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2021 Vol. 43, No. 2

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Survey & Review
Au-Doped HgCdTe Infrared Material and Device Technology
SONG Linwei, KONG Jincheng, LI Dongsheng, LI Xiongjun, WU Jun, QIN Qiang, LI Lihua, ZHAO Peng
2021, 43(2): 97-103.
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The minority carrier lifetime of p-type HgCdTe materials can be improved significantly by using Au atoms instead of Hg vacancies, which have been considered as deep-level energy recombination centers; consequently, the dark current of n-on-p HgCdTe devices reduced and performance improved. Further, Au doping is helpful for developing high-performance n-on-p LWIR/VLWIR and high operating temperature (HOT) MWIR HgCdTe infrared detectors with high resolution and high sensitivity. In this paper, Au-doped HgCdTe IR material and device technologies were reviewed. Critical processes and the effect of Au doping on the device properties were discussed as well.
Micro-coolers Based on MEMS Technology
TONG Xin, CHEN Xiaoping, LI Jiapeng, XIA Ming, HUAI Yang, CHEN Junyuan
2021, 43(2): 104-109.
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Micro-electro-mechanical systems (MEMS) are a new type of high-tech devices that combine microelectronics and mechanical engineering technology. Their manufacturing process can be highly integrated and conducted at the minimum nanometer scale. MEMS products also require corresponding refrigeration solutions because of their small volume, high integration, high performance, and high heat production. This study focuses on micro-semiconductors and Joule-Thomson (JT) coolers fabricated via MEMS technology that can also be applied to MEMS products. The working principles, performance, and development trends of the micro-coolers are discussed, and the advantages and disadvantages of micro-semiconductors and JT coolers are analyzed, respectively. Additionally, certain suggestions regarding the future development of micro-coolers are provided
Systems & Designs
Analysis of the Influence of Installation Errors of an Infrared Stabilized Platform on Line-of-sight Angular Velocity
CHEN Zheng, FU Kuisheng, DING Haishan
2021, 43(2): 110-115.
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Installation errors of a stabilized platform with a frame structure affect the calculation accuracy of the line-of-sight (LOS) angular velocity. Mathematical descriptions for the axis system deviation of frames are given. Based on these, calculation methods for a three degree- of-freedom infrared stabilized platform are studied under the conditions of axis system deviation and cross coupling of sensitive axes of gyros. The influences on the measuring accuracy of LOS angular velocity caused by these two kinds of installation errors are compared. It is shown by simulation results that compensating for installation errors can effectively improve the measuring accuracy of LOS angular velocity. The results are important for error index decomposition for the design of a late-model-stabilized platform with a frame structure.
Composite Current Control Method for Small Inertia Infrared Stable Platforms
XIONG Hui, LIN Yu, ZHANG Yanwei, LI Ruihua, SHU Junyi, YAN Xinjie, FENG Jianwei
2021, 43(2): 116-126.
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Miniaturization and high dynamics are the development trends of infrared imaging stabilization platform technology. Owing to a small moment of inertia, traditional PI(Proportion Integral)-type current loop control cannot completely overcome the slope interference of the back electromotive force(back-EMF), which will reduce the dynamic response of small inertia infrared stable platforms. Concurrently, balancing dynamics and anti-disturbance performance is another difficulty with regard to high dynamic and small inertia infrared stable platform technology. To solve the a forenoted problems, a composite current control method based on dead-beat predictive control and extended state observation(ESO) is proposed in this paper, which effectively improves the dynamic response and anti-disturbance ability of small inertia infrared stable platforms. Simulation and experimental results show that the composite current control method reduces the settling time of the current loop of a small inertia infrared stable platform by 1/3. It also improves the dynamic performance and anti-disturbance performance of the speed response, and has good performance robustness.
Design of Large Aperture Transmission Ultraviolet Optical System Based on Solar-blind Ultraviolet Image Intensifier
WANG Miaoxin, CHENG Hongchang, LI Jinbo
2021, 43(2): 127-130.
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Based on the AlGaN photocathode solar-blind UV image intensifier developed by the Science and Technology on Low-Light-Level Night Vision Laboratory, this study designs a UV optical system that matches the solar-blind UV image intensifier to improve the detection performance of the detector. The working wavelength of the optical system is 240-280 nm, the field of view is 40°, and the relative aperture is 1/2.5. The system consists of five lenses that are all spherical mirrors, and the total length of the optical system is 50.74 mm. When the optical transfer function is 40 lp/mm, the on- and off-axes are greater than or equal to 0.8 and 0.6, respectively. The imaging quality is good, and the structure is compact to meet the design requirements.
Research on Highway State Detection Based on Visible-Near-Infrared Spectrum
XIONG Xianming, ZHANG Qiankun, QIN Zujun
2021, 43(2): 131-137.
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Spectral technology is a promising prospect for highway state detection(whether frozen, water accumulated, or snow accumulated). However, there is little research on using sunlight as a light source to identify highway states. Sunlight and halogen tungsten lamps were used as experimental light sources in the day and night. Spectral curves of the visible-near-infrared bands of ice, water, snow, and highway backgrounds were obtained using a micro-spectrometer. During the day, the state of icing and stagnant water resulted in a phenomenon known as "Different substances with similar spectra" under different illumination conditions. Then, based on the characteristics of sunlight illumination, the solution of "environmental variables" as eigen values was proposed. The curve of the spectrum and the normalized "environmental variables" were combined into a new data waveform, and a neural network model based on Dropout and an Adam optimizer was established for training and recognition. The final recognition rate was 99.375%. At night, due to the evident differences in the spectra of various samples, the spectral curves of each sample were identified using the "combination-threshold" method. Experiments proved that the method of combining two light sources can effectively identify the road surface state.
Guidance & Countermeasure
Infrared Extinction Calculations of Smokescreen Particles by Moment Method
LIU Qinghai, JIANG Yun, PENG Wenlian, ZHANG Tong, DAI Xiaodong
2021, 43(2): 138-144.
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A moment-method-based infrared extinction model of rotating smokescreen particles is applied to perform calculations entailing three graphite particles including flakes, spheres, and cylinders, mainly focusing on the relationship between extinction ability and particle parameters, such as shape, diameter, and thickness. The calculations suggest that extinction is attributed to absorption when the particle size is small and attributed to scattering when the particle size is large. Flakes exhibit the best infrared extinction performance. When flakes become thinner, their extinction abilities are enhanced. Flakes with 100 nm thickness and 1.5–2.1 μm radius exhibit outstanding extinction performance in the 1–10 μm infrared wavelength range, with an average infrared extinction coefficient as high as 5.0 m2/g.
Image Processing & Simulation
Small Scale Fire Identification Based on Constrained Inhomogeneous Deformation Feature
WANG Xiangjun, DU Zhiwei, GAO Chao
2021, 43(2): 145-152.
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Video based fire detection(VFD) is a convenient, low-cost method widely used in fire detection. However, it's not credible enough to distinguish true fire from possible disruptors by traditional fire features. This paper extract two new features to analyze the time series behavior of fire based on the motion of edge pixels. The inter frame behavior of edge pixels is regarded as a nonuniformty constrained deformation procedure. Combined with HMM and additional geometric features to distinguish true fire from possible disruptors, the accuracy of fire detection is greatly improved and the false alarm rateis efficiently reduced.
Classification and Recognition Algorithm for Long-wave Infrared Targets Based on Support Vector Machine
WANG Zhouchun, CUI Wennan, ZHANG Tao
2021, 43(2): 153-161.
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Infrared images have a low resolution and a single color, but they play an important role in some scenes because they can be used under all weather conditions. This study adopts a support vector machine algorithm for long-wave infrared target image classification and recognition. The algorithm extracts edge and texture features, which are used as the recognition features of the target, and forwards them to a support vector machine. Then, the target category is output for infrared target recognition. Several models, such as the histogram of oriented gradient, gray level co-occurrence matrix, and support vector machine, are combined to collect images of eight types of target scenes for training and testing. The experimental results show that the algorithm can classify the same target person wearing different clothes with high accuracy and that it has a good classification effect on different target characters. Therefore, under certain scene conditions, this combined algorithm model can meet the needs and has certain advantages in the field of target recognition.
Infrared and Visible Light Image Fusion Based on Mahalanobis Distance and Guided Filter Weighting
LIU Jia, LI Dengfeng
2021, 43(2): 162-169.
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To improve the definition of fusion images and obtain better target information during the fusion of infrared and visible light images using the characteristics of non-subsampled contourlet transform(NSCT) coefficients, an Manalanobis distance weighted Laplacian energy combined with guided filtering is proposed to improve the frequency tuned (FT) algorithm. First, the visible light image is subjected to contrast limited adaptive histogram equalization(CLAHE), and the infrared image and the CLAHE processed visible light image are decomposed into a low-frequency approximate image and a high-frequency detail image through a multi-scale and multi-directional NSCT transform. Second, the FT algorithm improved by guided filtering isused to extract the significance graph of infrared images, the adaptive weighted fusion rule based on the significance graph of infrared images is used for low-frequency images, and the fusion rule based on the Laplace energy and maximum weighted by the Manalanobis distance is used for high-frequency images. Finally, the fusion image is obtained by the NSCT inverse transformation of the fused low-frequency and high-frequency images. The experimental results show that this fusion method has better performance in terms of subjective vision and objective indexes than other traditional fusion methods.
Infrared Ship Target Detection Algorithm Based on Improved Faster R-CNN
GU Jiaojiao, LI Bingzhen, LIU Ke, JIANG Wenzhi
2021, 43(2): 170-178.
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To solve the problem of insufficient feature extraction and repeated detection of infrared ship targets by the Faster R-CNN algorithm, a ship target detection algorithm based on an improved Faster R-CNN is proposed. First, three feature graphs are drawn from the backbone network, VGG-16, after a three-segment convolution, and the features are spliced to form a multi-scale feature graph to obtain a feature vector with richer semantic information; second, the Anchor is improved based on the dataset, and the number and size of the Anchor boxes are reset; finally, the loss function of the improved Faster R-CNN is optimized to improve the feature extraction ability of the target. An analysis of the experimental results on the test dataset demonstrates that the average accuracy of the improved detection algorithm was 83.98%, which is 3.95% higher than that of the original Faster RCNN.
Measurements
Compensation Method for Temperature Distribution Measured by Infrared Thermography for Non-flat Surfaces
FU Wanchao, FAN Chunli, YANG Li
2021, 43(2): 179-185.
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When employing an infrared thermal imager to measure surface temperature, the emissivity of the surface to be measured should be set first and kept constant during the measurement process. However, when the infrared imager is placed in the range of more than 50° of the zenith angle of the points to be measured, the emissivities of the points in this angle will vary significantly; hence, temperature measurement errors will occur, especially for points on non-flat surfaces. In view of the measurement error caused by the variation of emissivity of different points in the measured non-flat surface when using a monocular infrared thermal imager, this paper provides a compensation factor based on the variation rules of the emissivity with the measuring angle. In addition, based on 3D modeling technology, the relationship between the positions of the points in the thermographic image and those in the actual surface is determined. The compensation method of the temperature measurements for a non-flat surface is presented. The feasibility of the method was verified through experiments.
IR Applications
Comparative Study of Using Ultrasonic Infrared Thermography for Detecting Aeroengine Blade Cracks
XI Xiaowen, SU Qingfeng, YUAN Yanni, JIANG Haijun, CHEN Li, WEI Yibing
2021, 43(2): 186-191.
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Owing to the complex curved surface structure of aeroengine blades, it is difficult to detect tiny cracks formed during servicing. In this study, ultrasonic infrared thermography technology was used to detect the blade cracks of an aero engine. Ultrasonic infrared thermal imaging technology was studied, and an experimental platform for ultrasonic infrared thermal imaging was built. In addition, the working blade of an aero engine with cracks arising from actual servicing was detected. The results of ultrasonic infrared thermography were compared with those of osmotic detection and metallographic detection. Experimental results show that in the working blade of the aero engine, ultrasonic infrared thermography technology detected two crack defects and one opening defect, whereas only one crack defect is detected by penetrant testing and two crack defects are detected by a metallographic microscope.The widths are approximately 15 μm and 0.5 μm, respectively, which are consistent with the detection results of ultrasonic infrared thermography. The results show that ultrasonic infrared thermography technology can effectively detect crack defects in aeroengine blades with complex curved surfaces.
A Non-contact Alcohol Measurement Method Based on Neural Network Correction Algorithm
ZHAO Leihong, PAN Dongning, LI Yingjie, SONG Yuanqing, WANG Lei, DU Lihua
2021, 43(2): 192-197.
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This paper presents a non-contact method for the measurement of alcohol gas emission based on the neural network correction algorithm, to mitigate the influence of external factors on the measurement process. The proposed method combines the characteristics of alcohol gas absorption in the infrared spectrum and the nonlinear processing method of the back propagation(BP) neural network algorithm. The algorithm considers the influence of temperature and humidity on light intensity during the gas absorption process and trains it as the input to the neural network and measurement parameters. Simultaneously, the proposed algorithm is compared with the data fitting algorithm, and the experimental results show that this algorithm achieves better results.

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