Infrared Physics & Technology最新文献_第8页

Instrument-invariant near-infrared spectroscopy via domain adaptation for robust quantitative analysis of barley protein content 基于区域自适应的仪器不变近红外光谱对大麦蛋白质含量进行稳健定量分析

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-30 DOI: 10.1016/j.infrared.2026.106436

Gan Zhang , Xu Zhang , Hongyan Li , Jinhui Zhao , Yao Qin , Qinghui Zhang , Mingxing Li , Yu Yang

Near-infrared (NIR) spectroscopy has emerged as a rapid and non-destructive tool for food quality assessment, yet variations among instruments remain a major barrier to its widespread deployment in grain protein prediction. This study introduces a joint domain adaptation–spectral reconstruction–prediction model (JDA-SR-PM) to achieve reliable instrument transfer for online monitoring of protein content in barley kernels. Spectral data were collected from a master and a slave instrument, and the dataset was expanded via unsupervised augmentation. The model was optimized using the Adam algorithm and benchmarked against three state-of-the-art transfer learning methods: TCASVR, PRETL, and PEAMATL. Results demonstrated that JDA-SR-PM achieved superior predictive performance, with R² = 0.923, RMSE = 0.553, and RPD = 3.607 on the test set, outperforming competing approaches. Bland–Altman analysis further confirmed close agreement between predicted and reference protein values, validating the potential of JDA-SR-PM as an alternative to commercial analyzers. SHAP-based feature attribution highlighted critical spectral regions (920 nm, 1200 nm, and 1400–1550 nm), consistent with known chemical overtones, and provided a foundation for simplified instrument design. These findings suggest that NIR spectroscopy combined with domain adaptation can extend rapid protein monitoring beyond laboratory settings, supporting practical applications in grain quality control.

近红外（NIR）光谱已成为一种快速、无损的食品质量评估工具，但不同仪器之间的差异仍然是其在谷物蛋白质预测中广泛应用的主要障碍。为了实现大麦籽粒蛋白质含量在线监测的可靠仪器转移，提出了一种联合域自适应-光谱重建-预测模型（JDA-SR-PM）。光谱数据分别从一台主从仪器采集，并通过无监督增强对数据集进行扩展。该模型使用Adam算法进行了优化，并针对三种最先进的迁移学习方法：TCASVR、PRETL和PEAMATL进行了基准测试。结果表明，JDA-SR-PM具有较好的预测性能，在测试集上R2 = 0.923, RMSE = 0.553, RPD = 3.607，优于竞争方法。Bland-Altman分析进一步证实了预测值和参考值之间的密切一致，验证了JDA-SR-PM作为商用分析仪替代品的潜力。基于shap的特征归属突出了关键光谱区域（920 nm、1200 nm和1400-1550 nm），与已知的化学泛音一致，为简化仪器设计提供了基础。这些发现表明，近红外光谱结合结构域自适应可以将快速蛋白质监测扩展到实验室环境之外，支持谷物质量控制的实际应用。

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引用次数: 0

Ranging method of weak lidar signal based on manta ray foraging optimization and variational modal decomposition 基于蝠鲼觅食优化和变分模态分解的弱激光雷达信号测距方法

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-18 DOI: 10.1016/j.infrared.2026.106412

Tianyi Zhang , Xiaobin Xu , Zerun Sun , Shanshan Chen , Zheng Liu , Yingying Ran , Zhiying Tan

Regarding the difficulty of the detection of Lidar weak echo signal, this paper proposes a ranging method based on MRFO algorithm to optimize the VMD parameters and the peak detection. Based on the analysis of Lidar echo signals, MRFO optimization algorithm was used to calculate the optimal VMD decomposition parameters, and the bhattacharyya distance was combined to reconstruct the echo signal. The ranging was then realized by the peak moment identification method. Simulation analysis was conducted to compare the denoising effects with different VMD parameter optimization algorithms. The experimental platform of a Lidar system was built, and it was demonstrated that the laser echo signal completely submerged in noise can be detected by the proposed algorithm. When the ground truths of distances are 46.964 m and 25.363 m, compared with SVD-WT, WT-ST, EMD-ST and DFA-EMD, the de-noising effect and the ranging accuracy of the proposed algorithm are the best. Even though the time cost of proposed algorithm is higher than that of WT-ST, its success rate can reach 89.3 % with different distances, which is more than 20 % better compared with other algorithms. The proposed algorithm provides technical support for faint signal detection for Lidar remote sensing.

针对激光雷达微弱回波信号检测困难的问题，本文提出了一种基于MRFO算法的测距方法来优化VMD参数和峰值检测。在对激光雷达回波信号分析的基础上，采用MRFO优化算法计算最优VMD分解参数，并结合巴塔查里亚距离重构回波信号。然后利用峰矩识别法实现测距。通过仿真分析，比较了不同VMD参数优化算法的去噪效果。搭建了激光雷达系统实验平台，实验结果表明，该算法可以检测到完全淹没在噪声中的激光回波信号。当地面真实距离为46.964 m和25.363 m时，与SVD-WT、WT-ST、EMD-ST和DFA-EMD相比，本文算法的降噪效果和测距精度最好。尽管该算法的时间成本高于WT-ST算法，但在不同距离下，其成功率可达89.3%，比其他算法高出20%以上。该算法为激光雷达遥感微弱信号检测提供了技术支持。

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引用次数: 0

Generative adversarial translation of RGB to thermal infrared images for enhanced multimodal data 增强多模态数据的RGB到热红外图像的生成对抗转换

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-10 DOI: 10.1016/j.infrared.2026.106367

Huijie Zhu , Qingyuan Zhu , Kai Ding , Hao Tang , Yuchen Li

The combination of visible (RGB) and thermal infrared (TIR) data holds significant potential for all-day-all-night applications. However, research in this area is hampered by the limited size and demanding alignment requirements of multi-modal datasets. To address these challenges, we propose a generative adversarial network (GAN) to translate RGB data into TIR data, thereby significantly expanding the availability of RGBT data and alleviating the need for laborious alignment processes. Our method employs pixel-wise perceptual loss and a multi-scale architecture in the generator and discriminator, respectively, to ensure high-quality TIR data generation. Conditioned on the original RGB data, our model generates TIR data depicting the same scene, providing paired and aligned RGBT data that facilitates downstream tasks. Qualitative and quantitative analyses demonstrate the effectiveness of the generated RGBT data. In a questionnaire, participants found it difficult to distinguish between generated and real data. On the RGBT tracking task, methods trained with generated data performed comparably to those trained with real data, proving the utility and efficacy of our approach. Code is available at https://github.com/NJ587/RGB2TIR.

可见光（RGB）和热红外（TIR）数据的结合具有全天候、全天候应用的巨大潜力。然而，这一领域的研究受到多模态数据集有限的规模和苛刻的校准要求的阻碍。为了解决这些挑战，我们提出了一种生成对抗网络（GAN）来将RGB数据转换为TIR数据，从而大大扩展了RGB数据的可用性，并减轻了费力的校准过程的需要。我们的方法在生成器和鉴别器中分别采用逐像素感知损失和多尺度架构，以确保高质量的TIR数据生成。在原始RGB数据的基础上，我们的模型生成描绘相同场景的TIR数据，提供配对和对齐的RGB数据，从而促进下游任务。定性和定量分析证明了所生成的RGBT数据的有效性。在问卷调查中，参与者发现很难区分生成的数据和真实的数据。在RGBT跟踪任务中，使用生成数据训练的方法与使用真实数据训练的方法表现相当，证明了我们方法的实用性和有效性。代码可从https://github.com/NJ587/RGB2TIR获得。

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引用次数: 0

Infrared low-frequency non-uniformity correction method based on gradient-domain weighted B-spline 基于梯度域加权b样条的红外低频非均匀性校正方法

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-09 DOI: 10.1016/j.infrared.2026.106392

Zexiao Zheng , Yaohong Zhao , Wei Xiang

Low-frequency non-uniformity noise, caused by scene-independent stray thermal radiation incident on the infrared detector, is a common form of additive noise in infrared images. Its presence significantly degrades image quality and adversely affects subsequent image processing and analysis. Due to the complex and diverse origins of such radiation, low-frequency non-uniformity exhibits varying characteristics, while existing correction algorithms generally have limited generalization capability and suboptimal performance. To address this issue, a correction method based on gradient-domain weighted B-spline is proposed. Specifically, non-uniform B-splines are employed in the gradient domain with an adaptive knot placement strategy, which allows the density of B-spline knots to be flexibly adjusted across different regions for accurate fitting. Furthermore, an adaptive gradient-domain filter is designed to robustly extract low-frequency information, with adaptive parameters estimating the noise distribution and better suppressing edges and texture details. To further suppress residual high-frequency components, a weighting scheme based on a second-order derivative prior is incorporated into the model. Experimental results demonstrate that the proposed method achieves superior adaptability and robustness, effectively removing diverse low-frequency non-uniform noise.

低频非均匀性噪声是红外图像中常见的一种加性噪声，是由入射到红外探测器上的与场景无关的杂散热辐射引起的。它的存在大大降低了图像质量，并对随后的图像处理和分析产生不利影响。由于这种辐射的来源复杂多样，低频非均匀性表现出不同的特征，而现有的校正算法一般泛化能力有限，性能欠佳。针对这一问题，提出了一种基于梯度域加权b样条的校正方法。具体而言，在梯度域采用非均匀b样条，采用自适应结点布置策略，使b样条结点的密度可以在不同区域灵活调整，从而达到精确拟合的目的。此外，设计了自适应梯度域滤波器，利用自适应参数估计噪声分布，更好地抑制边缘和纹理细节，鲁棒地提取低频信息。为了进一步抑制残留的高频分量，在模型中加入了基于二阶导数先验的加权方案。实验结果表明，该方法具有较好的自适应性和鲁棒性，能有效去除各种低频非均匀噪声。

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引用次数: 0

Stable high temperature meta-film for visible and infrared compatible camouflage 用于可见光和红外兼容伪装的稳定高温元膜

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-23 DOI: 10.1016/j.infrared.2026.106427

Wenzhuang Ma , Yang Xiang , Gefei Shen , Yujia Zhou , Kewei You , Yang Zhou , Ningtao Wang , Li Zhang

The advancement of multispectral detection has spurred the development of camouflage materials for both visible and infrared spectra. This is especially challenging for hypersonic vehicles, where extreme heat during flight demands highly durable materials. However, research on high-temperature visible-infrared camouflage remains limited. Here, we propose a high-temperature-resistant visible-infrared camouflage strategy. The designed material enables tunable coloration in the visible spectrum while maintaining low infrared emissivity (<0.25) in dual infrared bands (3-5 and 8-14 μm), effectively minimizing thermal radiation leakage. Our findings reveal that the spectral degradation of conventional Pt/Al₂O₃/Pt multilayers at high temperatures primarily stems from film structural degradation and intrinsic material property alterations, particularly the irregular agglomeration of the top Pt layer, which disrupts film continuity and causes unpredictable spectral shifts. By introducing an Al₂O₃ protective layer, we suppress Pt agglomeration, enabling a transition from three-dimensional disorder to two-dimensional order, thereby enhancing spectral predictability. Building on these insights, we propose an innovative pre-aging strategy, wherein the material’s optical properties in a stabilized post-annealing state are reverse-engineered and pre-aged through thermal treatment to achieve the target spectral performance. This approach ensures long-term high-temperature stability for effective camouflage functionality. Experimental results demonstrate that the designed material retains its camouflage efficacy for over 100 hours at 600°C. This study lays the foundation for the intelligent design and fabrication of next-generation high-temperature-resistant camouflage materials for future applications.

多光谱探测技术的进步促进了可见光和红外光谱伪装材料的发展。这对高超音速飞行器来说尤其具有挑战性，因为飞行过程中的极端高温需要高度耐用的材料。然而，对高温可见红外伪装的研究仍然有限。在此，我们提出了一种耐高温的可见-红外伪装策略。设计的材料可以在可见光谱中实现可调的颜色，同时在双红外波段（3-5 μm和8-14 μm）保持低红外发射率（<0.25），有效地减少热辐射泄漏。我们的研究结果表明，传统Pt/Al2O3/Pt多层膜在高温下的光谱退化主要源于薄膜结构退化和材料固有性质的改变，特别是顶层Pt层的不规则团聚，这破坏了薄膜的连续性并导致不可预测的光谱位移。通过引入Al2O3保护层，我们抑制了Pt团聚，实现了从三维无序到二维有序的转变，从而提高了光谱的可预测性。基于这些见解，我们提出了一种创新的预老化策略，其中材料在稳定的退火状态下的光学特性被逆向工程和通过热处理预老化以达到目标光谱性能。这种方法确保了有效伪装功能的长期高温稳定性。实验结果表明，该材料在600℃下可保持100小时以上的伪装效果。该研究为下一代耐高温伪装材料的智能化设计和制造奠定了基础。

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引用次数: 0

NIRS regression model for dry matter content estimation in olive fruit with XGBoost pre-treatment method XGBoost预处理法估算橄榄果实干物质含量的NIRS回归模型

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-05 DOI: 10.1016/j.infrared.2026.106374

Wenyi Sun , Yinji Chen , Zhiqi Gao , Tianyu Li , Xupu Chen , Yizhen Liu , Qiaoyun Wang

Dry matter content (DMC) is a key indicator in evaluating olive fruit quality, particularly in assessing its suitability for oil extraction. The Near-infrared (NIR) spectroscopy combined with machine learning methods is widely used to evaluate the DMC in olive fruit. In this paper, Extreme gradient boosting (XGBoost) algorithm with high efficiency, accuracy and flexibility was used as a preprocessing method to enhance the predictive performance of DMC estimation models. And the prediction result of XGBoost preprocessing with the partial least squares (PLS) and Multi-Layer Perceptron (MLP) models were compared with other widely used preprocessing methods (D¹, D², MA, MSC, SG, SNV, WAVE). Experimental results showed that the XGBoost preprocessing method outperformed other preprocessing methods in predictive accuracy, achieving lower values of root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and standard error of prediction (SEP), and higher ratio of performance to deviation (RPD) and coefficient of determination (R²). Moreover, the XGBoost-MLP model had better performance than that of XGBoost-PLS model. The experimental results demonstrate that the XGBoost preprocessing method achieved better fitting performance than other preprocessing methods.

干物质含量（DMC）是评价橄榄果实品质，特别是评价橄榄果实榨油适宜性的关键指标。近红外光谱技术与机器学习技术相结合被广泛应用于橄榄果实DMC的评价。本文采用高效、准确、灵活的极限梯度增强算法（Extreme gradient boost, XGBoost）作为预处理方法，提高DMC估计模型的预测性能。并将偏最小二乘（PLS）和多层感知器（MLP）模型对XGBoost进行预处理后的预测结果与其他常用的预处理方法（D1、D2、MA、MSC、SG、SNV、WAVE）进行比较。实验结果表明，XGBoost预处理方法在预测精度上优于其他预处理方法，交叉验证均方根误差（RMSECV）、预测均方根误差（RMSEP）和预测标准误差（SEP）均较低，性能偏差比（RPD）和决定系数（R2）较高。此外，XGBoost-MLP模型比XGBoost-PLS模型具有更好的性能。实验结果表明，与其他预处理方法相比，XGBoost预处理方法具有更好的拟合性能。

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引用次数: 0

Defect detection for micro-LED by multi-illumination and deep learning 基于多点照明和深度学习的微型led缺陷检测

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-03 DOI: 10.1016/j.infrared.2025.106357

Qicheng Lin , Zhiguo Xie , Kiyoshi Takamasu , Meiyun Chen

Micro-LED wafer defect detection faces challenges such as weak optical contrast, diverse defect types, and stringent real-time requirements. To tackle these issues, this paper proposes the Multi-illumination Movable Detection System (MIMDS) and DMI-Net. MIMDS uses multi-angle illumination and multi-spectral fusion for higher-quality defect images. DMI-Net integrates three core innovations: Dual Receptive-field Attention Convolution (DRAConv) module that enhances feature extraction while reducing computational cost through grouped and segmented convolution; Mixed Local Channel Attention RepNBottleneck (MRB) that improves small defect recognition via multi-scale feature refinement; and Inner Focaler IoU (IF-IoU) loss function that adapts to sample difficulty for faster convergence and better accuracy. Experiments on VOC2012 and Micro-LED wafer datasets show that DMI-Net achieves mAP scores of 0.754 and 0.893 at 21 FPS, meeting real-time requirements and demonstrating strong reliability.

微型led晶圆缺陷检测面临光学对比度弱、缺陷类型多样、实时性要求严格等挑战。为了解决这些问题，本文提出了多照度移动检测系统（MIMDS）和DMI-Net。MIMDS采用多角度照明和多光谱融合技术来获得高质量的缺陷图像。DMI-Net集成了三个核心创新：双接受场注意卷积（DRAConv）模块，通过分组和分段卷积增强特征提取，同时降低计算成本；通过多尺度特征细化提高小缺陷识别的混合局部通道注意瓶颈（MRB）；以及适应采样难度的Inner Focaler IoU （IF-IoU）损失函数，以实现更快的收敛和更好的精度。在VOC2012和Micro-LED晶圆数据集上的实验表明，DMI-Net在21 FPS下的mAP得分分别为0.754和0.893，满足实时性要求，可靠性强。

引用次数: 0

Thermally tunable terahertz switchable quad-band to broadband absorption induced by Mie–plasmon coupling 热可调谐太赫兹切换四波段到宽带吸收诱导的密离激元耦合

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-02-06 DOI: 10.1016/j.infrared.2026.106447

Shuncong Zhong , Shilin Cheng , Yi Huang , Fuwei Sun , Rongkun Yuan , Qiuming Zeng , Simin Ding , Yujie Zhong , Ziheng Zhou

Metamaterials enabling on-demand switchable terahertz (THz) absorption functionalities are essential for advancing multifunctional integrated photonic devices. However, most existing tunable designs rely on fine-tuning a single dominant resonance mode. This physical mechanism limits their functionality primarily to frequency shifting or intensity modulation, making it difficult to achieve distinct switchable operation between different operating modes. To address this, we propose a vertically integrated VO₂–dielectric microsphere hybrid metasurface absorber. It utilizes the insulator-to-metal transition (IMT) of VO₂ to actively control the coupling between the top-layer VO₂ plasmon resonance and the bottom-layer ZrO₂ microsphere Mie resonance. In the insulating state of VO₂, the coupling is disabled, and the device is dominated by Mie resonances, exhibiting an efficient quad-band absorption mode with each peak absorptivity exceeding 95%. When VO₂ transitions to its metallic state, the coupling is activated, allowing the top-layer plasmon resonance to couple with the bottom-layer Mie resonances. This interaction induces a spectral reconfiguration that merges the discrete high-frequency resonance peaks into a continuous broadband absorption band (0.919–1.157 THz) with an absorptivity exceeding 90%, thereby realizing switchable performance from quad-band to broadband absorption. This design strategy provides a new physical paradigm for realizing intelligent metamaterials with switchable functionalities.

实现可按需切换太赫兹（THz）吸收功能的超材料对于推进多功能集成光子器件至关重要。然而，大多数现有的可调谐设计依赖于对单个主共振模式进行微调。这种物理机制限制了它们的功能主要是移频或强度调制，使其难以在不同的工作模式之间实现不同的可切换操作。为了解决这个问题，我们提出了一种垂直集成的vo2 -介电微球混合超表面吸收剂。它利用VO2的绝缘体到金属跃迁（IMT）来主动控制顶层VO2等离子体共振与底层ZrO2微球Mie共振之间的耦合。在VO2的绝缘状态下，耦合失效，器件以Mie共振为主，呈现出高效的四波段吸收模式，各峰吸收率均超过95%。当VO2跃迁到金属态时，耦合被激活，允许顶层等离子体共振与底层Mie共振耦合。这种相互作用引起了光谱重构，将离散的高频共振峰合并成一个连续的宽带吸收带（0.919-1.157 THz），吸收率超过90%，从而实现了从四波段到宽带吸收的可切换性能。这种设计策略为实现具有可切换功能的智能超材料提供了一种新的物理范式。

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引用次数: 0

Visible, infrared and laser multi-spectral compatible camouflage metasurface emitter based on ultrathin silver 基于超薄银的可见光、红外和激光多光谱兼容伪装超表面发射器

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-20 DOI: 10.1016/j.infrared.2026.106419

Jiaxin Li , Yiyang Shen , Yimin Zhang , Aoxue Guo , Yufang Liu , Shuwen Zheng , Mengdan Qian

Camouflage technology serves as a critical anti-reconnaissance tool, utilizing technical methods to minimize the likelihood of detection and identification by surveillance systems. Accordingly, the advancement of new camouflage technologies is a fundamental strategy to improving the survivability of military weapons and equipment. In this study, an optically transparent metasurface emitter consisting of Ag disk /SiO₂/Ag/ZnS is designed and fabricated by virtue of the inherent absorption characteristics of transparent dielectric films and ultrathin Ag layers. This configuration integrates multispectral camouflage, covering the visible, infrared, and laser ranges, with effective radiative heat management. Relative to a blackbody reference (T = 300 K), the fabricated emitter demonstrates infrared signal reduction rates of 79.5 % and 83.2 % in the 3–5 μm and 8–14 μm detection bands, respectively, together with enhanced absorption performance at the 10.6 μm operating wavelength of CO₂ laser radar. The ultrathin Ag film ensures excellent optical transparency while maintaining its other functionalities. Experimental verification confirms that the emitter effectively dissipates heat through the non-atmospheric windows under high temperatures, with significantly lower surface temperatures observed compared to conventional broadband low-emissivity materials, indicating excellent thermal management performance. This work proposes an innovative approach for achieving multispectral-compatible camouflage, offering substantial potential for applications in observation windows of military equipment and related fields.

伪装技术是一种关键的反侦察工具，利用技术方法将监视系统发现和识别的可能性降到最低。因此，新型伪装技术的发展是提高军事武器装备生存能力的基本战略。本研究利用透明介质膜和超薄银层固有的吸收特性，设计并制作了由Ag盘/SiO2/Ag/ZnS组成的光学透明超表面发射体。这种配置集成了多光谱伪装，覆盖可见光、红外和激光范围，具有有效的辐射热管理。相对于黑体基准（T = 300 K），该发射体在3 ~ 5 μm和8 ~ 14 μm探测波段的红外信号衰减率分别为79.5%和83.2%，在CO2激光雷达工作波长10.6 μm处的吸收性能增强。超薄银膜在保持其其他功能的同时确保了优异的光学透明度。实验验证证实，在高温下，发射器通过非大气窗口有效散热，与传统的宽带低发射材料相比，观察到的表面温度显着降低，表明了出色的热管理性能。这项工作提出了一种实现多光谱兼容伪装的创新方法，为军事装备和相关领域的观测窗口应用提供了巨大的潜力。

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引用次数: 0

Aluminium alloy emissivity correction model based on photon-phonon coupling and wavelength weight optimization 基于光子-声子耦合和波长权重优化的铝合金发射率校正模型

IF 3.4 3区物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION

Infrared Physics & Technology

Pub Date : 2026-03-01 Epub Date: 2026-01-09 DOI: 10.1016/j.infrared.2026.106376

An Wang , Yu-Cun Zhang , Qun Li

This paper proposes an emissivity correction model based on the surface phonon-photon coupling (SPCC) system of aluminum alloy, aimed at addressing the complexity of emissivity variation with temperature and wavelength under high-temperature conditions. The model combines the SPCC system with a wavelength-weight optimization algorithm, considering the interaction between phonons and photons on the aluminum alloy surface, and accurately describes the impact of multi-band infrared radiation intensity on temperature measurement. By introducing a swarm optimization algorithm to optimize the wavelength weight function, the model adjusts the contribution of different bands to temperature measurement, significantly improving the infrared temperature measurement accuracy in the range of 300–500 °C. Experimental results demonstrate that, compared to traditional fixed emissivity models, this model reduces temperature measurement errors by more than 20.6 %, providing a crucial theoretical foundation and technical support for precise temperature control of high-temperature aluminum alloy ring forgings.

针对高温条件下发射率随温度和波长变化的复杂性，提出了一种基于铝合金表面声光子耦合（SPCC）系统的发射率校正模型。该模型将SPCC系统与波长-权重优化算法相结合，考虑了铝合金表面声子与光子的相互作用，准确描述了多波段红外辐射强度对测温的影响。该模型通过引入群优化算法对波长权函数进行优化，调整不同波段对测温的贡献，显著提高了300-500℃范围内红外测温精度。实验结果表明，与传统的固定发射率模型相比，该模型的测温误差降低了20.6%以上，为高温铝合金环类锻件的精确控温提供了重要的理论基础和技术支持。

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引用次数: 0