Optical anapole modes in hybrid metal–dielectric nanoantenna for near-field enhancement and optical sensing

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.

High-throughput phenotyping of plant leaf morphological, physiological,and biochemical traits on multiple scales using optical sensing

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.

Experimental study on the variation of optical remote sensing imaging characteristics of internal solitary waves with wind speed

Optical remote sensing has been widely used to study internal solitary waves(ISWs).Wind speed has an important effect on ISW imaging of optical remote sensing.The light and dark bands of ISWs cannot be observed by optical remote sensing when the wind is too strong.The relationship between the characteristics of ISWs bands in optical remote sensing images and the wind speed is still unclear.The influence of wind speeds on the characteristics of the ISWs bands is investigated based on the physical simulation experiments with the wind speeds of 1.6,3.1,3.5,3.8,and 3.9 m/s.The experimental results show that when the wind speed is 3.9 m/s,the ISWs bands cannot be observed in optical remote sensing images with the stratification of h_(1)∶h_(2)=7∶58,ρ_(1)∶ρ_(2)=1∶1.04.When the wind speeds are 3.1,3.5,and 3.8 m/s,which is lower than 3.9 m/s,the ISWs bands can be obtained in the simulated optical remote sensing image.The location of the band’s dark and light extremum and the band’s peak-to-peak spacing are almost not affected by wind speed.More-significant wind speeds can cause a greater gray difference of the light-dark bands.This provided a scientific basis for further understanding of ISW optical remote sensing imaging.

Optical remote sensing image characteristics of large amplitude convex mode-2 internal solitary waves:an experimental study

A series of experiments are designed to propose a new method to study the characteristics of convex mode-2internal solitary waves(ISWs)in optical remote sensing images using a laboratory-based optical remote sensing simulation platform.The corresponding wave parameters of large-amplitude convex mode-2 ISWs under smooth surfaces are investigated along with the optical remote sensing characteristic parameters.The mode-2 ISWs in the experimentally obtained optical remote sensing image are produced by their overall modulation effect on the water surface,and the extreme points of the gray value of the profile curve of bright-dark stripes appear at the same location as the real optical remote sensing image.The present data extend to a larger range than previous studies,and for the characteristics of large amplitude convex mode-2 ISWs,the experimental results show a second-order dependence of wavelength on amplitude.There is a close relationship between optical remote sensing characteristic parameters and wave parameters of mode-2 ISWs,in which there is a positive linear relationship between the bright-dark spacing and wavelength and a nonlinear relationship with the amplitude,especially when the amplitude is very large,there is a significant increase in bright-dark spacing.

An Intelligent Detection Method for Optical Remote Sensing Images Based on Improved YOLOv7

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.

Long-period grating inscription on polymer functionalized optical microfibers and its applications in optical sensing

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.

A Low-Cost, Portable Optical Sensing System With Wireless Communication Compatible of Real-Time and Remote Detection of Dissolved Ammonia

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.

Construction monitoring of lock head base plate using distributed optical fibre sensing technique

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.

Mapping the bathymetry of shallow coastal water using singleframe fine-resolution optical remote sensing imagery

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.

Structural Deformation Monitoring of Flight Vehicles Based on Optical Fiber Sensing Technology:A Review and Future Perspectives

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.

Influences of Atmospheric Turbulence on Image Resolution of Airborne and Space-Borne Optical Remote Sensing System

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.

Optical Remote-sensing Monitoring and Forecasting of Atmospheric Pollution in Huaibei Area, China

Huaibei is an energy city. Coal as the primary energy consumption brings a large number of regional pollution in Huaibei area. Differential optical absorption spectroscopy （DOAS） as optical remote sensing technology has been applied to monitor regional average concen- trations and inventory of nitrogen dioxide, sulfur dioxide and ozone. DOAS system was set up and applied to monitor the main air pollutants in Huaibei area. Monitoring data were obtained from 7 to 28 August, 2011. Monitoring results show measurements in controlling pollution are effective, and emissions of pollutants are up to the national standard in Huaibei area. Prediction model was also created to track changing trend of pollutions. These will provide raw data support for effective evaluation of environmental quality in Huaibei area.

A hardening load transfer function for rock bolts and its calibration using distributed fiber optic sensing

Confinement of rock bolts by the surrounding rock formation has long been recognized as a positive contributor to the pull-out behavior,yet only a few experimental works and analytical models have been reported,most of which are based on the global rock bolt response evaluated in pull-out tests.This paper presents a laboratory experimental setup aiming to capture the rock formation effect,while using distributed fiber optic sensing to quantify the effect of the confinement and the reinforcement pull-out behavior on a more local level.It is shown that the behavior along the sample itself varies,with certain points exhibiting stress drops with crack formation.Some edge effects related to the kinematic freedom of the grout to dilate are also observed.Regardless,it was found that the mid-level response is quite similar to the average response along the sample.The ability to characterize the variation of the response along the sample is one of the many advantages high-resolution fiber optic sensing allows in such investigations.The paper also offers a plasticity-based hardening load transfer function,representing a"slice"of the anchor.The paper describes in detail the development of the model and the calibration/determination of its parameters.The suggested model captures well the coupled behavior in which the pull-out process leads to an increase in the confining stress due to dilative behavior.

Feasibility study on sinkhole monitoring with fiber optic strain sensing nerves

Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This paper presents an experimental study to evaluate the feasibility of fiber optic strain sensing nerves in sinkhole monitoring.Combining the artificial neural network(ANN)and particle image velocimetry(PIV)techniques,a series of model tests have been performed to explore the relationship between strain measurements and sinkhole development and to establish a conversion model from strain data to ground settlements.It is demonstrated that the failure mechanism of the soil above the sinkhole developed from a triangle failure plane to a vertical failure plane with increasing collapse volume.Meanwhile,the soil-embedded fiber optic strain sensing nerves allowed deformation monitoring of the ground soil in real time.Furthermore,the characteristics of the measured strain profiles indicate the locations of sinkholes and the associated shear bands.Based on the strain data,the ANN model predicts the ground settlement well.Additionally,micro-anchored fiber optic cables have been proven to increase the soil-to-fiber strain transfer efficiency for large deformation monitoring of ground collapse.

Optical SDMA for applying compressive sensing in WSN

In order to apply compressive sensing in wireless sensor network, inside the nodes cluster classified by the spatial correlation, we propose that a cluster head adopts free space optical communication with space division multiple access, and a sensor node uses a modulating retro-reflector for communication. Thus while a random sampling matrix is used to guide the establishment of links between head cluster and sensor nodes, the random linear projection is accomplished. To establish multiple links at the same time, an optical space division multiple access antenna is designed. It works in fixed beams switching mode and consists of optic lens with a large field of view（FOV）, fiber array on the focal plane which is used to realize virtual channels segmentation, direction of arrival sensor, optical matrix switch and controller. Based on the angles of nodes＇ laser beams, by dynamically changing the route, optical matrix switch actualizes the multi-beam full duplex tracking receiving and transmission. Due to the structure of fiber array, there will be several fade zones both in the focal plane and in lens＇ FOV. In order to lower the impact of fade zones and harmonize multibeam, a fiber array adjustment is designed. By theoretical, simulated and experimental study, the antenna＇s qualitative feasibility is validated.

Health monitoring by optical fiber sensing technology for rechargeable batteries

With the proposal of a“smart battery,”real-time sensing by rechargeable batteries has become progressively more important in both fundamental research and practical applications.However,many traditional sensing technologies suffer from low sensitivity,large size,and electromagnetic interference problems,rendering them unusable in the harsh and complicated electrochemical environments of batteries.The optical sensor is an alternative approach to realize multiple-parameter,multiple-point measurements simultaneously.Thus,it has garnered significant attention.Through analyzing these measured parameters,the state of interest can be decoded to monitor a battery's health.This review summarizes current progress in optical sensing techniques for batteries with respect to various sensing parameters,discussing the current limitations of optical fiber sensors as well as directions for their future development.

Electromagnetic and Optical Methods for Measurements of Salt Concentration of Water

Sensors for monitoring the salinity of water are useful tools in both environmental sciences and chemical engineering. Sensors based on a large variety of principles have been developed. Here we describe the design and testing of two different, noninvasive measurement methods for monitoring the salt concentration of water. The first method is based measurements of the refractive index using a folded-path optical refractometer, while the second utilizes an electromagnetic resonator, consisting of a magnetic coil and a capacitor, which is brought to resonance by an external magnetic field source. It is demonstrated that the folded-path optical refractometer allows one to monitor changes in salt concentration down to 1 mM in the range between 0 and 0.7 M, whereas the electromagnetic resonator has the capability of monitoring concentration changes as small as 0.3 mM over the more limited range between 0 and 5 mM.

PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform

Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral in-formation, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be im-proved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transfor-mation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar （ASAR） loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensi-ty-saturation （HIS） space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue （RGB） space, and the optical image from the China-Brazil Earth Resources Satellite （CBERS-02B） was transferred from the RGB space to the HIS space. The principal component analysis （PCA） method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice identification.

Experimental study on the deformation and failure mechanism of overburden rock during coal mining using a comprehensive intelligent sensing method

Understanding the spatiotemporal evolution of overburden deformation during coal mining is still a challenge in engineering practice due to the limitation of monitoring techniques. Taking the Yangliu Coal Mine as an example, a similarity model test was designed and conducted to investigate the deformation and failure mechanism of overlying rocks in this study. Distributed fiber optic sensing(DFOS), highdensity electrical resistivity tomography(HD-ERT) and close-range photogrammetry(CRP) technologies were used in the test for comprehensive analyses. The combined use of the three methods facilitates the investigation of the spatiotemporal evolution characteristics of overburden deformation, showing that the mining-induced deformation of overburden strata was a dynamic evolution process. This process was accompanied by the formation, propagation, closure and redevelopment of separation cracks.Moreover, the key rock stratum with high strength and high-quality lithology played a crucial role in the whole process of overburden deformation. There were generally three failure modes of overburden rock layers, including bending and tension, overall shearing, and shearing and sliding. Shear failure often leads to overburden falling off in blocks, which poses a serious threat to mining safety. Therefore, realtime and accurate monitoring of overburden deformation is of great significance for the safe mining of underground coal seams.

Deformation and failure characteristics of sandstone under uniaxial compression using distributed fiber optic strain sensing

This paper investigates the deformation and fracture propagation of sandstone specimen under uniaxial compression using the distributed fiber optic strain sensing(DFOSS)technology.It shows that the DFOSS-based circumferential strains are in agreement with the data monitored with the traditional strain gage.The DFOSS successfully scans the full-field view of axial and circumferential strains on the specimen surface.The spatiotemporal strain measurement based on DFOSS manifests crack closure and elastoplastic deformation,detects initialization of microcrack nucleation,and identifies strain localization within the specimen.The DFOSS well observes the effects of rock heterogeneity on rock deformation.The advantage of DFOSS-based strain acquisition includes the high spatiotemporal resolution of signals and the ability of full-surface strain scanning.The introduction to the DFOSS technology yields a better understanding of the rock damage process under uniaxial compression.