MEMS仪表惯性组合导航系统发展现状与趋势

基于MEMS仪表的惯性组合导航系统是飞行器实现轻小型化的关键配套设备之一。针对国外MEMS惯性组合导航系统产品的实现方案与性能指标进行了综述;介绍我国在该领域的研究现状,简要分析当前存在的问题与技术瓶颈,指出我国应结合现有硅微惯性器件加工水平与理论研究成果展开有针对性的研究工作。最后,对该领域的技术发展方向进行了分析。     

Detection of fatigue damage in steel using laser speckle

We investigated a method to detect fatigue damage of steels without contact using laser speckle. In the earlier stage of fatigue in steels, slipbands appear on the surface and microscopic shear strain is stored in the slipbands. The slipbands appear more densely with progress of fatigue damage. When a laser illuminates the surface of the fatigued steel, light intensity distribution of the laser speckle pattern formed by the reflected light changes with the change of surface properties caused by slipbands. It has been clarified that the width of the speckle pattern broadens corresponding to spatial frequency distribution of the surface profile and thus it is presumed that speckle pattern broadens with increase of slipband density. This shows that we can detect fatigue damage by observing the laser speckle pattern on material surface. The method presented in this paper is based on this phenomenon. We observed change of the speckle pattern during fatigue loading under constant stress amplitude using a steel specimen and the relation between speckle pattern, number of loading cycles and also magnitude of loading was considered. We investigated the possibility of detection of fatigue damage using this method and also proposed a method to estimate fatigue life by observing change tendency of the speckle pattern depending on the number of loading cycles in the earlier stage of fatigue before crack initiation.     

Structure information from fusion barriers

It is shown that the analysis of fusion barrier distributions is not always an unambiguous test or a ‘fingerprint’ of the structure information of the colliding nuclei. Examples are presented with same fusion barrier distributions for nuclei having different structures. The fusion excitation functions for ¹⁶O+²⁰⁸Pb, using the coupled reaction channel (CRC) method and correct structure information, have been analysed. The barrier distributions derived from these excitation functions including many of the significant channels are featureless, although these channels have considerable effects on the fusion excitation function. However, a simultaneous analysis of the fusion, elastic and quasi-elastic channels would fix the structure and the reaction unambiguously.     

Voxel-based morphometry with templates and validation in a mouse model of Huntington’s disease

Despite widespread application to human imaging, voxel-based morphometry (VBM), where images are compared following grey matter (GM) segmentation, is seldom used in mice. Here VBM is performed for the R6/2 model of Huntington’s disease, a progressive neurological disorder. This article discusses issues in translating the methods to mice and shows that its statistical basis is sound in mice as it is in human studies. Whole brain images from live transgenic and control mice are segmented into GM maps after processing and compared to produce statistical parametric maps of likely differences. To assess whether false positives were likely to occur, a large cohort of ex vivo magnetic resonance brain images were sampled with permutation testing. Differences were seen particularly in the striatum and cortex, in line with studies performed ex vivo and as seen in human patients. In validation, the rate of false positives is as expected and these have no discernible distribution through the brain. The study shows that VBM successfully detects differences in the Huntington’s disease mouse brain. The method is rapid compared to manual delineation and reliable. The templates created here for the mouse brain are freely released for other users in addition to an open-source software toolbox for performing mouse VBM.     

An improvement of image registration based on phase correlation

This paper is dedicated to studying the extended phase correlation method that applies to the sub-pixel evaluation of translational displacement between images. On the basis of experiments, this paper proposes an improved version of classical Hanning window, with involving parameters optimization in the process. We add a window function to the input images in the space domain and a weighting function to the spectrum in the frequency domain. The statistics and distribution of errors prove the applicability of the proposal. The experimental results of the proposed extended phase correlation algorithm show the registration accuracy of 1/100 pixel.     

Kernel-aligned multi-view canonical correlation analysis for image recognition

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.     

Activated sludge characterization through microscopy: A review on quantitative image analysis and chemometric techniques

In wastewater treatment processes, and particularly in activated sludge systems, efficiency is quite dependent on the operating conditions, and a number of problems may arise due to sludge structure and proliferation of specific microorganisms. In fact, bacterial communities and protozoa identification by microscopy inspection is already routinely employed in a considerable number of cases. Furthermore, quantitative image analysis techniques have been increasingly used throughout the years for the assessment of aggregates and filamentous bacteria properties. These procedures are able to provide an ever growing amount of data for wastewater treatment processes in which chemometric techniques can be a valuable tool. However, the determination of microbial communities’ properties remains a current challenge in spite of the great diversity of microscopy techniques applied. In this review, activated sludge characterization is discussed highlighting the aggregates structure and filamentous bacteria determination by image analysis on bright-field, phase-contrast, and fluorescence microscopy. An in-depth analysis is performed to summarize the many new findings that have been obtained, and future developments for these biological processes are further discussed.     

Blind restoration of real turbulence-degraded image with complicated backgrounds using anisotropic regularization

This paper proposes a novel blind image restoration method based on estimating the point-spread functions by using two real turbulence-degraded images as input. The non-negative constraint and the spatial correlation are transformed mathematically into the penalty terms and added to the objective function. An anisotropic and nonlinear regularization function is proposed to adequately punish the differences of the point spread functions (PSFs) in the process of optimization estimation. Some definitions of weighted second-order differences are given and a fast method to construct the matrix of second-order weighted gradient operator is derived. The PSF values can be quickly estimated. With the estimated PSFs, the true images can be recovered by non-blind restoration methods. Experiment results for the restoration of real turbulence-degraded images with complicated backgrounds support the effectiveness of this proposed method.     

Combining multiset resolution and segmentation for hyperspectral image analysis of biological tissues

Hyperspectral images can provide useful biochemical information about tissue samples. Often, Fourier transform infrared (FTIR) images have been used to distinguish different tissue elements and changes caused by pathological causes. The spectral variation between tissue types and pathological states is very small and multivariate analysis methods are required to describe adequately these subtle changes.