Detectability conditions for output-only subspace identification

ABSTRACT

The scope of output-only/blind identification is restricted to stochastic/statistical processes, but for the first time in this study, the detectability conditions for general output-only subspace identification are investigated. This aids the range of input sources to be extended in a much realistic manner, beyond the only stochastic inputs. For this purpose, the subspace framework is assigned to make a connection between the output signal contents and the LTI system order. A few substantial hypotheses and algebraic statements are propounded affirming the sufficiency of the genuine output sequences for the identification purpose. This can be perceived as the cornerstone of state-space model reconstruction. In order to consolidate the notions according to reality, several examples are studied and examined for different input classes with stochastic disturbance.     

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.     

Summary of ISO/TC 201 standard: ISO 19668—Surface chemical analysis—X‐ray photoelectron spectroscopy—Estimating and reporting detection limits for elements in homogeneous materials

This International Standard specifies a procedure by which elemental detection limits in X‐ray photoelectron spectroscopy (XPS) can be estimated from data for a particular sample in common analytical situations and reported. This document is applicable to homogeneous materials and is not applicable if the depth distribution of elements is inhomogeneous within the information depth of the technique.     

CS—244／344红外碳硫测定仪计量检定中的几个问题

探讨CS-244/344红外碳硫测定仪检定规程在实际运用中存在的几个问题及相应的对策。     

原子吸收分光光度计计量检定中的几个问题

对原子吸收分光光度计计量检定中的几个问题作了一些探讨,并提出了相应的改进措施。     

From local to global analysis of defect detectability in infrared non-destructive testing

Several image processing techniques are employed in Infrared Non-Destructive Testing (IRNDT) to enhance defect detectability. To date, there is no adequate global measurement that objectively assesses defect visibility in processed frames. In this work, a Global Signal to Noise Ratio (GSNR) that comprehensively evaluates defect detectability in processed infrared (IR) images is proposed, as well as a defect visibility measure named Infrared Image Quality Index (IRIQI) that compares the structural information of defective and sound areas. In addition, GSNR and IRIQI are validated by using the area under ROC curve (AUC). AUC quantitatively assesses defect visibility by comparing the outcomes of processing techniques to human judgements. The remarkable benefit of this global approach is that it allows one to determine the frame at which processing techniques reveals the majority of the defects by evaluating the times at which AUC curves reach their maxima. The test pieces were a Carbon-Fiber Reinforced Plastic (CFRP) sample containing delaminations and a honeycomb specimen with delaminations, skin unbonds, excessive adhesive, and crushed core.     

On the detectability of Galactic dark matter annihilation into monochromatic gamma-rays

Monochromatic γ-rays are thought to be the smoking gun signal for identifying dark matter annihilation. However, the flux of monochromatic γ-rays is usually suppressed by virtual quantum effects since dark matter should be neutral and does not couple with γ-rays directly. In this work, we study the detection strategy of the monochromatic γ-rays in a future space-based detector. The flux of monochromatic γ-rays between 50 GeV and several TeV is calculated by assuming the supersymmetric neutralino as a typical dark matter candidate. The detection both by focusing on the Galactic center and in a scan mode that detects γ-rays from the whole Galactic halo are compared. The detector performance for the purpose of monochromatic γ-ray detection, with different energy and angular resolution, field of view, and background rejection efficiencies, is carefully studied with both analytical and fast Monte-Carlo methods.     

彩色融合技术在军事中的应用

采用基于l空间的色彩传递理论实现实时的红外与可见光彩色融合技术,并介绍了自行研制的红外与微光彩色融合系统的组成和工作流程。介绍了彩色融合技术在军事中的典型应用:夜间狙击手探测和伪装车辆探测,并给出了实验图像。设计了一种图像中目标探测性的主观评价方法,并对两组实验图像进行了评价。实验结果表明,彩色融合技术能够大大提高军事目标的探测性。     

A Novel Approach to Improve the Detectability of CO2 by GC Analysis

A novel stochastic resonance algorithm was employed to enhance the signal-to-noise ratio (SNR) of signals of analytical chemistry.By using a gas chromatographic data set,it was proven that the SNR was greatly improved and the quantitative relationship between concentrations and chromatographic responses remined simultancously.The linear range was extended beyond the instrumental detection limit.