Despite numerous research investigations to understand the influences of various structural parameters,to the authors'knowledge,no research has been the effect of different angles of incidence on stab response and...Despite numerous research investigations to understand the influences of various structural parameters,to the authors'knowledge,no research has been the effect of different angles of incidence on stab response and performance of different types of protective textiles.Three distinct structures of 3D woven textiles and 2D plain weave fabric made with similar high-performance fiber and areal density were designed and manufactured to be tested.Two samples,one composed of a single and the other of 4-panel layers,from each fabric type structure,were prepared,and tested against stabbing at[0○],[22.5○],and[45○]angle of incidence.A new stabbing experimental setup that entertained testing of the specimens at various angles of incidence was engineered and utilized.The stabbing bench is also equipped with magnetic sensors and a UK Home Office Scientific Development Branch(HOSDB)/P1/B sharpness engineered knives to measure the impact velocity and exerted impact energy respectively.A silicon compound was utilized to imprint the Back Face Signature(BFS)on the backing material after every specimen test.Each silicon print was then scanned,digitized,and precisely measured to evaluate the stab response and performance of the specimen based on different performance variables,including Depth of Trauma(DOT),Depth of Penetration(DOP),and Length of Penetration(LOP).Besides,the post-impact surface failure modes of the fabrics were also measured using Image software and analyzed at the microscale level.The results show stab angle of incidence greatly influences the stab response and performance of protective textiles.The outcome of the study could provide not only valuable insights into understanding the stab response and capabilities of protective textiles under different angle of incidence,but also provide valuable information for protective textile manufacturer,armor developer and stab testing and standardizing organizations to consider the angle of incidence while developing,testing,optimizing,and using protective textiles in various applications.展开更多
In this paper,we introduce an incident angle based fusion method for radar and infrared sensors to improve the recognition rate of complex targets under half space scenarios,e.g.,vehicles on the ground in this paper.F...In this paper,we introduce an incident angle based fusion method for radar and infrared sensors to improve the recognition rate of complex targets under half space scenarios,e.g.,vehicles on the ground in this paper.For radar sensors,convolutional operation is introduced into the autoencoder,a“winner-take-all(WTA)”convolutional autoencoder(CAE)is used to improve the recognition rate of the radar high resolution range profile(HRRP).Moreover,different from the free space,the HRRP in half space is more complex.In order to get closer to the real situation,the half space HRRP is simulated as the dataset.The recognition rate has a growth more than 7%com-pared with the traditional CAE or denoised sparse autoencoder(DSAE).For infrared sensor,a convolutional neural network(CNN)is used for infrared image recognition.Finally,we com-bine the two results with the Dempster-Shafer(D-S)evidence theory,and the discounting operation is introduced in the fusion to improve the recognition rate.The recognition rate after fusion has a growth more than 7%compared with a single sensor.After the discounting operation,the accuracy rate has been improved by 1.5%,which validates the effectiveness of the proposed method.展开更多
文摘Despite numerous research investigations to understand the influences of various structural parameters,to the authors'knowledge,no research has been the effect of different angles of incidence on stab response and performance of different types of protective textiles.Three distinct structures of 3D woven textiles and 2D plain weave fabric made with similar high-performance fiber and areal density were designed and manufactured to be tested.Two samples,one composed of a single and the other of 4-panel layers,from each fabric type structure,were prepared,and tested against stabbing at[0○],[22.5○],and[45○]angle of incidence.A new stabbing experimental setup that entertained testing of the specimens at various angles of incidence was engineered and utilized.The stabbing bench is also equipped with magnetic sensors and a UK Home Office Scientific Development Branch(HOSDB)/P1/B sharpness engineered knives to measure the impact velocity and exerted impact energy respectively.A silicon compound was utilized to imprint the Back Face Signature(BFS)on the backing material after every specimen test.Each silicon print was then scanned,digitized,and precisely measured to evaluate the stab response and performance of the specimen based on different performance variables,including Depth of Trauma(DOT),Depth of Penetration(DOP),and Length of Penetration(LOP).Besides,the post-impact surface failure modes of the fabrics were also measured using Image software and analyzed at the microscale level.The results show stab angle of incidence greatly influences the stab response and performance of protective textiles.The outcome of the study could provide not only valuable insights into understanding the stab response and capabilities of protective textiles under different angle of incidence,but also provide valuable information for protective textile manufacturer,armor developer and stab testing and standardizing organizations to consider the angle of incidence while developing,testing,optimizing,and using protective textiles in various applications.
基金supported by the National Natural Science Foundation of China(61571022,61971022).
文摘In this paper,we introduce an incident angle based fusion method for radar and infrared sensors to improve the recognition rate of complex targets under half space scenarios,e.g.,vehicles on the ground in this paper.For radar sensors,convolutional operation is introduced into the autoencoder,a“winner-take-all(WTA)”convolutional autoencoder(CAE)is used to improve the recognition rate of the radar high resolution range profile(HRRP).Moreover,different from the free space,the HRRP in half space is more complex.In order to get closer to the real situation,the half space HRRP is simulated as the dataset.The recognition rate has a growth more than 7%com-pared with the traditional CAE or denoised sparse autoencoder(DSAE).For infrared sensor,a convolutional neural network(CNN)is used for infrared image recognition.Finally,we com-bine the two results with the Dempster-Shafer(D-S)evidence theory,and the discounting operation is introduced in the fusion to improve the recognition rate.The recognition rate after fusion has a growth more than 7%compared with a single sensor.After the discounting operation,the accuracy rate has been improved by 1.5%,which validates the effectiveness of the proposed method.
