrella
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双重遗忘卡尔曼滤波PMLSM无位置传感控制研究 被引量:5
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作者 朱军 李香君 +2 位作者 付融冰 吴宇航 田淼 《系统仿真学报》 CAS CSCD 北大核心 2018年第2期672-678,共7页
针对EKF估计PMLSM位置存在模型不精确、噪声统计特性不确定时估计精度不高,且有可能导致滤波发散的问题,提出一种双重遗忘卡尔曼滤波法,它是在EKF的基础上引入自适应渐消因子,实现第一重遗忘,引入Sage-Husa自适应滤波法,实现第二重遗忘... 针对EKF估计PMLSM位置存在模型不精确、噪声统计特性不确定时估计精度不高,且有可能导致滤波发散的问题,提出一种双重遗忘卡尔曼滤波法,它是在EKF的基础上引入自适应渐消因子,实现第一重遗忘,引入Sage-Husa自适应滤波法,实现第二重遗忘。实验表明:该方法不论是同步速度还是负载突变,均按正弦规律递减,负载突变前、后速度稳定误差最大值分别为0.469%、0.943%,最终将稳定在0.167%附近,跟踪效果随仿真时间的加长而更好。 展开更多
关键词 PMLSM 卡尔曼滤波 自适应渐消因子 Sage-Husa自适应滤波 双重遗忘卡尔曼滤波
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