The Synthetic Aperture Radar(SAR)raw data generator is required to the evaluation of focusing algorithms,moving target analysis,and hardware design.The time-domain SAR simulator can generate the accurate raw data but ...The Synthetic Aperture Radar(SAR)raw data generator is required to the evaluation of focusing algorithms,moving target analysis,and hardware design.The time-domain SAR simulator can generate the accurate raw data but it needs much time.The frequency-domain simulator not only increases the efficiency but also considers the trajectory deviations of the radar.In addition,the raw signal of the extended scene included static and moving targets can be generated by some frequency-domain simulators.However,the existing simulators concentrate on the raw signal simulation of the static extended scene and moving targets at uniform speed mostly.As for the issue,the two-dimensional signal spectrum of moving targets with constant acceleration can be derived accurately based on the geometric model of a side-looking SAR and reversion of series.And a frequency-domain algorithm for SAR echo signal simulation is presented based on the two-dimensional signal spectrum.The raw data generated with proposed method is verified by several simulation experiments.In addition to reveal the efficiency of the presented frequency-domain SAR scene simulator,the computational complexity of the proposed method is compared with the time-domain approach using the complex multiplication.Numerical results demonstrate that the present method can reduce the computational time significantly without accuracy loss while simulating SAR raw data.展开更多
Low energy impact can induce invisible damage of carbon fiber reinforced polymer(CFRP).The damage can seriously affect the safety of the CFRP structure.Therefore,damage detection is crucial to the CFRP structure.Impac...Low energy impact can induce invisible damage of carbon fiber reinforced polymer(CFRP).The damage can seriously affect the safety of the CFRP structure.Therefore,damage detection is crucial to the CFRP structure.Impact location information is the premise of damage detection.Hence,impact localization is the primary issue.In this paper,an impact localization system,based on the fiber Bragg grating(FBG)sensor network,is proposed for impact detection and localization.For the completed impact signal,the FBG sensor and narrow-band laser demodulation technology are applied.Wavelet packet decomposition is introduced to extract available frequency band signals and attenuate noise.According to the energy of the available frequency band signal,an impact localization model,based on the extreme learning machine(ELM),is established with the faster training speed and less parameters.The above system is verified on the 500 mm×500 mm×2 mm CFRP plate.The maximum localization error and the minimum localization error are 30.4 mm and 6.7 mm,respectively.The average localization error is 14.7 mm,and training time is 0.7 s.Compared with the other machine learning methods,the localization system,proposed in this paper,has higher accuracy and faster training speed.This paper provides a practical system for impact localization of the CFRP structure.展开更多
In practical application, carbon fiber reinforced plastics （CFRP） structures are easy to appear all sorts of invisible damages. So the damages should be timely located and detected for the safety of CFPR structures....In practical application, carbon fiber reinforced plastics （CFRP） structures are easy to appear all sorts of invisible damages. So the damages should be timely located and detected for the safety of CFPR structures. In this paper, an acoustic emission （AE） localization system based on fiber Bragg grating （FBG） sensing network and support vector regression （SVR） is proposed for damage localization. AE signals, which are caused by damage, are acquired by high speed FBG interrogation. According to the Shannon wavelet transform, time differences between AE signals are extracted for localization algorithm based on SVR. According to the SVR model, the coordinate of AE source can be accurately predicted without wave velocity. The FBG system and localization algorithm are verified on a 500mm×SOOmm×2mm CFRP plate. The experimental results show that the average error of localization system is 2.8 mm and the training time is 0.07 s.展开更多
In some applications in structural health monitoring （SHM）, the acoustic emission （AE） detection technology is used in the high temperature environment. In this paper, a high-temperature-resistant AE sensing syste...In some applications in structural health monitoring （SHM）, the acoustic emission （AE） detection technology is used in the high temperature environment. In this paper, a high-temperature-resistant AE sensing system is developed based on the fiber Bragg grating （FBG） sensor. A novel high temperature FBG AE sensor is designed With a high signal-to-noise ratio （SNR） compared with the traditional FBG AE sensor. The output responses of the designed sensors with different sensing fiber lengths also are investigated both theoretically and experimentally. Excellent AE detection results are obtained using the proposed FBG AE sensing system over a temperature range from 25℃ to 200℃. The experimental results indicate that this FBG AE sensing system can well meet the application requirement in AE detecting areas at high temperature.展开更多
基金The work was supported by the Natural Science Foundation of Shandong Province,China.(Grant No.ZR2017BF032)。
文摘The Synthetic Aperture Radar(SAR)raw data generator is required to the evaluation of focusing algorithms,moving target analysis,and hardware design.The time-domain SAR simulator can generate the accurate raw data but it needs much time.The frequency-domain simulator not only increases the efficiency but also considers the trajectory deviations of the radar.In addition,the raw signal of the extended scene included static and moving targets can be generated by some frequency-domain simulators.However,the existing simulators concentrate on the raw signal simulation of the static extended scene and moving targets at uniform speed mostly.As for the issue,the two-dimensional signal spectrum of moving targets with constant acceleration can be derived accurately based on the geometric model of a side-looking SAR and reversion of series.And a frequency-domain algorithm for SAR echo signal simulation is presented based on the two-dimensional signal spectrum.The raw data generated with proposed method is verified by several simulation experiments.In addition to reveal the efficiency of the presented frequency-domain SAR scene simulator,the computational complexity of the proposed method is compared with the time-domain approach using the complex multiplication.Numerical results demonstrate that the present method can reduce the computational time significantly without accuracy loss while simulating SAR raw data.
基金This research is supported by the National Natural Science Foundation of China under Grant Nos.61503218 and 61705098Natural Science Foundation of Shandong Province,China under Grant Nos.ZR2017BF042,ZR2016FM36,and ZR2017BF032Ph.D.Programs Foundation of Ludong University under Grant No.LA2017006.
文摘Low energy impact can induce invisible damage of carbon fiber reinforced polymer(CFRP).The damage can seriously affect the safety of the CFRP structure.Therefore,damage detection is crucial to the CFRP structure.Impact location information is the premise of damage detection.Hence,impact localization is the primary issue.In this paper,an impact localization system,based on the fiber Bragg grating(FBG)sensor network,is proposed for impact detection and localization.For the completed impact signal,the FBG sensor and narrow-band laser demodulation technology are applied.Wavelet packet decomposition is introduced to extract available frequency band signals and attenuate noise.According to the energy of the available frequency band signal,an impact localization model,based on the extreme learning machine(ELM),is established with the faster training speed and less parameters.The above system is verified on the 500 mm×500 mm×2 mm CFRP plate.The maximum localization error and the minimum localization error are 30.4 mm and 6.7 mm,respectively.The average localization error is 14.7 mm,and training time is 0.7 s.Compared with the other machine learning methods,the localization system,proposed in this paper,has higher accuracy and faster training speed.This paper provides a practical system for impact localization of the CFRP structure.
文摘In practical application, carbon fiber reinforced plastics （CFRP） structures are easy to appear all sorts of invisible damages. So the damages should be timely located and detected for the safety of CFPR structures. In this paper, an acoustic emission （AE） localization system based on fiber Bragg grating （FBG） sensing network and support vector regression （SVR） is proposed for damage localization. AE signals, which are caused by damage, are acquired by high speed FBG interrogation. According to the Shannon wavelet transform, time differences between AE signals are extracted for localization algorithm based on SVR. According to the SVR model, the coordinate of AE source can be accurately predicted without wave velocity. The FBG system and localization algorithm are verified on a 500mm×SOOmm×2mm CFRP plate. The experimental results show that the average error of localization system is 2.8 mm and the training time is 0.07 s.
基金This research is supported by the National Natural Science Foundation of China （Grant Nos. 61403233, 61503218, 61573226, and 61473176）, the Excellent Young and Middle-Aged Scientist Award Grant of Shandong Province of China （No. BS2013DX018）, and the Natural Science Foundation of Shandong Province for Outstanding Young Talents （No. ZR2015JL021）.
文摘In some applications in structural health monitoring （SHM）, the acoustic emission （AE） detection technology is used in the high temperature environment. In this paper, a high-temperature-resistant AE sensing system is developed based on the fiber Bragg grating （FBG） sensor. A novel high temperature FBG AE sensor is designed With a high signal-to-noise ratio （SNR） compared with the traditional FBG AE sensor. The output responses of the designed sensors with different sensing fiber lengths also are investigated both theoretically and experimentally. Excellent AE detection results are obtained using the proposed FBG AE sensing system over a temperature range from 25℃ to 200℃. The experimental results indicate that this FBG AE sensing system can well meet the application requirement in AE detecting areas at high temperature.
