In the research field of photonic crystal (PC) devices,there is a lack of research on multifunctional devices.This article proposes a two-dimensional square lattice photonic crystal wave guide structure of beaming of light emitting with filtering function.The output port of this structure is in a stepped horn shape,through the interference between the radiation wave and the surface wave generated by the contact horn surface,the light beaming is enhanced,and the effective propagation distance is greatly increased.In addition,there are two coupled filters at the front end of the horn opening,respectively filtering the center wavelength of 1.505 μm and 1.516 μm narrow band,filtering efficiency reaching 99.64% and 99.02%.Through the structural design of the above two parts,when the wavelength of the incident light is not in the narrow band range of 1.505 μm and 1.516 μm,the induced beaming of light emitting will be greatly enhanced.According to the finite-difference time-domain analysis,the effective propagation distance of the structure reaches 111.4 μm when the input wavelength is 1.460 μm.

In this paper,a strain sensing characteristic of fiber Fabry-Perot (F-P) micro-cavity fabricated by hydrofluoric acid (HF) chemical etching method in ultra-low temperature liquid nitrogen environment was presented.The groove structure was obtained by corroding the end face of the single-mode fiber with a concentration of 20% HF solution for 15 min,and the corroded end was welded with the single-mode fiber with the other end face cutting flat to form flat an F-P micro-cavity.The F-P reflection spectrum contrast was 7.98 dB and the free spectrum range (FSR) was 17.8 nm.The fiber F-P sensor was pasted on the equal strength girder and placed in liquid nitrogen (-196 ℃) environment,and the strain range was 70—630 με in the experiment.The wavelength of F-P reflection spectrum drifted 4.21 nm in the short-wave direction,the strain sensitivity is -7.17 pm/με and the R-squared is 99.928% during the applied strain.The wavelength of F-P reflection spectrum drifted 4.33 nm in the long-wave direction,the strain sensitivity is 7.34 pm/με and the R-squared is 99.923% during the unloading strain.Through the hysteresis analysis of the ultra-low temperature strain response characteristic experiment,it is found that the maximum deviation of applied-unloading strain wavelength drift is 0.17 nm,which proves that the designed sensor has stability and reliability.

Silicon nanowires (SiNWs) prepared by metal-assisted chemical etching (MACE) method have photoluminescence (PL) properties.However,the preparation conditions have great influence on the structure and luminescence properties of SiNWs.To obtain SiNWs with better structural morphology and luminescence properties,the H2O2 concentration,etching temperature and etching time were optimized.The results show that when the concentration of H2O2 in the etching solution is 0.5 mol/L and the temperature is 25 ℃,the etching rate is moderate,the SiNWs have the most uniform and regular structure,and the PL performance is the best.With the increase of etching time,the length of SiNWs and surface oxides show an increasing trend,and the diameter of SiNWs is about 100 nm.The orange-red PL spectrum is believed to be caused by the quantum confinement effect of silicon nanocrystals.With the increase of etching time,the two main luminescence peaks at 633 nm and 699 nm are blue shifted.The SiNWs etched for 4 min have a moderate structure and length,and the luminescence intensity is the strongest,which is an order of magnitude stronger than that etched for 12 min.SiNWs prepared by this method have important application potential in the fabrication of silicon nanostructured based optoelectronic devices.

Currently,power delivery fiber is limited by core diameter and material defects,and the conflict between large-mode-area and outstanding transmission performance in the mid-infrared wavelength range is difficult to solve.In this paper,a seven-tube hollow core anti-resonant fiber (HC-ARF) is proposed,in which the cladding tube is connected to the outsourcing layer in an intersecting manner.The fiber is numerically analyzed by the finite element method with perfectly matched layer (PML) boundary conditions,and the optimal results are obtained by comprehensively analyzing fiber loss and single-mode property.When the core diameter is 120.0 μm,the cladding tube thickness is 0.7 μm,the number of cladding tubes is 7,the cladding tube diameter is 84.0 μm and the outsourcing layer radius is 146.9 μm,the fiber loss is 0.004 dB/m at 3.0 μm,and for wavelength range from 2.5 μm to 3.6 μm,the fiber has a loss below 0.01 dB/m,a mode area over 6 000 μm2 and excellent single-mode property.The proposed hollow core anti-resonant fiber can achieve low-loss single-mode transmission under large-mode-area conditions,which has great potential in the field of mid-infrared power delivery.

A master oscillator power-amplifier (MOPA) type wavelength tunable high-power single-frequency narrow linewidth fiber laser is designed and implemented,in which the oscillation stage adopts a ring-cavity structure,and the tunable fiber Fabry-Perot (FP) filter and self-induction fiber Bragg grating (FBG) filter are used to realize the output of a single-frequency narrow linewidth laser,and the amplification stage is double-cladding gain fiber pumped by a high-power multi-mode laser diode.The 2 m erbium-doped fiber (EDF) pumped by a 980 nm laser diode is used as the gain medium,the dynamic FBG generated by the tunable fiber FP filter and the 2 m unpumped erbium-doped fiber is used as the narrowband filtering device,the 4 m erbium-ytterbium co-doped double-cladding fiber (EYDF) is used as the laser amplification stage gain medium.The wavelength tunable narrow linewidth single-frequency laser output in the range of 1524.35—1566.10 nm is realized,with an average linewidth of 12.7 kHz and a laser output power of 1.16 W,which significantly improves the output power of the tunable narrow linewidth laser.

This paper proposes and prepares a new Mach-Zender interferometric sensor for structural health monitoring of solid rocket motors.The sensing structure is composed of a multimode fiber,an oxide-doped fiber and a multimode fiber (MMF),which are fused by hand in turn.Wherein the doped fiber is a sensing unit,the fiber core of the doped fiber is mainly formed by doping Y2O3,Al2O3 and P2O5,and the refractive index (RI) of the fiber core presents linear-like distribution.The theoretical model of the sensor is established,and the optical field transmission characteristics of the sensor are analyzed.The sensor samples are developed.Temperature,bending and strain experiments are carried out.The results show that the temperature,bending and strain sensitivities of the sensor are 57 pm/℃,9.41 nm/m-1 and 3 pm/με,respectively.Compared with the same type of sensor,the sensitivity is greatly improved,and the sensor shows different spectral characteristics.The sensor has the advantages of simple preparation process and compact structure,and can be applied to the measurement of multiple parameters such as temperature,bending and strain.

Aiming at the problem that it is difficult to accurately detect irregular defects on the surface of lead frames,a method for detecting defects on the surface of lead frames is proposed by integrating attention and multi-level residuals.First,a multi-scale global attention module is proposed to further acquire the global information of the lead frame and improve the segmentation accuracy by capturing the channel and spatial information of the defective edge region.Then,in order to realize the multi-scale fusion of defect information,a multi-level residual fusion attention network module is designed to extract the global semantic information of surface scratch defects.In addition,the encoder employs a smooth maximum unit (SMU) activation function to improve the detail missing phenomenon during detection.The comparative experimental results indicate that the mean intersection over union (MIoU) metrics of the proposed lead frame surface defect detection method are improved by 25.05%,26.79%,12.11% and 21.02% compared with the four typical methods on the homemade lead frame surface defect dataset,respectively.The ablation experiments prove that the proposed method has better defect detection performance and can obtain more effective defect information.

Existing CNN (convolutional neural network)-based image super resolution reconstruction methods are usually realized on full-resolution or progressively low-resolution image representations.The former can achieve the spatially accurate but contextually weak super-resolution reconstruction result,while the latter can obtain the semantically reliable but less spatially accurate output.To solve the above-mentioned problems,a new super-resolution reconstruction model and method based on across-multi-resolution information flow and multiple attention mechanism (AMRMA) is proposed in this paper.Multi-scale feature extraction and aggregation are realized by using cross-multi-resolution information flow and information interaction mechanism.Multiple attention mechanism is used for capturing context information to enhance image high-frequency information.A new weighted loss function is designed to optimize the model parameters.The experimental results on five public datasets show that,compared with classic and existing methods,such as Bicubic,SRCNN,VDSR,RDN and MuRNet,the peak signal-to-noise ratio (PNSR) and structural similarity (SSIM) of the proposed method are improved by 0.33 dB and 0.004 8,and the proposed method has better super-resolution reconstruction effect.

To address the scarcity of power meter detection data,significant distribution differences between generated and real data,and the weak generalization ability of feature extraction networks,an unsupervised object detection algorithm based on data generation is proposed.Firstly,a large number of annotated power meter images are generated using a text-to-image model.Then,a domain adaptation strategy based on sample mixing is proposed,where real images with high-confidence output are selected and spliced with generated images for mixed training,which can mitigate the negative impact of the distribution differences between generated and real data.Finally,a mask consistency module is added to enable the model to learn more universal feature representations and improve its generalization ability in unknown scenarios.The test results show that the algorithm improves the mean average precision (mAP) by 14.1% compared with networks trained only on generated images and outperforms the existing classic domain adaptation algorithm SWDA Faster R-CNN (strong-weak domain adaptation Faster R-CNN) by 10.9%.

To address the problems of poor adaptability and weak security in the encryption of remote sensing images,this paper proposes a multi-band remote sensing image encryption algorithm based on a novel two-dimensional chaotic system.First,to enhance the randomness of the chaotic sequence,we design a new two-dimensional chaotic system using Cubic and Sine mappings.Experiments verify that its performance surpasses that of previous chaotic systems.Second,to enhance the performance and security of the shuffling and diffusion phases in the encryption algorithm,we introduce a pixel replacement method based on the characterics of cyclic groups.Furthermore,this algorithm fully leverages the multi-band characteristics of remote sensing images and optimizes the encryption effect by enabling each band to cross-confuse with others during the encryption process.Experimental results demonstrate that the algorithm offers a large key space and high security,making it resilient to common cryptanalytic attacks.

Addressing the issue of imbalanced data acquisition in circuit breakers,this study adopts the Mahalanobis distance-based modified synthetic minority over-sampling technique (MSMOTE) for data augmentation to achieve efficient fault diagnosis for circuit breakers.Additionally,the firefly algorithm (FA) is utilized to optimize the number of nodes in the hidden layers and learning rate of convolutional neural network-long short-term memory (CNN-LSTM).The data expanded by the MSMOTE algorithm is input into the FA-CNN-LSTM model for training and classification.Experimental results indicate that the proposed method can efficiently diagnose circuit breaker faults even in scenarios with limited fault samples.With the optimization by the FA algorithm,the classification accuracy reaches 99%.Therefore,the circuit breaker fault diagnosis method proposed in this study exhibits excellent performance,offering a novel and effective approach for the analysis of power grid equipment status.

In order to study the impact of X-ray flares caused by solar activities on the communication performance of the quantum satellite-terrestrial link,this paper constructs an ionospheric electron density increment model based on Chapman theory,and obtains the ionospheric extra attenuation factor about the X-ray flares radiation flux and the solar zenith angle based on this model.The variations of mean-based weighted channel capacity,interval-based weighted channel survival function,quantum channel establishment rate and quantum key distribution (QKD) system bit error rate (BER) with X-ray flares radiation level are analyzed by simulation.The results show that under the interference of X-ray flares,the maximum increment of electron density in the ionosphere can be as high as 2.78×106 cm-3.The mean weighted channel capacity attenuation is 0.142 bit/s when the photonic quantum signal passes through the ionosphere with a thickness of 1 km and the X-ray flare radiative flux increases from 10-5 W/m2 to 10-4 W/m2.When the X-ray flares radiation flux increases from 10-5.5 W/m2 to 10-4.25 W/m2,the interval-weighted channel survivor function decays from 0.986 to 0.799,and the ability of the channel to maintain high efficient service state decreases significantly.When weighted channel fidelity F′=0.92,the channel establishment rate decays from 18 pairs per second to 7 pairs per second as the X-ray flares radiation flux increases from 10-5.2 W/m2 to 10-4.4 W/m2 ,when the signal transmission distance is 6 km.When the transmission distance is 15 km and the X-ray flares radiation level is heavy,the BER of the key distribution system is as high as 0.021,and the BER increases with the increase of electron density.Therefore,the impact of X-ray flares on the satellite-terrestrial quantum communication link should not be ignored,and the parameter indexes of the quantum satellite can be adjusted appropriately according to the radiation level of X-ray flares to ensure the reliability and effectiveness of the communication.

In MRR (modulating retroreflector) FSO (free-space optical) communication system using the MCCRA (micro corner-cube reflector array) as a retro-reflector,the PPCE (pseudo phase conjugation effect) is formed to reduce the atmospheric effect,and however,there is lack of systematic study of the simulation method,statistical model and performance analysis for this typical double-pass channel.This paper introduces a simplified realization of double-pass wave-optics simulation for the MCCRA channel,and the fading of the MCCRA-based MRR FSO channel is statistically studied using this simulation method.Through comparing the composite channel models based on double lognormal and double GG (Gamma-Gamma) distributions,the results show that the double GG model is more suitable to describe the MCCRA-based MRR FSO double-pass channel.The average system BER (bit error rate) is evaluated with the aid of the double GG model,and we first verify the performance gain of PPCE is larger than the performance impairment of channel correlation.