An intelligent sensor for detection of milling chatter

In this paper, a new real-time sensor system has been developed to detect chatter in milling operations. In the developed sensor system, a pattern recognition technique based on an unsupervised neural network using the adaptive resonance theory (ART) is adopted for detection of milling chatter. The features on the cutting force spectrum are fed into the sensor system to classify the milling process with or without chatter. The experimental results indicate that the proposed sensor system can accurately detect milling chatter regardless of the variation in cutting conditions.     

Theory and characteristics of novel variable reluctance 1X resolver

Although brushless resolvers have been used widely as angular position transducers, they are expensive due to their intricate construction, involving a rotary transformer to supply the exciting coils wound on the rotor poles with the current. It is shown theoretically in this paper that the resolver without rotary transformer or brushes can be realized by simple construction, which consists of the stator core with both 4-poles exciting windings and 2-poles output ones and the rotor core carrying no windings. In this resolver the rotor core has minimum gap at one side and a maximum gap at another side of the diameter. It is characterized by an outer surface form that makes the fluctuation part of gap permeance very in proportion to cos θ, where θ represents the angular position of a point in the air gap with respect to the origin on the rotor, the point of minimum air gap. The method determining the rotor form to embody the aforementioned gap permeance variation is also shown. It has been confirmed not only by simulation but also experiment that the 2-phase output voltages of a model designed based on the theory have sinusoidal waveforms with very small harmonic contents. Moreover, the rotor position detected by processing the output voltages through the conventional resolver/digital converter was within acceptable engineering accuracy.     

形态学边缘检测的新算法及其应用

提出了一种基于数学形态学的边缘检测的所算法，该算法具有简便和灵活可编程控制等优点，比原来主算法更国完善，在实际应用中有着很好的前景，并给出了实验结果。     

How to study drying shrinkage microcracking in cement-based materials using optical and scanning electron microscopy?

Three different ‘destructive’ microscopy methods were tested on their ability to show drying shrinkage microcracks on a specimen cross-section. The first two were methods in which the microcracks were impregnated with a fluorescent epoxy and examined with fluorescence microscopy. In one method, the impregnation was applied before making the cross-section and in the other after making the cross-section. In the third method, the sample was kept wet constantly and examined in an environmental scanning electron microscope (ESEM). It was concluded that the method in which the dried specimen was impregnated before making the cross-section was the most reliable method to record drying shrinkage microcracks. With this method, it was possible to impregnate the complete drying shrinkage microcrack pattern in the studied cement-based materials from the surface, and there was no risk of recording microcracks introduced by sample preparation.     

数字图像边缘检测算子的性能实验比较

本文对数字图像中几种具有代表性的边缘检测算子进行了理论分析，并通过VC编程实验，对各种算法进行实现，通过比较得出了各自的优缺点和适用范围。     

补偿式光纤F—P干涉仪的信号处理系统

本文提出并研制成补偿式光纤F-P干涉仪信号处理系统,提出了用来测量微小位移信号的三种方法及电路,即透射峰时间间隔测量法、光脉冲基波幅度测量法(精密整流法)、鉴相法。测试结果表明:时间间隔测量法,它的最大灵敏度达到0.26纳米/微秒;精密整流法,最大灵敏度为2.38纳米/伏特。     

Background-subtraction using contour-based fusion of thermal and visible imagery

We present a new background-subtraction technique fusing contours from thermal and visible imagery for persistent object detection in urban settings. Statistical background-subtraction in the thermal domain is used to identify the initial regions-of-interest. Color and intensity information are used within these areas to obtain the corresponding regions-of-interest in the visible domain. Within each region, input and background gradient information are combined to form a Contour Saliency Map. The binary contour fragments, obtained from corresponding Contour Saliency Maps, are then fused into a single image. An A^* path-constrained search along watershed boundaries of the regions-of-interest is used to complete and close any broken segments in the fused contour image. Lastly, the contour image is flood-filled to produce silhouettes. Results of our approach are evaluated quantitatively and compared with other low- and high-level fusion techniques using manually segmented data.     

高功率激光焊接光致等离子体的检测

系统地归纳了高功率激光焊接过程中光致等离子体的声、光、电、热等四种特征信号,综述了国外在等离子体信号检测方面的试验方法及研究进展,分析了未来的发展趋势。     

A fast digital Radon transform—An efficient means for evaluating the Hough transform

A fast digital Radon transform based on recursively defined digital straight lines is described, which has the sequential complexity of N² log N additions for an N × N image. This transform can be used to evaluate the Hough transform to detect straight lines in a digital image. Whilst a parallel implementation of the Hough transform algorithm is difficult because of global memory access requirements, the fast digital Radon transform is vectorizable and therefore well suited for parallel computation. The structure of the fast algorithm is shown to be quite similar to the FFT algorithm for decimation in frequency. It is demonstrated that even for sequential computation the fast Radon transform is an attractive alternative to the classical Hough transform algorithm.     

Concealed weapon detection and visualization in a synthesized image

Images acquired by heterogeneous image sensors may provide complementary information about the scene, for instance, the visual image can provide personal identification information like the facial pattern while the infrared (IR) or millimeter wave image can detect the suspicious regions of concealed weapons. Usually, a technique, namely multiresolution pixel-level image fusion is applied to integrate the information from multi-sensor images. However, when the images are significantly different, the performance of the multiresolution fusion algorithms is not always satisfactory. In this study, a new strategy consisting of two steps is proposed. The first step is to use an unsupervised fuzzy k-means clustering to detect the concealed weapon from the IR image. The detected region is embedded in the visual image in the second step and this process is implemented with a multiresolution mosaic technique. Therefore, the synthesized image retains the quality comparable to the visual image while the region of the concealed weapon is highlighted and enhanced. The experimental results indicate the efficiency of the proposed approach.This material is based on part of the work carried out at the SPCR laboratory of Lehigh University and the work is partially supported by the U. S. Army Research Office under grant number DAAD19-00-1-0431. The content of the information does not necessarily reflect the position or the policy of the federal government, and no official endorsement should be inferred.