The application of near infrared spectroscopy (NIRS) in plastic sorting aims to identify plastic types and components, improve recycling efficiency, reduce environmental impact, and finally realize comprehensive utilization of resources. This paper firstly introduces the traditional sorting technology of plastics. Secondly, the principle of near infrared detection technology and its application in the field of plastics are summarized. Finally, the application prospect in the field of plastic separation is summarized and prospected. In the field of plastic sorting, compared with the traditional physical and chemical detection methods, near infrared spectroscopy detection technology has obvious advantages such as fast, non-destructive and efficient, and can identify and sort the tested object through real-time and online detection, qualitative and quantitative ways. Although the technology has achieved remarkable stage results in some experimental studies, it still needs further research and optimization in practical engineering applications, especially in the accuracy of detection and new application scenarios.

In this paper, the structure and kinetic theory of linear compressors for small cryogenic refrigeration machines are introduced, and the research progress of linear compressors in major research units at home and abroad is summarized in the light of the literature and reports in the past 20 years. The key factors affecting linear compressors, such as magnetic circuit design, support technology and clearance sealing technology of linear compressors are concluded. Finally, the current future research trends of linear compressors for infrared detectors are proposed.

Traditional solid-state solid-state lasers are large, heavy, and have high power consumption, limiting their use in space-constrained equipment. Diode-pumped Passively Q-Switched solid-state laser eliminate the need for complex temperature control devices, have a simple Q-tuning mechanism, and are able to meet the requirements of miniaturization and low power consumption for special application scenarios in complex temperature environment. An approach is proposed to realize a 1.06 m laser pulse output based on dual-wavelength LD pumping with a wide temperature range and temperature-free threshold adaption. The corner-cube resonator is designed based on Nd∶YAG crystal, and the effect of the the face-center distance from LD to laser rod on the thermal load is analyzed through the numerical analysis, and the optimal face-centre distance of 4 mm is determined. The variation of laser static energy output in the temperature range of -40 ℃ to 60 ℃ with the same pump power, and influences of saturable absorber with different initial transmittance on threshold pulse width are analyzed through numerical simulation. Result shows that threshold pulse width under 200 s in the temperature range from -37 ℃ to 60 ℃, the lowest point reached 29.4 s. A threshold adaptive adjustment module is constructed with laser pulse real-time detection, and then the experiment setup is established. The experimental results show that the threshold pulse width varies from 40 s to 180 s in the temperature range of -35 ℃ to 60 ℃. Engineering application is realized through adopting the integrated molding process of laser cavity and the lightweight aluminum, the volume is 83.5 mm×44 mm×29.5 mm and the weight is about 230 g. Single pulse output energy of 42 mJ is achieved under the condition of a saturated absorber with an initial transmittance of 23.8%, with a pulse width of 5.2 ns.

In practice, the output energy stability of a light source affects the reliability and performance of the light source in various applications, such as laser therapy, spectral analysis, photoelectric countermeasures, and optical imaging. In this paper, the output energy stability of the optical parametric oscillator (OPO) system is first analyzed from three aspects, laser pumping source, resonant cavity structure and nonlinear crystal. Experimentally, a pulsed laser-pumped 3~8 m mid-infrared OPO radiation source is constructed using a BaGa4Se7 (BGSe) crystal, and the output energy fluctuation is measured and analyzed in detail from both the laser pumping source and the OPO system. When the input pump energy is 30 mJ and the positive-incidence output is 4.5 m, the average energy is 2.151 mJ with a standard deviation of 56.49 J, and the calculated RMS fluctuation is 2.62%. According to the analysis, it is concluded that the fluctuation of the output pulse decreases with the increase of the laser gain and the decrease of the cavity loss. This study provides a useful guide for the selection of operating parameters of infrared radiation sources with BGSe crystals in different application scenarios.

Recently, high-power linearly polarized narrow linewidth fiber lasers are widely applied in coherent detection and wavelength beam combining. Inhigh-power linearly polarized narrow linewidth fiber lasers, the effect of mode instability (TMI) is one of the mainfactors limiting its power increase. In this paper, the influence of TMI effect on the output power of high-power linearlypolarized narrow-linewidth fiber laser is analyzed, and the suppression method of TMI effect is proposed. Long-wavepumping technologies are used in this article. A single frequency laser with an output power of 100 mW is used as theseed source. And the phase modulator broadens the linewidth of the seed source to 23 GHz. After three stageamplification, the linewidth of 23 GHz, power of 2.2 kW, and center wavelength of 1064nm are finally realized. Linearlypolarized narrow linewidth fiber laser output with extinction ratio of 98% is achieved. Beam quality is Mx2=1.2 and My2=1.21. The influence of the pump wavelength on the TMI effect is analyzed. Due to the small core diameter of thefiber (20 m), a high absorption coefficient of the gain fiber for the pump light (1.8 dB/m@976 nm), the core temperatureis high. And the heat introduced by the pump photo quantum defect, causes the refractive index of the fiber core tochange. Finally, the TMI effect occurs at lower power. When the pump wavelength is shifted to the long wavelength, thequantum defect of the pump light and the pump absorption coefficient are both reduced. The heat distribution on theentire length of the fiber or on the unit length is reduced. The TMI threshold is increased. And the output power of thelinearly polarized narrow linewidth fiber laser is improved.

In slow speed rendezvous simulation test on one channel of each of the two laser fuzes, it is found that the start-up performance of the two channels under the same rendezvous conditions differs greatly. In this paper, the performance of of two fuzes' transmitting and receiving components are tested and compared with the distance cut-off test results. It is found that the performance of two fuzes' receiving components is comparable in terms of responsiveness, and the optical power of transmitting components has a greater impact on the cut-off distance of the fuzes.

In order to research the influence of process parameters on the etching depth of K424 high temperature alloy during water-jet guided laser (WJGL) processing, etching experiments on K424 high-temperature alloy are carried out on the influence of three key process parameters including laser power, feed rate and number of times of processing. The experimental results show that higher power, smaller feed rate and multiple times of machining produce deeper etching. In addition, the prediction model between laser power, feed rate and number of times of machining and depth of machining is established by using four models, XGBoost, RF, BPNN and SVR. The XGBoost and SVR models outperform in terms of fitting effect, with the maximum percentage of error being less than 0.3%; in terms of prediction results, it shows that XGBoost has a maximum percentage of error percentage of 6.698%, which is better than the other three models. Finally, it is concluded that XGBoost model has better performance in fitting and predicting the depth of machining of K424 high temperature alloy. The water-jet guided laser processing technique reduces material thermal damage and improves processing quality compared to conventional dry laser processing. This study provides a reference for water-guided laser processing of K424 high-temperature alloy.

In the process of online monitoring of H2S gas concentration, due to its strong adhesion, it is easy to occur pipeline adsorption, resulting in deviations in measurement results, especially in the process of trace H2S detection. Therefore, it is particularly necessary to study the surface adsorption characteristics of H2S gas pipeline materials. In this work, a set of online H2S concentration measurement system is designed and constructed based on tunable diode laser absorption spectroscopy (TDLAS), and the measurement performance of the system is tested. On this basis, the adsorption characteristics of H2S on the surface of stainless steel materials at room temperature are investigated. The experimental results show that the online H2S concentration determination system has the characteristics of strong stability, low detection limit and high sensitivity, and can be used to achieve on-line continuous determination of trace H2S concentration. After a series of experiments, it is proved that H2S has obvious and stable adsorption effect on the surface of stainless steel material, and the adsorption capacity per unit area of H2S on the surface of stainless steel material is 1014(PCS/cm2). The experimental results can provide a certain reference for on-line accurate measurement of trace hydrogen sulfide.

The laser cladding technology is used to clad Fe-W-B ternary boride cladding layer on 65Mn steel surface. Through the experiments of single-pass cladding and single-layer multi-channel cladding, the effects of laser power, scanning speed, powder feeding rate and lap rate on the quality of cladding layer are explored to obtain the optimal combination of laser process parameters. The cladding layer is analyzed by optical microscope, X-ray diffractometer and Vickers hardness tester. The results show that the influence of process parameters on the height of the molten pool and the width of the molten pool are in descending order: powder feeding rate, scanning speed and laser power, and the influence on Vickers hardness is in descending order: scanning speed, powder feeding rate and laser power. The optimal combination of process parameters is obtained as follows: laser power of 800 W, scanning speed of 3 mm/s, powder feeding rate of 4 g/min, lap rate of 50%. The average Vickers hardness of the cladding layer is 757.9 HV, which is 3.5 times that of the substrate. The cladding layer is well combined with the metallurgy of the substrate, and its microstructure consists of dendritic crystals, cytocrystals and columnar crystals.

In order to solve the problem of poor adaptivity of the cloth simulation filtering (CSF) algorithm, an improved CSF algorithm (WOA-CSF) based on the whale optimization algorithm (WOA) and adaptive parameter tuning is proposed. In this paper, a fitness evaluation function based on the minimum error rate of misclassified point clouds as the criterion is constructed, then the WOA algorithm is used to adaptively optimize the four parameters of the CSF algorithm, and the WOA-CSF filtering algorithm is constructed, and finally the comparative study of the filtering experiments of the WOA-CSF algorithm and the CSF algorithm is carried out. The experimental results show that the average Kappa coefficient of WOA-CSF algorithm in four complex environments such as cities, towns, villages and mountainous areas improves from 68.33% to 81.54%, the average total error rate decreases from 10.54% to 6.62%, and the average class I error rate decreases from 25.87% to 6.77%. In the complex scene, the non-ground points are well filtered while the terrain features are retained to a great extent.

In the process of signal processing in the laser Doppler velocity measurement system, the fast Fourier transform is usually used to extract the Doppler frequency shift and calculate the motion speed of the measured object. Due to the influence of spectrum leakage and barrier effect, the measurement accuracy can be reduced. In this paper, a hybrid convolution window function with a four-term Nuttall window and a five-term Rife Vincent window combined with an improved six spectral line interpolation algorithm is proposed to reduce the effects of spectrum leakage and barrier effects, so as to improve the accuracy of laser Doppler signal processing. A dual-beam backscattering differential laser Doppler velocimetry platform is built, and the minimum relative error measured with this hybrid convolution window with the addition of Gaussian white noise with RSN=-10 dB is 0.0027% by simulation and real measurements, whereas the minimum relative errors measured using the two single window functions are 0.0103% and 0.0461%, respectively. Thus, the effectiveness of this method is verified.

As the quality of CdZnTe substrate for high performance HgCdTe infrared detectors continues to improve, the development of high quality CdZnTe substrate materials is imperative. The substrate high temperature heat treatment process with vacuum high temperature heat treatment temperature field and source control is used to systematically study the influence of the main heat treatment parameters on the Zn component in CdZnTe substrates. An empirical formula for controlling the Zn component in heat treatment is given to preliminarily obtain the compositional control of the Zn component in the CdZnTe substrate and the method of high-component uniformity distribution, which improves the quality of the CdZnTe substrate.

A complete infrared detector consist a detection device, readout circuit, and package structure and refrigeration component. At present, according to different application scenarios, the detection band range is constantly widening, the detection sensitivity needs to be improved, and the imaging speed requirements are accelerated, which put forward stricter and more complex index requirements for detector design. Among them, the readout circuit converts the detection optical signal into an electrical signal for transmission to the system, and is the key core module of the detector component. In this paper, an infrared focal plane detector reading circuit corresponding to a multicolor laminated quantum well device is designed, which is capable of detecting four-band signals at the same time and read them out at the same time, and there is no mutual interference between the detecting integrals of the four-band signals and the readout. The detector specification is 640×512, with a range of 50 m, the signal of each band can be achieved by time integration, respectively adjusted. Adopting the work mode of integrating while reading out, the readout frame frequency can reach ≥50 Hz in four-band detection, the circuit noise ≤0.5 mV, the dynamic range ≥70 dB, power consumption ≤600 mW, which is an ultra-large-scale, low-noise, high-frame-frequency, high-performance readout circuits.

InAs/GaSb type-II superlattice (T2SL) infrared detectors have great advantages in the field of long-wave infrared detection due to their broad-band detection capability, high material uniformity, suppressed Auger recombination rates and flexible energy band design. However, the performances do not reach the theoretical prediction due to the large dark current. The pBn structure is designed to add a monopole barrier between the absorption layer and the contact layer of the detector to suppress the G-R dark current and tunneling dark current. In this paper, the superlattice band structure of absorption layer, barrier layer and contact layer are studied theoretically separately. This study simulates a InAs/GaSb T2SL with pBn structure and study its doping concentration of the absorption layer, the doping concentration of the barrier layer and the thickness of the barrier layer to reduce the dark current. Through optimizing the doping concentration of the absorption layer, the thickness and the doping concentration of the barrier layer, the pBn structure InAs/GaSb T2SL with dark current density of 8.35×10-7 A/cm2 is obtained, which reduces the dark current by one order of magnitude as compared with that of the structure before optimization. The research process not only provides guidance for designing the low dark current with pBn structure device, but also develops a systematic method to optimize the dark current of superlattice device.

According to the current influence of temperature changes on the detection range of airborne infrared search and tracking (IRST) systems, the changes of target and background radiation contrast, atmospheric transmittance, optics, and detector performance with temperature in the detection process of the system are modeled and analyzed. Based on this, the idea of dynamically setting of the threshold noise ratio according to the temperature change is proposed, and the specific setting algorithm is given. The detection probability envelope under the optimized threshold-to-noise ratio and the traditional constant threshold-to-noise ratio conditions is further simulated and compared, and the results show that he detection envelope of the former increases significantly, indicating that the method of setting the threshold-to-noise ratio according to the temperature can significantly improve the detection performance of IRST.

The infrared imaging simulation of aircraft requires temperature field distribution under different flight conditions. In this study, the Standard k- Model, SST k- model and S-A model are used to simulate the temperature field of the aircraft respectively, and the simulation accuracy and difference of the temperature field of the three turbulence models at different flight speeds and flight heights are studied. Further comparison with the theoretical values is made to select a suitable simulation model of the temperature field of the aircraft, in order to provide an important reference for the infrared imaging simulation of the aircraft. Firstly, MutiGen Creator software is used to establish the three-dimensional geometric modeling of the aircraft. Secondly, surface mesh and volume mesh are generated in Hypemesh software and fluent mesh software in turn. Finally, Fluent 2022R1 software is used to simulate the static temperature field distribution of the vehicle, and the temperature field of the vehicle is simulated under different flight speeds and different altitudes by changing the turbulence model and the boundary condition settings, and compared with the theoretical results. By changing the turbulence model and boundary condition settings, the temperature field of the aircraft at different flight speeds and different altitudes is simulated numerically and compared with the theoretical results. The experimental results show that the three turbulence models can simulate the temperature of the inner wall of the nozzle and the skin of the aircraft better. The temperature of the skin of the aircraft rises with the increase of the flight Mach number, and decreases with the increase of the flight altitude, which is consistent with the theoretical results. In the tail nozzle inner wall surface temperature simulation, three kinds of turbulence model simulation of the inner wall surface temperature of the highest difference of 21 K, the relative error in 1.8% or so, in the infrared simulation of the approximate negligible, so the three kinds of turbulence model are suitable for tail nozzle inner wall surface temperature field simulation. And it can better simulate the effect of aerodynamic heating on the temperature field of the vehicle. The model is more accurate and more suitable for the simulation of the flow field of the aircraft, which can better simulate the effect of aerodynamic heating on the temperature field of the aircraft.

Target tracking is a basic function of photoelectric equipment. In order to cope with the impact of fast target movement, complex background interference and occlusion in tracking tasks, an infrared target tracking algorithm using deep learning is proposed in this paper, which is different from traditional generative methods and kernel correlation filtering methods. The input is mapped using a double-branch Siamese network into a higher dimensional space of features, and the image blocks in video frames divided by anchors are sent into the "classification" and "regression" branches of the regional proposal network. Then, correlation calculations will be conducted on "classification" branch to evaluate the matching scores between features from the template image and the search image, producing a matrix of scores for every anchor generated. The best anchor is selected after the score evaluation, and the target tracking prediction box is determined after the boundary regression from that anchor with the information of "regression" branch. An infrared single-light macro single-target tracking algorithm meeting the real-time requirements is proposed. This approach can be obtained by training the overall system parameters end-to-end completely offline, is simple to produce, and has full potential for performance that can be exploited with proper parameter fine-tuning of the methodology.

In this paper, a composite realization method is designed which using a three-axis flight motion table simulates the bomb's attitude and the movement of line of sight in the multi-mode combined guidance system. Firstly, the technical principle of the synthetic line of sight method and coordinate system is summarized, the angular velocity vector conversion and its mapping relationship between software and hardware space is given. The realization process of the synthetic target line of sight semi-physical simulation is investigated, and the methods of solving the drive data of the three-axis simulation rotary table and injecting angular velocity into the line of sight of the guide head stabilizing loop are deduced. Finally, the mathematical simulation of the synthetic target line of sight method is carried out. The optical axis motion law of the guide head tracking the target as well as the target deviation angle and the command output of the bullet eye line-of-sight angular velocity are consistent compared with the real line-of-sight simulation method, which providing a new emulation means for the support application of the bullet eye line-of-sight motion in the semi-physical simulation of the multi-mode composite guidance, as well as the simulation application of the method to provide technical support.

With the continuous development and application of USV technology, its threat to ships is increasing. In order to improve the recognition performance of multi-component laser/infrared/millimeter wave detector on small surface targets, a composite detection signal recognition method MCCNN-XGB based on multi-channel convolutional neural network (Multi-Channel Convolutional Neural Network, MCCNN) and extreme gradient lifting decision tree (Extreme Gradient Boosting, XGBoost) is proposed. At the same time, a single channel CNN recognition network and XGBoost recognition algorithm based on artificial feature extraction are constructed as a comparison. Then, the target recognition performance of the above three models is evaluated and compared through the test data of UAV mount USV target. The test results show that the recognition algorithm based on MCCNN-XGB performs the best, with a test accuracy of 97.26%. The recognition method proposed in this paper can effectively extract the features of the complex detection signal, and can reduce the false recognition rate and missing recognition rate, which has a good recognition effect.

In this paper, a large array high-resolution triple-zoom double telecentrica large front array high-resolution triplex double telecentric optical system is designed for surface defect detection of chips in the plastic encapsulation. Through the analysis of telecentric model and aberration optimization, a dual telecentric optical system with a large field of view, high precision, variable magnification and low distortion is obtained. The system uses a 6500 W pixel industrial camera consisting of 13 spherical lenses operating in the visible wavelength range with an F-number of 7, and magnification of -0.305x,-0.427x and -0.500x, with an overall length of the system of less than 362mm. The design results show that the full-field-of-view modulation transfer function under different magnification is greater than 0.1 at the Nyquist frequency of 156 lp/mm, the maximum distortion is no more than 0.2%, and the telecycenter of the object is less than 0.2°. The optical system has good imaging quality, which has certain reference value of reference in the field of optical design for the detection of defects on the industrial surface.

Aiming at the problems of low contrast, unhighlighted detail information and poor overall sharpness of wide dynamic range infrared images in terms of visual effects, a wide dynamic range infrared image detail enhancement algorithm based on the guided filter layering is proposed in this paper. The original image is layered using variance decision weighted guided filtering to obtain a base layer closer to the original image and a finer detail layer. In order to upgrade the contrast of the base layer, the global clipping point of CLAHE are firstly improved to enhance the enhancement effect, and then the integration of global and local histograms is guided based on the AC visual salience model, giving reasonable consideration to the image background and target. Moreover, to enhance the detail information effectively, a new detail layer with more comprehensive information is obtained based on multi-scale weighted guided filtering, followed by noise cancellation using gradient domain guided filtering, and then the Sigmoid function is used to compress the strong edge and highlight the subtle target, and finally the information of the two layers is fused and output. The experimental results show that the proposed algorithm is stronger than the comparison algorithm in both subjective vision and quantitative indexes, and has strong adaptability and robustness.

As one of the important defects of pavement structure, pavement potholes are of great significance for ensuring the driving safety of autonomous vehicles or the operation of mobile robots. When dealing with pavement pothole detection, challenging computer vision tasks are faced, requiring diverse data samples to be processed under different working conditions. Weather factors such as fog, rain, and snow can negative affect the quality and visibility of road images, which in turn increases the difficulty of data preprocessing and feature extraction. Traditional target detection algorithms are usually difficult to effectively adapt to these scenario variations, resulting in training datasets that do not adequately reflect the diversity and complexity of road potholes, which reduces the generalization ability and accuracy of the target detection model. In practical applications, these methods are prone to lead to omission and misdetection errors, which have an impact on efficiency and quality of road condition identification and evaluation. In this paper, an improved pavement pothole detection algorithm based on YOLOv5 is proposed, which improves the detection accuracy as well as the recall rate of the model. By introducing a simple, powerful but very novel attention mechanism (BiFPN) and replacing the appropriate activation function and loss function, while the calculation parameters are reduced and the detection model is simplified. The experimental results show that the improved algorithm in this paper improves the accuracy (Precision) by 7.2% compared with the original model, the recall rate (Recall) by 5.5%, and the average accuracy (mAP) by 80.8%, which is 2.1% higher than the original YOLOv5 model. In summary, compared with the commonly used traditional algorithms, the improved algorithm in this paper can significantly improve the detection accuracy and reduce the missed detection rate without sacrificing the running speed, which has a better value for mobile deployment and reference value for corresponding research.

Due to various physical and technical limitations, the radiation energy received by different sensors and the amount of data collected vary, and a single sensor cannot simultaneously obtain high spatial and spectral images. Therefore, it is necessary to develop an ideal application-oriented technique for generating multi-spectral image with high spatial resolution. The pan-sharpening method fuses the low spatial resolution multispectral image with the high spatial resolution panchromatic image to obtain a hyperspectral image with rich spatial spectral information. Although significant progress has been made in pan-sharpening methods in recent years, most methods still have two limitations: firstly, limited by network structure and single attention mechanism, global and local features cannot be used simultaneously, resulting in loss of spatial information; secondly, using the Wald protocol to obtain high-resolution multispectral images leads to loss of spectral and detail information. To address these problems, this paper proposes a pan-sharpening framework MAPNet based on multiple attention progressive network. In order to extract more important information, we fully utilize the feature information contained in panchromatic and multispectral images to reduce the interference of redundant information. The low resolution and full resolution phases are closely linked using a progressive pattern. MAPNet trains the ability to extract global information, spectral information and gradient information to reduce the loss of spectrum and detail due to size changes. The multi-attention module combines self-attention, spatial attention and channel attention to achieve multi-modal analysis of global features, local features, spatial features and channel features, thereby further improving MAPNet's ability to retain texture details. The algorithm proposed in this paper is compared with the existing traditional methods BT-H, C-MTF-GLP-CBD, GS, BDSD, PRACS and deep learning methods MUCNN, MDCUN, Band-Aware, PNN and TFNet on the GF-2 dataset. Additionally, this paper records the performance of models with different stages and structures. Objective measurements include RMSE, RASE, SAM, ERGAS, QAVE, SSIM, FSIM, QNR, Ds, D. By combining subjective visual assessment with objective evaluation, the results indicate that MAPNet fusion images retain more spectral and detail information.

In this paper, a wide range of low refractive index (RI) detection surface plasmon resonance (SPR) sensors based on D-ring-shaped side double-core photonic crystal fiber in the mid-infrared band is proposed. A metal layer is deposited on both the inner and outer surfaces of the D-ring. The full vector finite element method is used to analyze the performance of the sensor, and its sensing characteristics are studied. The results show that the sensor can achieve low and high external refractive index sensing sensitivity in the mid-infrared band. The detectable refractive index range of the analyte is 1.20~1.38, and the average wavelength sensitivity and maximum wavelength sensitivity can reach 13717 nm/RIU and 21150 nm/RIU respectively, with a resolution of 1.94×10-5 RIU. The designed sensor plays an important role in the fields of chemical, biological, and environmental detection.