对无线HART网络的图表路由算法的研究

在无线HART网络层协议中图表路由算法被规定为常规的路由方法。协议仅对图表路由算法进行了定义以及规定了其特点,并没有实现明确的仿真以及评估,本文在TinyOS中运用nesC语言对图表路由算法进行仿真,并且在吞吐量、延迟2个方面与AODV协议进行对比评估,通过TinyOS模拟仿真和评估可以看出,图表路由算法在无线HART网络中具有明显优势。

基于连通域的联锁表扫描件图表自动识别算法

针对目前主流图表自动识别算法不适用于大型联锁表扫描件图像的问题,本文设计了基于连通域的联锁表扫描件图表自动识别算法。该算法能通过图像处理和神经网络对扫描件中的表格及文字进行识别后,完整复现在电子表格中,并将疑似识别错误的字符及其所在单元格突出显示,方便人工复核。算法主要分为预处理、定位和识别三个部分。其中预处理部分,提出了DN-OSTU与DNG-OTSU二值化算法,通过不同内核均值滤波和图像相除、线性归一化等方法对光线不均的扫描件进行二值化,并提出基于累计概率霍夫变换PPHT的倾斜矫正算法,能快速且准确检测出倾斜角度;定位部分,采用基于连通域的定位算法定位表格方框及文字区域,并提出基于图表特征的RS方框查补算法,确保表格的完整性和各单元格定位的准确性;识别部分,使用原图提取字符制作训练集,训练卷积循环神经网络CRNN,达到较高准确率。实验中,对多家设计院提供的联锁表进行测试,实验结果表明:单元格识别准确率达到92.8%,字符识别准确率为98.74%,单图从识别到电子表输出速率均在5秒以内。本文设计的联锁表扫描件图表自动识别算法具有准确率高、鲁棒性好、识别速度快等特点,可为纸质版联锁表扫描件复现电子版从而二次开发提供有效的技术途径。

对图表法计算井下低压电网短路电流的修正

本文分析了现用的图表法计算井下低压电网两相短路电流,存在着误差太大,不能保证短路保护装置可靠工作,并提出了对图表法的修正方法.

Navigation Map Data Representation and Parallel Display Algorithm in an Embedded Environment

Map data display is the basic information representation mode under embedded real-time navigation. After a navigation display data set （NDIS_SET） with several dimensions and corresponding mathematical description formula are designed, a series of rules and algorithms are advanced to optimize embedded navigation data and promote data index and input efficiency. A new parallel display algorithm with navigation data named N PDIS is then presented to adapt to limited embedded resources of computation and memory after a normal navigation data display algorithm named NDIS and related problems are analyzed, N_PDIS can synchronously create two preparative bitmapa by two parallel threads and switch one of them to screen automatically. Compared with NDIS, the results show that N_PDIS is more effective in improving display efficiency.

Parallel Image Processing Technology of Surface Detection System

To improve image processing speed and detection precision of a surface detection system on a strip surface,based on the analysis of the characteristics of image data and image processing in detection system on the strip surface,the design of parallel image processing system and the methods of algorithm implementation have been studied. By using field programmable gate array(FPGA) as hardware platform of implementation and considering the characteristic of detection system on the strip surface,a parallel image processing system implemented by using multi IP kernel is designed. According to different computing tasks and the load balancing capability of parallel processing system,the system could set different calculating numbers of nodes to meet the system's demand and save the hardware cost.

Linkage intensity learning approach with genetic algorithm for causality diagram

The causality diagram theory, which adopts graphical expression of knowledge and direct intensity of causality, overcomes some shortages in belief network and has evolved into a mixed causality diagram methodology for discrete and continuous variable. But to give linkage intensity of causality diagram is difficult, particularly in many working conditions in which sampling data are limited or noisy. The classic learning algorithm is hard to be adopted. We used genetic algorithm to learn linkage intensity from limited data. The simulation results demonstrate that this algorithm is more suitable than the classic algorithm in the condition of sample shortage such as space shuttle’s fault diagnoisis.

Traffic sign recognition algorithm based on shape signature and dual-tree complex wavelet transform

A novel traffic sign recognition system is presented in this work. Firstly, the color segmentation and shape classifier based on signature feature of region are used to detect traffic signs in input video sequences. Secondly, traffic sign color-image is preprocessed with gray scaling, and normalized to 64×64 size. Then, image features could be obtained by four levels DT-CWT images. Thirdly, 2DICA and nearest neighbor classifier are united to recognize traffic signs. The whole recognition algorithm is implemented for classification of 50 categories of traffic signs and its recognition accuracy reaches 90%. Comparing image representation DT-CWT with the well-established image representation like template, Gabor, and 2DICA with feature selection techniques such as PCA, LPP, 2DPCA at the same time, the results show that combination method of DT-CWT and 2DICA is useful in traffic signs recognition. Experimental results indicate that the proposed algorithm is robust, effective and accurate.

Two-Level Bregman Method for MRI Reconstruction with Graph Regularized Sparse Coding

In this paper, a two-level Bregman method is presented with graph regularized sparse coding for highly undersampled magnetic resonance image reconstruction. The graph regularized sparse coding is incorporated with the two-level Bregman iterative procedure which enforces the sampled data constraints in the outer level and updates dictionary and sparse representation in the inner level. Graph regularized sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge with a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can consistently reconstruct both simulated MR images and real MR data efficiently, and outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.

A Fault-tolerant Routing Control for Double Loop Networks

This paper divides the vertex set into several disjoined subsets and provides an optimal fault-tolerance routing algorithm based on the vertex set partition. This algorithm is efficient and convergent, in polynomial time, we can get the output if the vertex is given.