无线供电通信网络(Wireless-powered Communication Network,WPCN)不仅可以实现远程无线充电而且能够提供无线通信服务,因此受到了学术界和工业界的广泛关注。然而,低效率的能量收集和信息传输会限制WPCN的性能,并且在WPCN中的双重远近...无线供电通信网络(Wireless-powered Communication Network,WPCN)不仅可以实现远程无线充电而且能够提供无线通信服务,因此受到了学术界和工业界的广泛关注。然而,低效率的能量收集和信息传输会限制WPCN的性能,并且在WPCN中的双重远近效应会导致物联网设备收集的能量与消耗的能量之间的不平衡。为了解决这些问题,提出基于能量回收的主动智能反射面(Intelligent Reflecting Surface,IRS)辅助WPCN波束成形算法,其中物联网设备既能从功率站端收集能量,还能从其他物联网设备的上行信息传输中回收能量。考虑能量收集、吞吐量、时间分配,以及功率站和主动IRS的最大功率等约束,基于能量回收机制,建立了系统总吞吐量最大化的资源分配模型;然后,提出一种基于内层近似和双线性变换的交替优化算法进行求解。仿真结果表明,在相应的参数配置下,能量回收机制的应用能够提升约8.13%的吞吐量,而主动IRS的应用能够提升约61.1%的吞吐量。展开更多
The blades on the plane are one of the most important parts of the engine,in the course of service,due to high temperature,strong vibration and great centrifugal force and so on.The using environment is very bad,so it...The blades on the plane are one of the most important parts of the engine,in the course of service,due to high temperature,strong vibration and great centrifugal force and so on.The using environment is very bad,so it is easy to produce fatigue cracks in the welding site and the near surface of the root,which will seriously affect the blade of the work intensity and fatigue life,and even the safety of aircraft structure,causing a huge security risk.Therefore,it must be tested.In order to solve the problem of the rapid detection of aircraft engine in situ cracks,and gett the rela-tionship between feature information and detect depth,the laboratory experimental platform was built,laser was used to excite laser ultrasonic signals on a range of aviation aluminum plates with different depth defects,the collected sig-nal was processed by wavelet de-noising,and the band energy distribution of the reflected echo signal was studied by using wavelet packet.The results show that the energy of reflected echo signal is mainly concentrated in the S80~So7 band.When the depth of defect is 0.2 mm to 0.4 mm,the energy is mainly concentrated in the adjacent bands.When the depth of defect is 0.5 mm to 0.7 mm,the energy is mainly concentrated in the two bands.This method provides a way to quantify surface micro-defects by ultrasonic signals,which will lay a foundation for the future analysis of crack depth from band energy.In order to avoid the interference of other irregular cracks,the cracks of the aviation aluminum parts are used as ar-tificial way for producing.The overall size of the specimen is 200 mmx80 mmx100 mm,the width of the defect is 0.15 mm,the range of the defect depth is 0.2 mm~0.7 mm,step size is 0.1 mm,and the total number of the specimen is six.After the experimental data is proposed,choosing the reflected echo signal for analysis,performing wavelet packet transform,the decomposition layer is 8.The percentage in the Sao~Sa7band is 89.77%、91.82%、91.41%、90.94%、90.19%、and 87.86%.The result shows that most of the energy is concentrated in the first eight bands.Therefore,the paper selects the first eight bands for analysis.In order to analyze the distribution characteristics of the different depth defect and the band energy,the energy dis-tribution of the first four bands of the defect depth of 0.2 mm to 0.4 mm is plotted in Fig,according to the spectrum,getting the center frequency were 3.14 MHz,2.58 MHz,2.17 MHz.These frequencies are located in the S83,S82,S82 band,respectively,which are the largest energy band,but the energy distribution in the adjacent segment Ss:also ac-counts for a larger proportion.When the depth of the defect increases from 0.2 mm to 0.4 mm,the center frequency decreases gradually,and the sum of the energy of the center frequency band and the adjacent higher energy band in-creases gradually.展开更多
文摘无线供电通信网络(Wireless-powered Communication Network,WPCN)不仅可以实现远程无线充电而且能够提供无线通信服务,因此受到了学术界和工业界的广泛关注。然而,低效率的能量收集和信息传输会限制WPCN的性能,并且在WPCN中的双重远近效应会导致物联网设备收集的能量与消耗的能量之间的不平衡。为了解决这些问题,提出基于能量回收的主动智能反射面(Intelligent Reflecting Surface,IRS)辅助WPCN波束成形算法,其中物联网设备既能从功率站端收集能量,还能从其他物联网设备的上行信息传输中回收能量。考虑能量收集、吞吐量、时间分配,以及功率站和主动IRS的最大功率等约束,基于能量回收机制,建立了系统总吞吐量最大化的资源分配模型;然后,提出一种基于内层近似和双线性变换的交替优化算法进行求解。仿真结果表明,在相应的参数配置下,能量回收机制的应用能够提升约8.13%的吞吐量,而主动IRS的应用能够提升约61.1%的吞吐量。
文摘The blades on the plane are one of the most important parts of the engine,in the course of service,due to high temperature,strong vibration and great centrifugal force and so on.The using environment is very bad,so it is easy to produce fatigue cracks in the welding site and the near surface of the root,which will seriously affect the blade of the work intensity and fatigue life,and even the safety of aircraft structure,causing a huge security risk.Therefore,it must be tested.In order to solve the problem of the rapid detection of aircraft engine in situ cracks,and gett the rela-tionship between feature information and detect depth,the laboratory experimental platform was built,laser was used to excite laser ultrasonic signals on a range of aviation aluminum plates with different depth defects,the collected sig-nal was processed by wavelet de-noising,and the band energy distribution of the reflected echo signal was studied by using wavelet packet.The results show that the energy of reflected echo signal is mainly concentrated in the S80~So7 band.When the depth of defect is 0.2 mm to 0.4 mm,the energy is mainly concentrated in the adjacent bands.When the depth of defect is 0.5 mm to 0.7 mm,the energy is mainly concentrated in the two bands.This method provides a way to quantify surface micro-defects by ultrasonic signals,which will lay a foundation for the future analysis of crack depth from band energy.In order to avoid the interference of other irregular cracks,the cracks of the aviation aluminum parts are used as ar-tificial way for producing.The overall size of the specimen is 200 mmx80 mmx100 mm,the width of the defect is 0.15 mm,the range of the defect depth is 0.2 mm~0.7 mm,step size is 0.1 mm,and the total number of the specimen is six.After the experimental data is proposed,choosing the reflected echo signal for analysis,performing wavelet packet transform,the decomposition layer is 8.The percentage in the Sao~Sa7band is 89.77%、91.82%、91.41%、90.94%、90.19%、and 87.86%.The result shows that most of the energy is concentrated in the first eight bands.Therefore,the paper selects the first eight bands for analysis.In order to analyze the distribution characteristics of the different depth defect and the band energy,the energy dis-tribution of the first four bands of the defect depth of 0.2 mm to 0.4 mm is plotted in Fig,according to the spectrum,getting the center frequency were 3.14 MHz,2.58 MHz,2.17 MHz.These frequencies are located in the S83,S82,S82 band,respectively,which are the largest energy band,but the energy distribution in the adjacent segment Ss:also ac-counts for a larger proportion.When the depth of the defect increases from 0.2 mm to 0.4 mm,the center frequency decreases gradually,and the sum of the energy of the center frequency band and the adjacent higher energy band in-creases gradually.
