The surface acoustic wave （SAW） identification （ID）-tags have great potential for application in radio frequency identification （RFID） due to their characteristics of wireless sensing and passive operation. In t...The surface acoustic wave （SAW） identification （ID）-tags have great potential for application in radio frequency identification （RFID） due to their characteristics of wireless sensing and passive operation. In the measurements based on the frequency domain sampling （FDS）, to expand the range of detection and allow the system work in harsh environments, it is necessary to enhance the identification capability at low SNR. In addition, to identify the tags in real time, it is important to reduce identification time. Therefore, estimation of signal parameters based on the Procrustes rotations via the rotational invariance technique （PRO-ESPRIT） is adopted. Experimental results show that good identification capability is achieved with a relatively faster measurement speed.展开更多
Schlieren imaging is a widely used technique to visualize the structure of supersonic flow field,which is usually dominated by shock waves.Precise identification of shock waves in schlieren image provides critical ins...Schlieren imaging is a widely used technique to visualize the structure of supersonic flow field,which is usually dominated by shock waves.Precise identification of shock waves in schlieren image provides critical insights for flow diagnostics,especially for supersonic inlet whose performance is highly associated with that of the whole flight.However,conventional shock wave identification methods have limited accuracy in segmenting the shock wave.To overcome the limitation,we proposed an automated shock wave identification method(SW-Segment)that can attain high resolution and automatic shock wave segmentation by integrating correlation-based feature extraction with graph search.We demonstrated the efficacy of SW-Segment via the identification of shock waves in simulatively and experimentally obtained schlieren image.The results proved that SW-Segment showed a shock wave identification accuracy of 95.24%in the numerical schlieren image and an accuracy of 88.33%in the experimental image,clearly demonstrating its reliability.SW-Segment holds broad applicability for shock wave detection in diverse schlieren imaging scenarios,offering robust data support for flow field analysis and supersonic flight design.展开更多
Scholte waves at the seafloor interface are generally identified by their velocity features and seismic fields,which are measured using ocean bottom seismometers and geophones.These methods are effective in cases wher...Scholte waves at the seafloor interface are generally identified by their velocity features and seismic fields,which are measured using ocean bottom seismometers and geophones.These methods are effective in cases where there is a considerable difference between the velocities of Scholte and acoustic waves in water.However,they are ineffective when the velocities of these two types of waves are close to each other.Thus,in this paper,a method based on acoustic pressure field measurement for identifying Scholte waves is proposed according to their excitation and propagation characteristics.The proposed method can overcome the limitations on the velocities of two types of waves.A tank experiment is designed and conducted according to the proposed method,and an ocean environment is scaled down to the laboratory size.Acoustic measurements are obtained along virtual arrays in the water column using a robotic apparatus.Experiments show that changes in Scholte wave amplitudes,depending on different source depths and propagation distances,are consistent with the theoretical results.This means that Scholte waves generated at the seafloor interface are successfully measured and identified in the acoustic pressure field.展开更多
文摘The surface acoustic wave （SAW） identification （ID）-tags have great potential for application in radio frequency identification （RFID） due to their characteristics of wireless sensing and passive operation. In the measurements based on the frequency domain sampling （FDS）, to expand the range of detection and allow the system work in harsh environments, it is necessary to enhance the identification capability at low SNR. In addition, to identify the tags in real time, it is important to reduce identification time. Therefore, estimation of signal parameters based on the Procrustes rotations via the rotational invariance technique （PRO-ESPRIT） is adopted. Experimental results show that good identification capability is achieved with a relatively faster measurement speed.
基金supported by the National Natural Science Foundation of China(Grant Nos.12402336,U20A2070,12025202)the Natural Science Foundation of Jiangsu Province(Grant No.BK20230876)+2 种基金the National High-Level Talent Project(Grant No.YQR23069)the Key Laboratory of Intake and Exhaust Technology,Ministry of Education(Grant No.CEPE2024015)the Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics)(Grant No.MCAS-I-0325K01)。
文摘Schlieren imaging is a widely used technique to visualize the structure of supersonic flow field,which is usually dominated by shock waves.Precise identification of shock waves in schlieren image provides critical insights for flow diagnostics,especially for supersonic inlet whose performance is highly associated with that of the whole flight.However,conventional shock wave identification methods have limited accuracy in segmenting the shock wave.To overcome the limitation,we proposed an automated shock wave identification method(SW-Segment)that can attain high resolution and automatic shock wave segmentation by integrating correlation-based feature extraction with graph search.We demonstrated the efficacy of SW-Segment via the identification of shock waves in simulatively and experimentally obtained schlieren image.The results proved that SW-Segment showed a shock wave identification accuracy of 95.24%in the numerical schlieren image and an accuracy of 88.33%in the experimental image,clearly demonstrating its reliability.SW-Segment holds broad applicability for shock wave detection in diverse schlieren imaging scenarios,offering robust data support for flow field analysis and supersonic flight design.
基金the National Natural Science Foundation of China(No.11474258)the State Key Laboratory of Acoustics(No.SKLA202206)。
文摘Scholte waves at the seafloor interface are generally identified by their velocity features and seismic fields,which are measured using ocean bottom seismometers and geophones.These methods are effective in cases where there is a considerable difference between the velocities of Scholte and acoustic waves in water.However,they are ineffective when the velocities of these two types of waves are close to each other.Thus,in this paper,a method based on acoustic pressure field measurement for identifying Scholte waves is proposed according to their excitation and propagation characteristics.The proposed method can overcome the limitations on the velocities of two types of waves.A tank experiment is designed and conducted according to the proposed method,and an ocean environment is scaled down to the laboratory size.Acoustic measurements are obtained along virtual arrays in the water column using a robotic apparatus.Experiments show that changes in Scholte wave amplitudes,depending on different source depths and propagation distances,are consistent with the theoretical results.This means that Scholte waves generated at the seafloor interface are successfully measured and identified in the acoustic pressure field.
