In traditional sensing,each parameter is treated as a real number in the signal demodulation,whereas the electric field of light is a complex number.The real and imaginary parts obey the Kramers-Kronig relationship,wh...In traditional sensing,each parameter is treated as a real number in the signal demodulation,whereas the electric field of light is a complex number.The real and imaginary parts obey the Kramers-Kronig relationship,which is expected to help further enhance sensing precision.We propose a self-Bayesian estimate of the method,aiming at reducing measurement variance.This method utilizes the intensity and phase of the parameter to be measured,achieving statistical optimization of the estimated value through Bayesian inference,effectively reducing the measurement variance.To demonstrate the effectiveness of this method,we adopted an optical fiber heterodyne interference sensing vibration measurement system.The experimental results show that the signal-to-noise ratio is effectively improved within the frequency range of 200 to 500 kHz.Moreover,it is believed that the self-Bayesian estimation method holds broad application prospects in various types of optical sensing.展开更多
Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the faste...Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the fastest responses to external environmental stimuli, leaf phenotypic traits are indicators of plant growth,health, and stress levels. Combination of new imaging sensors, image processing, and data analytics permits measurement over the full life span of plants at high temporal resolution and at several organizational levels from organs to individual plants to field populations of plants. We review the optical sensors and associated data analytics used for measuring morphological, physiological, and biochemical traits of plant leaves on multiple scales. We summarize the characteristics, advantages and limitations of optical sensing and data-processing methods applied in various plant phenotyping scenarios. Finally, we discuss the future prospects of plant leaf phenotyping research. This review aims to help researchers choose appropriate optical sensors and data processing methods to acquire plant leaf phenotypes rapidly,accurately, and cost-effectively.展开更多
Metal–dielectric nanostructures in the optical anapole modes are essential for light–matter interactions due to the low material loss and high near-field enhancement. Herein, a hybrid metal–dielectric nanoantenna c...Metal–dielectric nanostructures in the optical anapole modes are essential for light–matter interactions due to the low material loss and high near-field enhancement. Herein, a hybrid metal–dielectric nanoantenna composed of six wedgeshaped gold(Au) nanoblocks as well as silica(SiO2) and silicon(Si) nanodiscs is designed and analyzed by the finite element method(FEM). The nanoantenna exhibits flexibility in excitation and manipulation of the anapole mode through the strong coupling between the metal and dielectrics, consequently improving the near-field enhancement at the gap. By systematically optimizing the structural parameters, the electric field enhancement factors at wavelengths corresponding to the anapole modes(AM1 and AM2) can be increased to 518 and 1482, respectively. Moreover, the nanoantenna delivers great performance in optical sensing such as a sensitivity of 550 nm/RIU. The results provide guidance and insights into enhancing the coupling between metals and dielectrics for applications such as surface-enhanced Raman scattering and optical sensing.展开更多
Gas-insulated equipment(GIE)plays a critical role in modern power systems,where reliable and accurate condition monitoring is essential for operational safety.Optical sensing technologies,benefiting from immunity to e...Gas-insulated equipment(GIE)plays a critical role in modern power systems,where reliable and accurate condition monitoring is essential for operational safety.Optical sensing technologies,benefiting from immunity to electromagnetic interference,high sensitivity,and adaptability to harsh environments,offer promising alternatives to traditional electrical sensors.This review presents a comprehensive survey of optical sensing technologies for GIE,including fiber Bragg gratings(FBG),fiber-optic interferometry,distributed acoustic and temperature sensing,gas absorption spectroscopy,and electric-field detection based on the electro-optic(EO)effect.The fundamental principles,implementation schemes,and typical applications of each method are systematically analyzed.Despite the demonstrated advantages,challenges remain in sensor packaging reliability,optical coupling efficiency,and long-term stability.Future research should focus on enhancing system robustness,spatial resolution,and integration with digital twins and intelligent diagnostic frameworks.This work seeks to bridge GIE and optical sensing technologies,facilitating the development and deployment of high-reliability optical sensing systems for the monitoring of next-generation GIE.展开更多
Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced tran...Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.展开更多
An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyram...An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.展开更多
The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system ...The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system with kilometer-level sensing distance and submeter spatial resolution.Based on this,we propose a Raman distributed optical fiber sensing scheme based on chaotic pulse cluster demodulation.Chaotic pulse clusters are used as the probe signal,in preference to conventional pulsed or chaotic single-pulse lasers.Furthermore,the accurate positioning of the temperature variety region along the sensing fiber can be realized using chaotic pulse clusters.The proposed demodulation scheme can enhance the signal-to-noise ratio by improving the correlation between the chaotic reference and the chaotic Raman anti-Stokes scattering signals.The experiment achieved a sensing spatial resolution of 30 cm at a distributed temperature-sensing distance of∼6.0 km.Furthermore,we explored the influence of chaotic pulse width and detector bandwidth on the sensing spatial resolution.In addition,the theoretical experiments proved that the sensing spatial resolution in the proposed scheme was independent of the pulse width and sensing distance.展开更多
Efficient segmentation of oiled pixels in optical remotely sensed images is the precondition of optical identification and classification of different spilled oils,which remains one of the keys to optical remote sensi...Efficient segmentation of oiled pixels in optical remotely sensed images is the precondition of optical identification and classification of different spilled oils,which remains one of the keys to optical remote sensing of oil spills.Optical remotely sensed images of oil spills are inherently multidimensional and embedded with a complex knowledge framework.This complexity often hinders the effectiveness of mechanistic algorithms across varied scenarios.Although optical remote-sensing theory for oil spills has advanced,the scarcity of curated datasets and the difficulty of collecting them limit their usefulness for training deep learning models.This study introduces a data expansion strategy that utilizes the Segment Anything Model(SAM),effectively bridging the gap between traditional mechanism algorithms and emergent self-adaptive deep learning models.Optical dimension reduction is achieved through standardized preprocessing processes that address the decipherable properties of the input image.After preprocessing,SAM can swiftly and accurately segment spilled oil in images.The unified AI-based workflow significantly accelerates labeled-dataset creation and has proven effective for both rapid emergency intelligence during spill incidents and the rapid mapping and classification of oil footprints across China’s coastal waters.Our results show that coupling a remote sensing mechanism with a foundation model enables near-real-time,large-scale monitoring of complex surface slicks and offers guidance for the next generation of detection and quantification algorithms.展开更多
We demonstrated long-period grating(LPG) inscription on polymer functionalized optical microfibers and its applications in optical sensing. Optical microfibers were functionalized with ultraviolet-sensitive polymethyl...We demonstrated long-period grating(LPG) inscription on polymer functionalized optical microfibers and its applications in optical sensing. Optical microfibers were functionalized with ultraviolet-sensitive polymethyl methacrylate jackets and, thus, LPGs could be inscribed on optical microfibers via point-by-point ultraviolet laser exposure. For a 2 mm long microfiber LPG(MLPG) inscribed on optical microfibers with a diameter of 5.4 μm, a resonant dip of 15 d B at 1377 nm was observed. This MLPG showed a high sensitivity of strain and axial force, i.e.,-1.93 pm∕με and-1.15 pm∕μN, respectively. Although the intrinsic temperature sensitivity of the LPGs is relatively low, i.e.,-12.75 pm∕°C, it can be increased to be-385.11 pm∕°C by appropriate sealing. Benefiting from the small footprint and high sensitivity, MLPGs could have potential applications in optical sensing of strain,axial force, and temperature.展开更多
A low-cost and portable optical chemical sensor based ammonia sensing system that is capable of detecting dissolved ammonia up to 5 ppm is presented. In the system, an optical chemical sensor is designed and fabricate...A low-cost and portable optical chemical sensor based ammonia sensing system that is capable of detecting dissolved ammonia up to 5 ppm is presented. In the system, an optical chemical sensor is designed and fabricated for sensing dissolved ammonia concentrations. The sensor uses eosin as the fluorescence dye which is immobilized on the glass substrate by a gas-permeable protection layer. A compact module is developed to hold the optical components, and a battery powered micro-controller system is designed to read out and process the data measured. The system operates without the requirement of laboratory instruments that makes it cost effective and highly portable. Moreover, the calculated results in the system can be transmitted to a PC wirelessly, which allows the remote and real-time monitoring of dissolved ammonia.展开更多
The concrete hydration heat release process of the base plate is monitored using Roman optical time domain reflectometry（ROTDR） sensing sensors. The monitoring data shows that the internal maximum temperature of the...The concrete hydration heat release process of the base plate is monitored using Roman optical time domain reflectometry（ROTDR） sensing sensors. The monitoring data shows that the internal maximum temperature of the base plate is about 54 ℃ after the concrete was cured for 120 h. The fiber Bragg grating （FBG） temperature sensors are adopted to measure the surface temperature of the concrete and the temperature results are used to compensate the data measured by the pulse-prepump Brillouin optical time-domain analyzer （PPP-BOTDA） to obtain the real concrete surface strain of the base plate. The monitoring data is analyzed to obtain a clear understanding of the strain state of the base plate under the effect of concrete hydration heat release. The monitoring results demonstrate the potential of distributed optical fibre sensing techniques as a powerful tool in real-time construction monitoring, and also provide an important insight into the design, construction and maintenance of large hydraulic structures.展开更多
Since the beginning of the twenty-first century,several countries have made great efforts to develop space remote sensing for building a high-resolution earth observation system.Under the great attention of the govern...Since the beginning of the twenty-first century,several countries have made great efforts to develop space remote sensing for building a high-resolution earth observation system.Under the great attention of the government and the guidance of the major scientific and technological project of the high-resolution earth observation system,China has made continuous breakthroughs and progress in high-resolution remote sensing imaging technology.The development of domestic high-resolution remote sensing satellites shows a vigorous trend,and consequently,a relatively stable and perfect high-resolution earth observation system has been formed.The development of high-resolution remote sensing satellites has greatly promoted and enriched modern mapping technologies and methods.In this paper,the development status,along with mapping modes and applications of China’s high-resolution remote sensing satellites are reviewed,and the development trend in high-resolution earth observation system for global and ground control-free mapping is discussed,providing a reference for the subsequent development of high-resolution remote sensing satellites in China.展开更多
Considering the important applications in the military and the civilian domain, ship detection and classification based on optical remote sensing images raise considerable attention in the sea surface remote sensing f...Considering the important applications in the military and the civilian domain, ship detection and classification based on optical remote sensing images raise considerable attention in the sea surface remote sensing filed. This article collects the methods of ship detection and classification for practically testing in optical remote sensing images, and provides their corresponding feature extraction strategies and statistical data. Basic feature extraction strategies and algorithms are analyzed associated with their performance and application in ship detection and classification.Furthermore, publicly available datasets that can be applied as the benchmarks to verify the effectiveness and the objectiveness of ship detection and classification methods are summarized in this paper. Based on the analysis, the remaining problems and future development trends are provided for ship detection and classification methods based on optical remote sensing images.展开更多
Structural deformation monitoring of flight vehicles based on optical fiber sensing(OFS)technology has been a focus of research in the field of aerospace.After nearly 30 years of research and development,Chinese and i...Structural deformation monitoring of flight vehicles based on optical fiber sensing(OFS)technology has been a focus of research in the field of aerospace.After nearly 30 years of research and development,Chinese and international researchers have made significant advances in the areas of theory and methods,technology and systems,and ground experiments and flight tests.These advances have led to the development of OFS technology from the laboratory research stage to the engineering application stage.However,a few problems encountered in practical applications limit the wider application and further development of this technology,and thus urgently require solutions.This paper reviews the history of research on the deformation monitoring of flight vehicles.It examines various aspects of OFS-based deformation monitoring including the main varieties of OFS technology,technical advantages and disadvantages,suitability in aerospace applications,deformation reconstruction algorithms,and typical applications.This paper points out the key unresolved problems and the main evolution paradigms of engineering applications.It further discusses future development directions from the perspectives of an evolution paradigm,standardization,new materials,intelligentization,and collaboration.展开更多
In this work,Eu^(3+)-doped CsPbCl_(2)Br_(1) in borosilicate glass was successfully synthesized by the melt quenching annealing technique and crystallization method.This work reports a novel Eu^(3+)-doped CsPbCl_(2)Br_...In this work,Eu^(3+)-doped CsPbCl_(2)Br_(1) in borosilicate glass was successfully synthesized by the melt quenching annealing technique and crystallization method.This work reports a novel Eu^(3+)-doped CsPbCl_(2)Br_(1) perovskite quantum dots(QDs)glass with high sensitivity for optical temperature sensing.The relation of fluorescence intensity ratio(FIR)with the temperature was studied in the temperature range of 80-440 K.Notably,the maximum absolute temperature sensitivity(Sa)and relative temperature sensitivity(Sr)of Eu^(3+)-doped CsPbCl_(2)Br_(1) perovskite QDs glass can reach as high as 0.0315 K-1 and3.097%/K,respectively.Meanwhile,Eu^(3+)-doped CsPbCl_(2)Br_(1) QDs glass demonstrates good water resistance,excellent thermal and cold cycling stability performance,The Eu^(3+)-doped QDs glass materials can bring inspiration to the future exploration of rare earth ion-doped QDs glass material on the application of optical temperature sensing in the future.展开更多
This paper presents a bathymetry inversion method using single-frame fine-resolution optical remote sensing imagery based on ocean-wave refraction and shallow-water wave theory. First, the relationship among water dep...This paper presents a bathymetry inversion method using single-frame fine-resolution optical remote sensing imagery based on ocean-wave refraction and shallow-water wave theory. First, the relationship among water depth, wavelength and wave radian frequency in shallow water was deduced based on shallow-water wave theory. Considering the complex wave distribution in the optical remote sensing imagery, Fast Fourier Transform （FFT） and spatial profile measurements were applied for measuring the wavelengths. Then, the wave radian frequency was calculated by analyzing the long-distance fluctuation in the wavelength, which solved a key problem in obtaining the wave radian frequency in a single-frame image. A case study was conducted for Sanya Bay of Hainan Island, China. Single-flame fine-resolution optical remote sensing imagery from QuickBird satellite was used to invert the bathymetry without external input parameters. The result of the digital elevation model （DEM） was evaluated against a sea chart with a scale of 1：25 000. The root-mean-square error of the inverted bathymetry was 1.07 m, and the relative error was 16.2%. Therefore, the proposed method has the advantages including no requirement for true depths and environmental parameters, and is feasible for mapping the bathymetry of shallow coastal water.展开更多
Er-Tm3+-Ybtri-doped BaMoOphosphors were synthesized by co-precipitation technique and characterized by X-ray diffraction analysis, absorption study and field emission scanning electron microscopy analysis. Upconversio...Er-Tm3+-Ybtri-doped BaMoOphosphors were synthesized by co-precipitation technique and characterized by X-ray diffraction analysis, absorption study and field emission scanning electron microscopy analysis. Upconversion as well as downconversion luminescence studies were performed by using near infrared(980 nm) and ultraviolet(380 nm) excitations. Energy level diagram, pump power dependence and colour coordinate study were utilized to describe the multicolor upconversion emission properties. Under single 980 nm diode laser excitation the dual mode sensing behaviour is realized via Stark sublevels and thermally coupled energy levels of the Tm3+ and Erions in the prepared tri-doped phosphors. A comparative fluorescence intensity ratio analysis for integrated emission intensities arising from the Stark sublevels {~1 G4(a)) and ~1 G4(b))} and thermally coupled energy levels {~2 Hand 4 S3/2} of the Tm3+ and Er3+ ions, respectively was carried out in the prepared tri-doped BaMoOphosphors. The maximum sensitivity for thermally coupled energy levels of the Er3+ and Stark sublevels of the Tm3+ ion was reported. The developed phosphors could be useful in the display devices and optical thermo metric applications.展开更多
Due to the bird’s eye view of remote sensing sensors,the orientational information of an object is a key factor that has to be considered in object detection.To obtain rotating bounding boxes,existing studies either ...Due to the bird’s eye view of remote sensing sensors,the orientational information of an object is a key factor that has to be considered in object detection.To obtain rotating bounding boxes,existing studies either rely on rotated anchoring schemes or adding complex rotating ROI transfer layers,leading to increased computational demand and reduced detection speeds.In this study,we propose a novel internal-external optimized convolutional neural network for arbitrary orientated object detection in optical remote sensing images.For the internal opti-mization,we designed an anchor-based single-shot head detector that adopts the concept of coarse-to-fine detection for two-stage object detection networks.The refined rotating anchors are generated from the coarse detection head module and fed into the refining detection head module with a link of an embedded deformable convolutional layer.For the external optimiza-tion,we propose an IOU balanced loss that addresses the regression challenges related to arbitrary orientated bounding boxes.Experimental results on the DOTA and HRSC2016 bench-mark datasets show that our proposed method outperforms selected methods.展开更多
A new way is proposed to evaluate the influence of atmospheric turbulence on image resolution of airborne and space-borne optical remote sensing system, which is called as arrival angle-method. Applying this method, s...A new way is proposed to evaluate the influence of atmospheric turbulence on image resolution of airborne and space-borne optical remote sensing system, which is called as arrival angle-method. Applying this method, some engineering examples are selected to analyze the turbulence influences on image resolution based on three different atmospheric turbulence models quantificationally, for the airborne remote sensing system, the resolution errors caused by the atmospheric turbulence are less than 1 cm, and for the space-borne remote sensing system, the errors are around 1 cm. The results are similar to that obtained by the previous Friedmethod. Compared with the Fried-method, the arrival angle-method is rather simple and can be easily used in engineering fields.展开更多
To address the issue of imbalanced detection performance and detection speed in current mainstream object detection algorithms for optical remote sensing images,this paper proposes a multi-scale object detection model...To address the issue of imbalanced detection performance and detection speed in current mainstream object detection algorithms for optical remote sensing images,this paper proposes a multi-scale object detection model for remote sensing images on complex backgrounds,called DI-YOLO,based on You Only Look Once v7-tiny(YOLOv7-tiny).Firstly,to enhance the model’s ability to capture irregular-shaped objects and deformation features,as well as to extract high-level semantic information,deformable convolutions are used to replace standard convolutions in the original model.Secondly,a Content Coordination Attention Feature Pyramid Network(CCA-FPN)structure is designed to replace the Neck part of the original model,which can further perceive relationships between different pixels,reduce feature loss in remote sensing images,and improve the overall model’s ability to detect multi-scale objects.Thirdly,an Implicitly Efficient Decoupled Head(IEDH)is proposed to increase the model’s flexibility,making it more adaptable to complex detection tasks in various scenarios.Finally,the Smoothed Intersection over Union(SIoU)loss function replaces the Complete Intersection over Union(CIoU)loss function in the original model,resulting in more accurate prediction of bounding boxes and continuous model optimization.Experimental results on the High-Resolution Remote Sensing Detection(HRRSD)dataset demonstrate that the proposed DI-YOLO model outperforms mainstream target detection algorithms in terms of mean Average Precision(mAP)for optical remote sensing image detection.Furthermore,it achieves Frames Per Second(FPS)of 138.9,meeting fast and accurate detection requirements.展开更多
基金supported by the National Key Research and Development Plan of China(Grant No.2022YFB3207402)the National Natural Science Foundation of China(Grant Nos.U1833104 and 61735011).
文摘In traditional sensing,each parameter is treated as a real number in the signal demodulation,whereas the electric field of light is a complex number.The real and imaginary parts obey the Kramers-Kronig relationship,which is expected to help further enhance sensing precision.We propose a self-Bayesian estimate of the method,aiming at reducing measurement variance.This method utilizes the intensity and phase of the parameter to be measured,achieving statistical optimization of the estimated value through Bayesian inference,effectively reducing the measurement variance.To demonstrate the effectiveness of this method,we adopted an optical fiber heterodyne interference sensing vibration measurement system.The experimental results show that the signal-to-noise ratio is effectively improved within the frequency range of 200 to 500 kHz.Moreover,it is believed that the self-Bayesian estimation method holds broad application prospects in various types of optical sensing.
基金supported by the National Natural Science Foundation of China (32171790 and 32171818)Jiangsu Province Modern Agricultural Machinery Equipment and Technology Demonstration Promotion Project (NJ2020-18)+2 种基金Key Research and Development Program of Jiangsu Province (BE2021307)Qinglan Project Foundation of Jiangsu province333 Project of Jiangsu Province。
文摘Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the fastest responses to external environmental stimuli, leaf phenotypic traits are indicators of plant growth,health, and stress levels. Combination of new imaging sensors, image processing, and data analytics permits measurement over the full life span of plants at high temporal resolution and at several organizational levels from organs to individual plants to field populations of plants. We review the optical sensors and associated data analytics used for measuring morphological, physiological, and biochemical traits of plant leaves on multiple scales. We summarize the characteristics, advantages and limitations of optical sensing and data-processing methods applied in various plant phenotyping scenarios. Finally, we discuss the future prospects of plant leaf phenotyping research. This review aims to help researchers choose appropriate optical sensors and data processing methods to acquire plant leaf phenotypes rapidly,accurately, and cost-effectively.
基金Project supported by the Outstanding young and middleaged research and innovation team of Northeast Petroleum University (Grant No. KYCXTD201801)the Natural Science Foundation Projects of Heilongjiang Province of China (Grant No. LH2021F007)+3 种基金the China Postdoctoral Science Foundation (Grant No. 2020M670881)the Study Abroad returnees merit-based Aid Foundation of Heilongjiang Province of China (Grant No. 070-719900103)the Northeastern University scientific research projects (Grant No. 2019KQ74)the City University of Hong Kong Donation Research (Grant Nos. 9220061 and DON-RMG 9229021),and the City University of Hong Kong Strategic Research (Grant No. SRG 7005505)。
文摘Metal–dielectric nanostructures in the optical anapole modes are essential for light–matter interactions due to the low material loss and high near-field enhancement. Herein, a hybrid metal–dielectric nanoantenna composed of six wedgeshaped gold(Au) nanoblocks as well as silica(SiO2) and silicon(Si) nanodiscs is designed and analyzed by the finite element method(FEM). The nanoantenna exhibits flexibility in excitation and manipulation of the anapole mode through the strong coupling between the metal and dielectrics, consequently improving the near-field enhancement at the gap. By systematically optimizing the structural parameters, the electric field enhancement factors at wavelengths corresponding to the anapole modes(AM1 and AM2) can be increased to 518 and 1482, respectively. Moreover, the nanoantenna delivers great performance in optical sensing such as a sensitivity of 550 nm/RIU. The results provide guidance and insights into enhancing the coupling between metals and dielectrics for applications such as surface-enhanced Raman scattering and optical sensing.
基金supported in part by Smart Grid-National Science and Technology Major Project(No.2024ZD0802405)State Key Laboratory of Power System Operation and Control(No.SKLD24KM12)National Natural Science Foundation of China(No.52407175).
文摘Gas-insulated equipment(GIE)plays a critical role in modern power systems,where reliable and accurate condition monitoring is essential for operational safety.Optical sensing technologies,benefiting from immunity to electromagnetic interference,high sensitivity,and adaptability to harsh environments,offer promising alternatives to traditional electrical sensors.This review presents a comprehensive survey of optical sensing technologies for GIE,including fiber Bragg gratings(FBG),fiber-optic interferometry,distributed acoustic and temperature sensing,gas absorption spectroscopy,and electric-field detection based on the electro-optic(EO)effect.The fundamental principles,implementation schemes,and typical applications of each method are systematically analyzed.Despite the demonstrated advantages,challenges remain in sensor packaging reliability,optical coupling efficiency,and long-term stability.Future research should focus on enhancing system robustness,spatial resolution,and integration with digital twins and intelligent diagnostic frameworks.This work seeks to bridge GIE and optical sensing technologies,facilitating the development and deployment of high-reliability optical sensing systems for the monitoring of next-generation GIE.
基金research was funded by Science and Technology Project of State Grid Corporation of China under grant number 5200-202319382A-2-3-XG.
文摘Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.
基金supported by the National Natural Science Foundation of China(No.62241109)the Tianjin Science and Technology Commissioner Project(No.20YDTPJC01110)。
文摘An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.
基金supported by the National Natural Science Foundation of China(Grant Nos.U23A20375 and 62075151)the National Key Research and Development Program of China(Grant No.202103021223042).
文摘The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system with kilometer-level sensing distance and submeter spatial resolution.Based on this,we propose a Raman distributed optical fiber sensing scheme based on chaotic pulse cluster demodulation.Chaotic pulse clusters are used as the probe signal,in preference to conventional pulsed or chaotic single-pulse lasers.Furthermore,the accurate positioning of the temperature variety region along the sensing fiber can be realized using chaotic pulse clusters.The proposed demodulation scheme can enhance the signal-to-noise ratio by improving the correlation between the chaotic reference and the chaotic Raman anti-Stokes scattering signals.The experiment achieved a sensing spatial resolution of 30 cm at a distributed temperature-sensing distance of∼6.0 km.Furthermore,we explored the influence of chaotic pulse width and detector bandwidth on the sensing spatial resolution.In addition,the theoretical experiments proved that the sensing spatial resolution in the proposed scheme was independent of the pulse width and sensing distance.
基金The National Natural Science Foundation of China under contract No.42371380the National Key Research and Development Program of China under contract No.2023YFC2811800the Fundamental Research Funds for the Central Universities under contract No.0904-14380035.
文摘Efficient segmentation of oiled pixels in optical remotely sensed images is the precondition of optical identification and classification of different spilled oils,which remains one of the keys to optical remote sensing of oil spills.Optical remotely sensed images of oil spills are inherently multidimensional and embedded with a complex knowledge framework.This complexity often hinders the effectiveness of mechanistic algorithms across varied scenarios.Although optical remote-sensing theory for oil spills has advanced,the scarcity of curated datasets and the difficulty of collecting them limit their usefulness for training deep learning models.This study introduces a data expansion strategy that utilizes the Segment Anything Model(SAM),effectively bridging the gap between traditional mechanism algorithms and emergent self-adaptive deep learning models.Optical dimension reduction is achieved through standardized preprocessing processes that address the decipherable properties of the input image.After preprocessing,SAM can swiftly and accurately segment spilled oil in images.The unified AI-based workflow significantly accelerates labeled-dataset creation and has proven effective for both rapid emergency intelligence during spill incidents and the rapid mapping and classification of oil footprints across China’s coastal waters.Our results show that coupling a remote sensing mechanism with a foundation model enables near-real-time,large-scale monitoring of complex surface slicks and offers guidance for the next generation of detection and quantification algorithms.
基金supported by National Natural Science Foundation of China(Grant No.61505096)
文摘We demonstrated long-period grating(LPG) inscription on polymer functionalized optical microfibers and its applications in optical sensing. Optical microfibers were functionalized with ultraviolet-sensitive polymethyl methacrylate jackets and, thus, LPGs could be inscribed on optical microfibers via point-by-point ultraviolet laser exposure. For a 2 mm long microfiber LPG(MLPG) inscribed on optical microfibers with a diameter of 5.4 μm, a resonant dip of 15 d B at 1377 nm was observed. This MLPG showed a high sensitivity of strain and axial force, i.e.,-1.93 pm∕με and-1.15 pm∕μN, respectively. Although the intrinsic temperature sensitivity of the LPGs is relatively low, i.e.,-12.75 pm∕°C, it can be increased to be-385.11 pm∕°C by appropriate sealing. Benefiting from the small footprint and high sensitivity, MLPGs could have potential applications in optical sensing of strain,axial force, and temperature.
基金This work was supported by Enterprise Ireland （El） and Science Foundation Ireland （SFI）. The authors would like to thank Pat O＇Leary from Faaltech Technologies Ltd and Jean-Michel Rubillon from Cork Institute of Technology for their support and help.
文摘A low-cost and portable optical chemical sensor based ammonia sensing system that is capable of detecting dissolved ammonia up to 5 ppm is presented. In the system, an optical chemical sensor is designed and fabricated for sensing dissolved ammonia concentrations. The sensor uses eosin as the fluorescence dye which is immobilized on the glass substrate by a gas-permeable protection layer. A compact module is developed to hold the optical components, and a battery powered micro-controller system is designed to read out and process the data measured. The system operates without the requirement of laboratory instruments that makes it cost effective and highly portable. Moreover, the calculated results in the system can be transmitted to a PC wirelessly, which allows the remote and real-time monitoring of dissolved ammonia.
基金The National Key Technology R&D Program during the 12th Five-Year Plan Period(No.2012BAK10B05)the State Key Program of National Natural Science of China(No.41427801)
文摘The concrete hydration heat release process of the base plate is monitored using Roman optical time domain reflectometry（ROTDR） sensing sensors. The monitoring data shows that the internal maximum temperature of the base plate is about 54 ℃ after the concrete was cured for 120 h. The fiber Bragg grating （FBG） temperature sensors are adopted to measure the surface temperature of the concrete and the temperature results are used to compensate the data measured by the pulse-prepump Brillouin optical time-domain analyzer （PPP-BOTDA） to obtain the real concrete surface strain of the base plate. The monitoring data is analyzed to obtain a clear understanding of the strain state of the base plate under the effect of concrete hydration heat release. The monitoring results demonstrate the potential of distributed optical fibre sensing techniques as a powerful tool in real-time construction monitoring, and also provide an important insight into the design, construction and maintenance of large hydraulic structures.
基金This work is supported by the National Natural Science Foundation of China[grant numbers 91738302 and 91838303]the National Science Fund for Distinguished Young Scholars[grant number 61825103]Thanks for the support of China Centre for Resources Satellite Data and Application(CRESDA).
文摘Since the beginning of the twenty-first century,several countries have made great efforts to develop space remote sensing for building a high-resolution earth observation system.Under the great attention of the government and the guidance of the major scientific and technological project of the high-resolution earth observation system,China has made continuous breakthroughs and progress in high-resolution remote sensing imaging technology.The development of domestic high-resolution remote sensing satellites shows a vigorous trend,and consequently,a relatively stable and perfect high-resolution earth observation system has been formed.The development of high-resolution remote sensing satellites has greatly promoted and enriched modern mapping technologies and methods.In this paper,the development status,along with mapping modes and applications of China’s high-resolution remote sensing satellites are reviewed,and the development trend in high-resolution earth observation system for global and ground control-free mapping is discussed,providing a reference for the subsequent development of high-resolution remote sensing satellites in China.
文摘Considering the important applications in the military and the civilian domain, ship detection and classification based on optical remote sensing images raise considerable attention in the sea surface remote sensing filed. This article collects the methods of ship detection and classification for practically testing in optical remote sensing images, and provides their corresponding feature extraction strategies and statistical data. Basic feature extraction strategies and algorithms are analyzed associated with their performance and application in ship detection and classification.Furthermore, publicly available datasets that can be applied as the benchmarks to verify the effectiveness and the objectiveness of ship detection and classification methods are summarized in this paper. Based on the analysis, the remaining problems and future development trends are provided for ship detection and classification methods based on optical remote sensing images.
基金funded by the National Natural Science Foundation of China(51705024,51535002,51675053,61903041,61903042,and 61903041)the National Key Research and Development Program of China(2016YFF0101801)+4 种基金the National Hightech Research and Development Program of China(2015AA042308)the Innovative Equipment Pre-Research Key Fund Project(6140414030101)the Manned Space Pre-Research Project(20184112043)the Beijing Municipal Natural Science Foundation(F7202017 and 4204101)the Beijing Nova Program of Science and Technology(Z191100001119052)。
文摘Structural deformation monitoring of flight vehicles based on optical fiber sensing(OFS)technology has been a focus of research in the field of aerospace.After nearly 30 years of research and development,Chinese and international researchers have made significant advances in the areas of theory and methods,technology and systems,and ground experiments and flight tests.These advances have led to the development of OFS technology from the laboratory research stage to the engineering application stage.However,a few problems encountered in practical applications limit the wider application and further development of this technology,and thus urgently require solutions.This paper reviews the history of research on the deformation monitoring of flight vehicles.It examines various aspects of OFS-based deformation monitoring including the main varieties of OFS technology,technical advantages and disadvantages,suitability in aerospace applications,deformation reconstruction algorithms,and typical applications.This paper points out the key unresolved problems and the main evolution paradigms of engineering applications.It further discusses future development directions from the perspectives of an evolution paradigm,standardization,new materials,intelligentization,and collaboration.
基金Project supported by the National Natural Science Foundation of China(51872207,51672192)。
文摘In this work,Eu^(3+)-doped CsPbCl_(2)Br_(1) in borosilicate glass was successfully synthesized by the melt quenching annealing technique and crystallization method.This work reports a novel Eu^(3+)-doped CsPbCl_(2)Br_(1) perovskite quantum dots(QDs)glass with high sensitivity for optical temperature sensing.The relation of fluorescence intensity ratio(FIR)with the temperature was studied in the temperature range of 80-440 K.Notably,the maximum absolute temperature sensitivity(Sa)and relative temperature sensitivity(Sr)of Eu^(3+)-doped CsPbCl_(2)Br_(1) perovskite QDs glass can reach as high as 0.0315 K-1 and3.097%/K,respectively.Meanwhile,Eu^(3+)-doped CsPbCl_(2)Br_(1) QDs glass demonstrates good water resistance,excellent thermal and cold cycling stability performance,The Eu^(3+)-doped QDs glass materials can bring inspiration to the future exploration of rare earth ion-doped QDs glass material on the application of optical temperature sensing in the future.
基金The Public Science and Technology Research Fund Project of Ocean under contract No.201105001the National Nature Science Foundation of China under contract No.41576174the Public Science and Technology Research Fund Project of Surveying,Mapping and Geoinformation under contract No.201512030
文摘This paper presents a bathymetry inversion method using single-frame fine-resolution optical remote sensing imagery based on ocean-wave refraction and shallow-water wave theory. First, the relationship among water depth, wavelength and wave radian frequency in shallow water was deduced based on shallow-water wave theory. Considering the complex wave distribution in the optical remote sensing imagery, Fast Fourier Transform （FFT） and spatial profile measurements were applied for measuring the wavelengths. Then, the wave radian frequency was calculated by analyzing the long-distance fluctuation in the wavelength, which solved a key problem in obtaining the wave radian frequency in a single-frame image. A case study was conducted for Sanya Bay of Hainan Island, China. Single-flame fine-resolution optical remote sensing imagery from QuickBird satellite was used to invert the bathymetry without external input parameters. The result of the digital elevation model （DEM） was evaluated against a sea chart with a scale of 1：25 000. The root-mean-square error of the inverted bathymetry was 1.07 m, and the relative error was 16.2%. Therefore, the proposed method has the advantages including no requirement for true depths and environmental parameters, and is feasible for mapping the bathymetry of shallow coastal water.
基金Project supported by Council of Scientific&Industrial Research(CSIR)New Delhi,India(03(1354)/16/EMR-II)
文摘Er-Tm3+-Ybtri-doped BaMoOphosphors were synthesized by co-precipitation technique and characterized by X-ray diffraction analysis, absorption study and field emission scanning electron microscopy analysis. Upconversion as well as downconversion luminescence studies were performed by using near infrared(980 nm) and ultraviolet(380 nm) excitations. Energy level diagram, pump power dependence and colour coordinate study were utilized to describe the multicolor upconversion emission properties. Under single 980 nm diode laser excitation the dual mode sensing behaviour is realized via Stark sublevels and thermally coupled energy levels of the Tm3+ and Erions in the prepared tri-doped phosphors. A comparative fluorescence intensity ratio analysis for integrated emission intensities arising from the Stark sublevels {~1 G4(a)) and ~1 G4(b))} and thermally coupled energy levels {~2 Hand 4 S3/2} of the Tm3+ and Er3+ ions, respectively was carried out in the prepared tri-doped BaMoOphosphors. The maximum sensitivity for thermally coupled energy levels of the Er3+ and Stark sublevels of the Tm3+ ion was reported. The developed phosphors could be useful in the display devices and optical thermo metric applications.
基金This work is supported by the National Natural Science Foundation of China[grant numbers 41890820,41771452,41771454,and 41901340]。
文摘Due to the bird’s eye view of remote sensing sensors,the orientational information of an object is a key factor that has to be considered in object detection.To obtain rotating bounding boxes,existing studies either rely on rotated anchoring schemes or adding complex rotating ROI transfer layers,leading to increased computational demand and reduced detection speeds.In this study,we propose a novel internal-external optimized convolutional neural network for arbitrary orientated object detection in optical remote sensing images.For the internal opti-mization,we designed an anchor-based single-shot head detector that adopts the concept of coarse-to-fine detection for two-stage object detection networks.The refined rotating anchors are generated from the coarse detection head module and fed into the refining detection head module with a link of an embedded deformable convolutional layer.For the external optimiza-tion,we propose an IOU balanced loss that addresses the regression challenges related to arbitrary orientated bounding boxes.Experimental results on the DOTA and HRSC2016 bench-mark datasets show that our proposed method outperforms selected methods.
文摘A new way is proposed to evaluate the influence of atmospheric turbulence on image resolution of airborne and space-borne optical remote sensing system, which is called as arrival angle-method. Applying this method, some engineering examples are selected to analyze the turbulence influences on image resolution based on three different atmospheric turbulence models quantificationally, for the airborne remote sensing system, the resolution errors caused by the atmospheric turbulence are less than 1 cm, and for the space-borne remote sensing system, the errors are around 1 cm. The results are similar to that obtained by the previous Friedmethod. Compared with the Fried-method, the arrival angle-method is rather simple and can be easily used in engineering fields.
基金Funding for this research was provided by 511 Shaanxi Province’s Key Research and Development Plan(No.2022NY-087).
文摘To address the issue of imbalanced detection performance and detection speed in current mainstream object detection algorithms for optical remote sensing images,this paper proposes a multi-scale object detection model for remote sensing images on complex backgrounds,called DI-YOLO,based on You Only Look Once v7-tiny(YOLOv7-tiny).Firstly,to enhance the model’s ability to capture irregular-shaped objects and deformation features,as well as to extract high-level semantic information,deformable convolutions are used to replace standard convolutions in the original model.Secondly,a Content Coordination Attention Feature Pyramid Network(CCA-FPN)structure is designed to replace the Neck part of the original model,which can further perceive relationships between different pixels,reduce feature loss in remote sensing images,and improve the overall model’s ability to detect multi-scale objects.Thirdly,an Implicitly Efficient Decoupled Head(IEDH)is proposed to increase the model’s flexibility,making it more adaptable to complex detection tasks in various scenarios.Finally,the Smoothed Intersection over Union(SIoU)loss function replaces the Complete Intersection over Union(CIoU)loss function in the original model,resulting in more accurate prediction of bounding boxes and continuous model optimization.Experimental results on the High-Resolution Remote Sensing Detection(HRRSD)dataset demonstrate that the proposed DI-YOLO model outperforms mainstream target detection algorithms in terms of mean Average Precision(mAP)for optical remote sensing image detection.Furthermore,it achieves Frames Per Second(FPS)of 138.9,meeting fast and accurate detection requirements.
