Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

Detection of delamination defects in CFRP materials using ultrasonic signal processing

In this paper, signal processing techniques are tested for their ability to resolve echoes associated with delaminations in carbon fiber-reinforced polymer multi-layered composite materials (CFRP) detected by ultrasonic methods. These methods include split spectrum processing (SSP) and the expectation-maximization (EM) algorithm. A simulation study on defect detection was performed, and results were validated experimentally on CFRP with and without delamination defects taken from aircraft. Comparison of the methods for their ability to resolve echoes are made.     

Digital Micro-mirror Device-based broadband optical image sensor for robust imaging applications

To the best of the authors' knowledge, presented for the first time is the design of a robust broadband optical image sensor using a Digital Micro-mirror Device (DMD). Electronic focus control of the imaging lens and full programmability of the spatial sampling aperture shape, size, and location on the DMD plane that mechanically scans the incident incoherent optical irradiance distribution lead to imaging smartness. Dual port single-point photo-detection design provides imaging operation robustness to the global light irradiance variations such as via environmental effects, e.g., moving clouds. As the Texas Instruments (TI) DMD can provide light modulation over 400 nm to 2500 nm wavelengths, visible, Near Infrared (NIR), and Short-Wave Infrared (SWIR) bands can be simultaneously processed to generate three independent band images via three point photo-detectors. A proof-of-concept experiment in the SWIR band at 1580 nm is conducted using an incoherent heart-shaped target that is sampled using the DMD imager set for a 68.4 μm side square moving pinhole. A 60 × 60 pixel image from the proposed imager produces a 0.94 cross-correlation peak when compared to an optically attenuated heart shape image produced by a near 9 μm pixel size phosphor coated Charge Coupled Device (CCD) imager. Using the dual-detection method, robust 633 nm visible light imaging of an Air Force (AF) Chart figure is successfully demonstrated for 3 Hz global light fluctuation. Applications for the proposed imager include optical sensing in the fields of astronomy, defense, medicine, and security.     

红外多波段点目标检测RX算法性能分析

给出了多波段条件下用于点目标检测的RX算法模型,以接收机工作特性曲线ROC以及恒虚警率条件下的检测概率为性能评价手段,分析了探测器像元数、光谱波段数以及广义信噪比对算法性能的影响,并重点分析了波段数与广义信噪比需要满足的匹配关系,据此给出了用于点目标检测的波段参量优化选择方法.最后应用该方法对飞机尾焰进行了最优化探测波段优化选择,证明了该方法的有效性.     

Comparison of three thermographic post processing methods for the assessment of a repaired aluminum plate with composite patch

Composite patches are widely used to repair damaged metal structures, especially in aerospace industry. Perfect patch and bonding are necessary to achieve an effective repair. Various thermographic methods such as step heating thermography are commonly applied to inspect repaired structures. Since accurate determination of defect features are admirable, some techniques are used to process the thermal films. In this study, three common post processing techniques of thermography (namely, principle component analysis (PCA), pulse phase thermography (PPT) and thermal signal reconstruction (TSR)) have been utilized to inspect an aluminum plate repaired with carbon/epoxy patches. Several delaminations with various sizes and locations along with some disbond defects were artificially embedded in five samples of composite patches to experimentally investigate the performance of the three techniques for post-processing of the step heating thermography data. Furthermore, the outputs of the mentioned processing techniques were quantitatively compared to find the most effective one. Based on the comparison results, it was demonstrated that, TSR outputs leads to the more accurate defect sizing.     

基于红外光谱的鲜地黄、生地黄和熟地黄成分差异分析

运用傅里叶变换衰减全反射红外光谱(ATR-FTIR)对鲜地黄水提物、生地黄水煎液和熟地黄水煎液的整体成分进行差异分析,并运用离子色谱法对差异成分进行定量分析,研究鲜地黄与其炮制品的整体成分及变化规律。ATR-FTIR中,三种地黄在糖区有差异,其中鲜地黄糖区特征峰在1 140, 1 047和1 000 cm^-1,生地黄糖区特征峰为1 140和1 045 cm^-1,熟地黄糖区特征峰为1 142和1 029 cm^-1,且三种地黄峰形状不同。二阶导数红外光谱(SDIR)进一步发现,地黄炮制过程中糖类成分在1 200～600 cm^-1之间的特征峰变化最为显著。三种地黄提取液的特征峰位置相近,但相对峰强度不同,且随着炮制过程呈规律性变化。可以推测出在鲜地黄炮制过程中,鲜地黄中多糖发生水解,变成熟地黄中的寡糖或者单糖。应用离子色谱法对8种单糖和寡糖进行定量分析,所建立方法线性关系良好(R²≥0.999 0)。定量结果显示,葡萄糖、蜜二糖、半乳糖、甘露糖、甘露三糖、水苏糖和毛蕊花糖苷在鲜地黄、...     

红外光谱结合化学计量学快速鉴别云南重楼不同炮制品

中药炮制是根据中医学理论,改变中药的性味和功效,以达到缓和药性、减毒增效等作用。炮制对中药的活性成分、药效、毒副作用影响甚大,建立一个系统鉴别和评价中药不同炮制品的方法,可为中药质量和临床用药安全提供重要支撑。采用红外光谱法对9种云南重楼不同炮制品进行对比分析,结合化学计量学建立主成分-马氏距离(PCA-MD)判别模型进行鉴别分析。云南重楼不同炮制品的红外光谱经自动基线校正和纵坐标归一化预处理后,取其平均光谱图。九种重楼不同炮制品的平均红外光谱和二阶导数光谱显示：(1)其主要特征吸收峰为3 387,2 923,1 745,1 463,1 338,1 240,1 207,1 158,1 180,1 080,1 048,1 020,988,921,895,859,833,765,708,572和529 cm-1;(2)重楼不同炮制品红外图谱的峰形基本相似,可显示出重楼所特有的红外光谱特征;(3)重楼不同炮制品红外图谱中少数特征吸收峰数目、位置和吸收强度存在差异,表明重楼经不同炮制后化学成分和含量发生了改变。红外光谱经多元散射校正(MSC),标准正态变量(SNV),一阶求导(1st Der),二阶求导(2nd Der)和平滑(SG)优化处理后,采用Kennard-Stone算法筛选训练集和预测集(3∶1),建立PCA-MD判别分析模型。结果显示,重楼不同炮制品的最佳预处理方法为1st Der+SG(11∶3)。提取前5个主成分,变量特征的解释能力为88.2%,以PC1,PC2和PC3为坐标轴建立PCA-MD三维得分图可知,九种炮制品可完全区分;其中重楼I,H,G和F的聚类效果最好,且前三种炮制品距离较近,表明晒干和烘干处理重楼与传统炮制重楼所含化学成分相似;重楼D和E空间距离较近,推测其经过微波和蒸汽高温处理后化学成分变化相似。预测集样本可准确的归属于训练集,PCA-MD判别模型的准确率为100%。红外光谱结合PCA-MD判别分析可准确区分云南重楼的不同炮制品,为云南重楼炮制品的临床应用提供参考,同时为中药炮制品的鉴别提供了借鉴。     

Infrared facility at the Canadian light source

The Canadian Light Source (CLS) is constructing two beamlines for Infrared Spectroscopy using synchrotron radiation (IRSR). One will supply mid-Infrared (2–25 μ) light to a Fourier Transform Infrared (FTIR) spectrometer and microscope for biological applications. The second will have a high resolution FTIR spectrometer for gas-phase and surface spectroscopy in the far-Infrared (beyond 25 μ). The Infrared beamlines will use dipole bending magnet radiation from a special bend magnet port design which provides a 50 mrad square acceptance. Issues with the first mirror and photon mask design, as well as the beamline layout and features are discussed.     

接触缺陷的振动调制超声导波检测技术研究

针对常规线性超声检测方法无法实现板结构接触类缺陷(如微裂纹、脱粘等)检测问题,将超声导波技术与振动声调制技术相结合,利用稀疏分布传感器发展了一种板结构中接触缺陷非线性超声检测方法。通过低频振动改变缺陷的接触状况,使得通过接触面的高频导波信号的相位和幅值受到调制。对受低频振动调制的超声导波二维时间序列进行时频分析,由于接触类缺陷的存在,在振动调制超声导波序列的时频分布上出现明显的低频振动频率分量。利用提取出的低频振动频率下的超声导波信号,进行了结构接触缺陷成像处理。检测试验表明,基于振动声调制的超声导波缺陷成像方法可以实现结构中的接触类缺陷检测。      

Computerized tomography technique for reconstruction of obstructed temperature field in infrared thermography

Infrared thermography is a rapid, non-invasive and full-field technique for non-destructive testing and evaluation (NDT&E). With all the achievements on IR instrumentation and image processing techniques attained, it has been extended far beyond simple hot-spot detection and becomes one of the most promising NDT&E techniques in the last decades. It has achieved increasing acceptance in different sectors include medical imaging, manufacturing component fault detection and buildings diagnostic. However, one limitation of IR thermography is that the testing results are greatly affected by object surface emissivity. Surface with various emissivities may lead to difficult discrimination between area of defect and area with different emissivity. Therefore, many studies have been carried out on eliminating emissivity, for example, the time derivative approach, lock-in processing and differential contrast measurements. In these methods, sequence of themo-data/images are recorded and being processed in order to eliminate differences of emissivity. Another problem of IR thermography is that any obstruction may limit stimulations and imaging which leads to the observation of unclear defect image. To solve this problem, this paper proposes an algorithm based on the principle of computerized tomography which permits the reconstruction of unavailable/partially available temperature distribution of the affected area using the measured surrounding temperature field. In the process, a set of imaginary rays are projected from many different directions across the area. For each ray, integration of the temperature derivatives along the ray is equals to the temperature difference between the boundary points intercepted by the ray. Therefore, a set of linear equations can be established by considering the multiple rays. Each equation expresses the unknown temperature derivatives in the affected area in terms of the measured boundary temperature data. Solution of the set of simultaneous equations yields unknown thermal distribution in the area which needs to be reconstructed. Based on the proposed computerized tomography reconstruction (CTR) technique, deviated temperature data due to missing temperature data hidden by obstacle can be reconstructed. With further development, this technique may have the potential to be applied in the reconstruction of any smooth physical fields like phase information in optical techniques.     

Infrared dim moving target tracking via sparsity-based discriminative classifier and convolutional network

Infrared dim and small target tracking is a great challenging task. The main challenge for target tracking is to account for appearance change of an object, which submerges in the cluttered background. An efficient appearance model that exploits both the global template and local representation over infrared image sequences is constructed for dim moving target tracking. A Sparsity-based Discriminative Classifier (SDC) and a Convolutional Network-based Generative Model (CNGM) are combined with a prior model. In the SDC model, a sparse representation-based algorithm is adopted to calculate the confidence value that assigns more weights to target templates than negative background templates. In the CNGM model, simple cell feature maps are obtained by calculating the convolution between target templates and fixed filters, which are extracted from the target region at the first frame. These maps measure similarities between each filter and local intensity patterns across the target template, therefore encoding its local structural information. Then, all the maps form a representation, preserving the inner geometric layout of a candidate template. Furthermore, the fixed target template set is processed via an efficient prior model. The same operation is applied to candidate templates in the CNGM model. The online update scheme not only accounts for appearance variations but also alleviates the migration problem. At last, collaborative confidence values of particles are utilized to generate particles' importance weights. Experiments on various infrared sequences have validated the tracking capability of the presented algorithm. Experimental results show that this algorithm runs in real-time and provides a higher accuracy than state of the art algorithms.     

红外光谱法研究盐酸丁咯地尔的热降解过程

本文采用傅里叶变换红外光谱、热重等多种分析方法,对盐酸丁咯地尔的热降解机理进行了较为详细的研究。实验结果表明盐酸丁咯地尔的热氧降解过程分为两个明显的阶段:一是脱盐酸、脱羧裂解,剩下苯环骨架结构;二是苯环骨架完全氧化裂解。通过对原药及其热氧降解中间产物的红外光谱分析,证实了以上的热氧降解历程。     

Speckle reduction by energy time-frequency filtering

Structural noise is a very important limitation to the visibility of flaw echoes in ultrasonic testing and evaluation of highly scattering materials. In order to enhance the signal-to-noise ratio, different algorithms have been developed. One of these techniques is based on filtering the spectrum low band of the received echo to obtain a significant improvement of the defect visibility. Based on this idea, in this work a new time-frequency technique is presented. In this method, block-processing autoregressive techniques are used to estimate the instantaneous center frequency of the traveling wave. From this information, a time-frequency filter is designed tuned at half the estimated instantaneous center frequency. Experimental results and the comparison with the non-time-frequency filtering technique are also included, showing that the proposed method has an excellent performance on SNR enhancement.     

红外光谱技术在饮料酒鉴别中的应用进展

红外光谱作为鉴别技术被广泛地用于各种饮料的品质检测和定性鉴别中。文章对比了各种用于饮料酒鉴别的技术的优缺点,介绍了红外光谱技术鉴别饮料酒的技术流程,以及红外光谱技术在葡萄酒、啤酒、威士忌、白兰地、日本清酒、中国黄酒等饮料酒的产地、酒龄以及分级等方面的国内外研究现状,分析了红外光谱技术应用于饮料酒鉴别的种种优势和需要解决的问题,并展望了其在我国饮料酒鉴别中的应用前景。     

Infrared and visible image fusion method based on saliency detection in sparse domain

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion. To better preserve the significant information of the infrared and visible images in the final fused image, the saliency maps of the source images is introduced into the fusion procedure. Firstly, under the framework of the joint sparse representation (JSR) model, the global and local saliency maps of the source images are obtained based on sparse coefficients. Then, a saliency detection model is proposed, which combines the global and local saliency maps to generate an integrated saliency map. Finally, a weighted fusion algorithm based on the integrated saliency map is developed to achieve the fusion progress. The experimental results show that our method is superior to the state-of-the-art methods in terms of several universal quality evaluation indexes, as well as in the visual quality.     

A novel compression algorithm for infrared thermal image sequence based on K-means method

High resolution in space and time is becoming the new trend of thermographic inspection of equipments, therefore, the development of a fast and precise processing and data store technique of high resolution thermal image should be well studied. This article will propose a novel global compression algorithm, which will provide an effective way to improve the precision and processing speed of thermal image data. This new algorithm is based on the decay of the temperature of thermograph and the feature of thermal image morphology. Firstly, it will sort the data in space according to K-means method. Then it will employ classic fitting calculation to fit all the typical temperature decay curves. At last, it will use the fitting parameters of the curves as the parameters for compression and reconstruction of thermal image sequence to achieve the method for which the thermal image sequence can be compressed in space and time simultaneously. To validate the proposed new algorithm, the authors used two embedded defective specimens made of different materials to do the experiment. The results show that the proposed infrared thermal image sequence compression processing algorithm is an effective solution with high speed and high precision. Compared to the conventional method, the global compression algorithm is not only noise resistant but also can improve the computing speed in hundreds of times.     

宝石级氟磷锰矿的化学成分及光谱学表征

氟磷锰矿是一种稀有矿物,宝石级氟磷锰矿可呈现高饱和度的红橙色.选取三颗来自巴基斯坦的样品,通过电子探针、拉曼光谱、红外光谱和紫外-可见光吸收光谱进行系统研究,旨在获得其化学成分、光谱学特征,分析致色离子,为其品种鉴定、优化处理等提供重要数据.样品平均化学成分化学式为(M n1.66,Fe0.17,Ca0.15,Mg0....     

用傅立叶变换红外光谱法研究核辐照对三七粉成分的影响

本文采用红外光谱法对经不同剂量核辐照的三七粉进行了对比研究, 比较了它们红外光谱的异同。三七粉的红外光谱主要由淀粉吸收带及碳水化合物的吸收带组成, 低辐照剂量(低于15 kGy)处理的三七粉组成成分的化学结构及含量几乎未发生变化; 较高辐照剂量(高于18 kGy)处理的三七粉组成成分中少数成分的化学结构及含量可能已经发生了变化。表明采用适当核辐照剂量杀灭三七粉中污染微生物和各种寄生虫卵是可取的。辐照剂量高于15 kGy后, 糖类(主要是多糖、庶糖)增加, 增加的糖可能是淀粉转化而来的。     

Influence of surface preparation on CdZnTe nuclear radiation detectors

High resolution X-ray diffraction (HRXRD), Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM) techniques were used to characterize the surface of CdZnTe (CZT) samples treated by mechanical lapping, polishing and chemical etching processes. The results confirm that the etching process produces the highest intensity diffraction peak, and the best full-width-at-half-maximum (FWHM). Fourier Transform Infrared (FTIR) spectroscopy shows that fine polishing increases the infrared transmission of the CZT sample, while etching with 2% bromine methanol (BM) etching decreases the infrared transmission. Different etchants and concentrations were investigated by comparing the surface morphology and roughness. The bromine methanol etching has shown more flat surface with lower roughness than the other etchants.     

Spectral information coding by infrared photoreceptors

Spontaneous pulsing has been observed in circuits containing cryogenically cooled silicon p-i-n (p⁺-n-n⁺) diodes under dc forward bias. The intensity of infrared radiation incident on the diodes controls the pulse rate with no appreciable effect on the shape or size of the pulses. A strong similarity is noted between these properties and the nearly universal means of coding of visual information by animal photoreceptors and neural networks. It is proposed that exploitation of this remarkable analogy could lead to radically new approaches to acquisition and processing of infrared optical information. Infrared analogs of neural color coding and color vision are proposed based on analysis of p-i-n spectral response measurements.