包钢酸洗冷连轧机组自动化控制系统简介

介绍了包钢酸洗冷连轧生产线的生产工艺和自动化控制系统的构成,该自动控制系统采用了西门子公司SIMATIC TDC硬件系统、S7-400系列PLC控制器,画面操作显示采用W IN CC,软件方面应用了西门子公司开发的扩展秒流量、AGC厚度自动控制、平直度控制、动态变规格、神经网络等多项技术,具有很高的自动化水平。

A Statistical Parameter Analysis and SVM Based Fault Diagnosis Strategy for Dynamically Tuned Gyroscopes

Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector machine (SVM) classification model was proposed for dynamically tuned gyroscopes (DTG). The SPA, a kind of time domain analysis approach, was introduced to compute a set of statistical parameters of vibration signal as the state features of DTG, with which the SVM model, a novel learning machine based on statistical learning theory (SLT), was applied and constructed to train and identify the working state of DTG. The experimental results verify that the proposed diagnostic strategy can simply and effectively extract the state features of DTG, and it outperforms the radial-basis function (RBF) neural network based diagnostic method and can more reliably and accurately diagnose the working state of DTG.

Autonomous Driving in the iCity-HD Maps as a Key Challenge of the Automotive Industry

This article provides in-depth insights into the necessary technologies for automated driving in future cities. State of science is reflected from different perspectives such as in-car computing and data man- agement, road side infrastructure, and ~loud solutions. Especially the challenges for the application of HD maps as core technology for automated driving are depicted in this article.

Automated Design and Visualization System of a House Foundation from Blocks

This article analyzes creation methods of automated design system, presents design system of a house foundation from blocks. The creation methods of automated design system of a house foundation from blocks are discovered with Unified Modeling Language. Analyzed objects-classes： block, specification, model. Graphical system can design foundation, form specification of objects and create 3D model of house foundation. There are several types and different dimensions of concrete blocks. The program optimally arranges selected blocks so that monolithic parts will be minimal volume. Program selects a house foundation blocks from database by using ActiveX Data Objects technology, which by programming method connects drawing and database. Drawing＇s graphical objects have additional data from which exchange of data between graphical system and database is executed. Visualization system and example of house foundation from blocks project with specifications is presented. Creation problems of automated design system are discussed and conclusions are made.

A Hopfield Neural Network Algorithm for Automatic Name Placement for Point Feature

This paper presents a method of adding label to the map especially for the point feature. This method overcomes the shortcoming of traditional methods, e.g. Conflict\|Backtracking method. Its kernel algorithm use the hopfield neural network to find the best label position for point feature. The experimental results proves that this algorithm has good permanence and high speed.

Infrastructure-based localisation of automated coal mining equipment

A novel radar-based system for longwall coal mine machine localisation is described. The system, based on a radar-ranging sensor and designed to localise mining equipment with respect to the mine tunnel gate road infrastructure, is developed and trialled in an underground coal mine. The challenges of reliable sensing in the mine environment are considered, and the use of a radar sensor for localisation is justified. The difficulties of achieving reliable positioning using only the radar sensor are examined. Several probabilistic data processing techniques are explored in order to estimate two key localisation parameters from a single radar signal, namely along-track position and across-track position, with respect to the gate road structures. For the case of across-track position, a conventional Kalman filter approach is sufficient to achieve a reliable estimate. However for along-track position estimation, specific infrastructure elements on the gate road rib-wall must be identified by a tracking algorithm. Due to complexities associated with this data processing problem, a novel visual analytics approach was explored in a 3D interactive display to facilitate identification of significant features for use in a classifier algorithm. Based on the classifier output, identified elements are used as location waypoints to provide a robust and accurate mining equipment localisation estimate.

Times Series Prediction to Basis of a Neural Network Conceived by a Real Genetic Algorithm

Neural network and genetic algorithms are complementary technologies in the design of adaptive intelligent system. Neural network learns from scratch by adjusting the interconnections betweens layers. Genetic algorithms are a popular computing framework that uses principals from natural population genetics to evolve solutions to problems. Various forecasting methods have been developed on the basis of neural network, but accuracy has been matter of concern in these forecasts. In neural network methods forecasted values depend to the choose of neural predictor structure, the number of the input, the lag. To remedy to these problem, in this paper, the authors are investing the applicability of an automatic design of a neural predictor realized by real Genetic Algorithms to predict the future value of a time series. The prediction method is tested by using meteorology time series that are daily and weekly mean temperatures in Melbourne, Australia, 1980-1990.

A fully automatic registration approach based on contour and SIFT for HJ-1 images

To achieve a fully automatic registration between HJ-1 CCD images and HJ-1 infrared images is a difficult task as it must deal with the varying illuminations and resolutions of the images,different perspectives,and the local deformations within the images.In this paper,aimed at those registration issues,a fully automatic registration approach based on contour and SIFT is proposed.The registration technique performs a pre-registration process using contour feature matching algorithm that decides the overlapping region between a reference image and an input image.Once the coarse regions are obtained,it performs a fine registration process based on SIFT detector and a local adaptive matching strategy.In the fine registration process,image blocking theory is used,which not only speeds up the features extraction and matching,but also makes the matching point pairs distributed uniformly in images,and further improves the accuracy of input image rectification.Experiments with visible images and infrared images from HJ-1A/B demonstrate the efficiency and the accuracy of the proposed technique for multisource remote sensing images registration.