Signal-to-noise ratio(SNR)fluctuations signiflcantly affect spectrum sensing performance in wireless communications.Traditional convolutional neural network(CNN)exhibits limited feature extraction capabilities and ine...Signal-to-noise ratio(SNR)fluctuations signiflcantly affect spectrum sensing performance in wireless communications.Traditional convolutional neural network(CNN)exhibits limited feature extraction capabilities and inefficient feature utilization at low SNR levels,leading to suboptimal spectrum sensing performance.This paper proposes a spectrum sensing method based on a multi-scale feature fusion network(MSFFNet)to address this issue.First,the proposed method employs a multi-scale feature extraction block(MSFEB)to capture multi-scale information from the input data comprehensively.Next,an adaptive feature screening strategy(AFSS)highlights key features while suppressing redundant information.Finally,a multi-level feature fusion mechanism(MLFFM)optimizes and integrates features across scales and levels,enhancing spectrum sensing performance.Simulation results demonstrate that compared to other methods,the proposed approach achieves superior performance in lowSNR communication scenarios.At an SNR of-14 d B,the detection probability Pd reaches 0.936,while the false alarm probability Pfa is only 0.1.Furthermore,this paper constructs a multi-level mixed-SNR dataset to simulate real communication environments and enhance the robustness of spectrum sensing.展开更多
The aerodynamic performance test rig for aircraft engine compressors serves as a core ground test facility for conducting aerodynamic design verification,performance evaluation,stability analysis,and flow mechanism re...The aerodynamic performance test rig for aircraft engine compressors serves as a core ground test facility for conducting aerodynamic design verification,performance evaluation,stability analysis,and flow mechanism research on compressors.The accuracy of its flow field measurement results directly determines the reliability of key conclusions,such as compressor characteristic curves,adiabatic efficiency,stability boundaries,and interstage matching relationships.In the context of developing a new generation of compressors with high load,high efficiency,and wide stability margins,traditional methods relying on empirical debugging and local calibration struggle to meet the requirements for high-precision aerodynamic testing.This paper takes an axial-flow compressor aerodynamic performance test rig as the research object,systematically elaborates on the typical process and mainstream methods of flow field calibration,analyzes the primary sources of error affecting measurement accuracy,and proposes an integrated strategy for improving accuracy from aspects such as probe calibration,flow rate calibration,flow field uniformity correction,installation and environmental compensation,and traceability of measurements.Furthermore,it provides a comparative analysis of calibration effects based on engineering test data.The research results indicate that through systematic flow field calibration and multi-dimensional error correction,the uncertainty in flow rate measurement can be reduced to better than±0.3%,with significant improvements in the measurement accuracy of total pressure and flow angle.The flow field non-uniformity is controlled within 3%,providing reliable data support for ground testing of high-performance compressors.展开更多
Air transportation systems are often subject to failures or attacks induced by unexpected abominable weather or temporal airspace occupation, while complex networks have been springing up as a convenient yet efficient...Air transportation systems are often subject to failures or attacks induced by unexpected abominable weather or temporal airspace occupation, while complex networks have been springing up as a convenient yet efficient tool to represent and analyze various realistic complex systems such as realistic airline system. In terms of Chinese airline network formed during the spring festival timespan, structural empirical research and invulnerability simulation analysis against various deliberate attack strategies were made using complex network theory, where nodes and edges denotes domestic airports and direct flights between them respectively. The analysis results indicate: The presented airline network is a small net-work with scale-free characteristics, and correlation shows remarkable hierarchical structure and obvious assortative characteristics;The network shows obvious invulnerability under deliberate node attack, while shows partly robustness under edge attack even with obvious attack effects against various attack strategies.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.62066016 and 62161012)the Natural Science Foundation of Hunan Province of China(No.2024JJ7395)+1 种基金the Scientific Research Project of Education Department of Hunan Province of China(No.22B0549)the Scientific Research Project of Jishou University(No.Jdy24049)。
文摘Signal-to-noise ratio(SNR)fluctuations signiflcantly affect spectrum sensing performance in wireless communications.Traditional convolutional neural network(CNN)exhibits limited feature extraction capabilities and inefficient feature utilization at low SNR levels,leading to suboptimal spectrum sensing performance.This paper proposes a spectrum sensing method based on a multi-scale feature fusion network(MSFFNet)to address this issue.First,the proposed method employs a multi-scale feature extraction block(MSFEB)to capture multi-scale information from the input data comprehensively.Next,an adaptive feature screening strategy(AFSS)highlights key features while suppressing redundant information.Finally,a multi-level feature fusion mechanism(MLFFM)optimizes and integrates features across scales and levels,enhancing spectrum sensing performance.Simulation results demonstrate that compared to other methods,the proposed approach achieves superior performance in lowSNR communication scenarios.At an SNR of-14 d B,the detection probability Pd reaches 0.936,while the false alarm probability Pfa is only 0.1.Furthermore,this paper constructs a multi-level mixed-SNR dataset to simulate real communication environments and enhance the robustness of spectrum sensing.
基金supported by the Natural Science Foundation of Sichuan Province(Grant No.2024NSFSC0522).
文摘The aerodynamic performance test rig for aircraft engine compressors serves as a core ground test facility for conducting aerodynamic design verification,performance evaluation,stability analysis,and flow mechanism research on compressors.The accuracy of its flow field measurement results directly determines the reliability of key conclusions,such as compressor characteristic curves,adiabatic efficiency,stability boundaries,and interstage matching relationships.In the context of developing a new generation of compressors with high load,high efficiency,and wide stability margins,traditional methods relying on empirical debugging and local calibration struggle to meet the requirements for high-precision aerodynamic testing.This paper takes an axial-flow compressor aerodynamic performance test rig as the research object,systematically elaborates on the typical process and mainstream methods of flow field calibration,analyzes the primary sources of error affecting measurement accuracy,and proposes an integrated strategy for improving accuracy from aspects such as probe calibration,flow rate calibration,flow field uniformity correction,installation and environmental compensation,and traceability of measurements.Furthermore,it provides a comparative analysis of calibration effects based on engineering test data.The research results indicate that through systematic flow field calibration and multi-dimensional error correction,the uncertainty in flow rate measurement can be reduced to better than±0.3%,with significant improvements in the measurement accuracy of total pressure and flow angle.The flow field non-uniformity is controlled within 3%,providing reliable data support for ground testing of high-performance compressors.
基金Supported by 2018 Education and Teaching Reform Special Fund in Central Colleges and Universities(E20180301)the Open Foundation of Civiation Aviation Flight University of China(J2015-02)
文摘Air transportation systems are often subject to failures or attacks induced by unexpected abominable weather or temporal airspace occupation, while complex networks have been springing up as a convenient yet efficient tool to represent and analyze various realistic complex systems such as realistic airline system. In terms of Chinese airline network formed during the spring festival timespan, structural empirical research and invulnerability simulation analysis against various deliberate attack strategies were made using complex network theory, where nodes and edges denotes domestic airports and direct flights between them respectively. The analysis results indicate: The presented airline network is a small net-work with scale-free characteristics, and correlation shows remarkable hierarchical structure and obvious assortative characteristics;The network shows obvious invulnerability under deliberate node attack, while shows partly robustness under edge attack even with obvious attack effects against various attack strategies.
