一种预测油气田产量及可采储量的新模型

基于概率统计学中的Γ（ｘ２）分布，提出了一种新的预测模型。该模型可用于预测油气田的产量、可采储量、最高年产量及其发生的时间。实际应用结果表明，该模型比较实用，预测的各项指标是比较可靠的。     

Monitoring of multivariable dynamic processes and sensor auditing

Industrial continuous processes are usually operated under closed-loop control, yielding process measurements that are autocorrelated, cross correlated, and collinear. A statistical process monitoring (SPM) method based on state variables is introduced to monitor such processes. The statistical model that describes the in-control variability is based on a canonical variate (CV) state space model. The CV state variables are linear combinations of the past process measurements which explain the variability of the future measurements the most, and they are regarded as the principal dynamic dimensions. A T² statistic based on the CV state variables is utilized for developing the SPM procedure. The CV state variables are also used for monitoring sensor reliability. An experimental application to a high temperature short time (HTST) pasteurization process illustrates the proposed methodology.     

A Unified Theory of Uncalibrated Stereo for Both Perspective and Affine Cameras

This paper addresses the recovery of structure and motion from uncalibrated images of a scene under full perspective or under affine projection. Particular emphasis is placed on the configuration of two views, while the extension to $N$ views is given in Appendix. A unified expression of the fundamental matrix is derived which is valid for any projection model without lens distortion (including full perspective and affine camera). Affine reconstruction is considered as a special projective reconstruction. The theory is elaborated in a way such that everyone having knowledge of linear algebra can understand the discussion without difficulty. A new technique for affine reconstruction is developed, which consists in first estimating the affine epipolar geometry and then performing a triangulation for each point match with respect to an implicit common affine basis.     

Rough Terrain Autonomous Mobility—Part 1: A Theoretical Analysis of Requirements

A basic requirement of autonomous vehicles is that of guaranteeing the safety of the vehicle by avoiding hazardous situations. This paper analyses this requirement in general terms of real-time response, throughput, and the resolution and accuracy of sensors and computations. Several nondimensional expressions emerge which characterize requirements in canonical form.The automatic generation of dense geometric models for autonomously navigating vehicles is a computationally expensive process. Using first principles, it is possible to quantify the relationship between the raw throughput required of the perception system and the maximum safely achievable speed of the vehicle. We derive several useful expressions for the complexity of terrain mapping perception under various assumptions. All of them can be reduced to polynomials in the response distance.The significant time consumed by geometric perception degrades real-time response characteristics. Using our results, several strategies of active geometric perception arise which are practical for autonomous vehicles and increasingly important at higher speeds.     

Robust Estimation of Rotation Angles from Image Sequences Using the Annealing M-Estimator

A robust method is presented for computing rotation angles of image sequences from a set of corresponding points containing outliers. Assuming known rotation axis, a least-squares (LS) solution are derived to compute the rotation angle from a clean data set of point correspondences. Since clean data is not guaranteed, we introduce a robust solution, based on the M-estimator, to deal with outliers. Then we present an enhanced robust algorithm, called the annealing M-estimator (AM-estimator), for reliable robust estimation. The AM-estimator has several attractive advantages over the traditional M-estimator: By definition, the AM-estimator involves neither scale estimator nor free parameters and hence avoids instabilities therein. Algorithmically, it uses a deterministic annealing technique to approximate the global solution regardless of the initialization. Experimental results are presented to compare the performance of the LS, M- and AM-estimators for the angle estimation. Experiments show that in the presence of outliers, the M-estimator outperforms the LS estimator and the AM-estimator outperforms the M-estimator.     

Bayesian Landmark Learning for Mobile Robot Localization

To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optimality, since they rely on a human to determine what aspects of the sensor data to use in localization (e.g., what landmarks to use). This paper describes a learning algorithm, called BaLL, that enables mobile robots to learn what features/landmarks are best suited for localization, and also to train artificial neural networks for extracting them from the sensor data. A rigorous Bayesian analysis of probabilistic localization is presented, which produces a rational argument for evaluating features, for selecting them optimally, and for training the networks that approximate the optimal solution. In a systematic experimental study, BaLL outperforms two other recent approaches to mobile robot localization.     

控制系统校正环节优化设计的计算机辅助分析

结合共轭梯度法,借助于MATLAB软件,提出一种控制系统校正环节优化设计的新方法.该方法利用了MAT-LAB软件中的符号数学工具箱、控制系统工具箱和优化设计工具箱,使设计简单、快捷,提高了编程效率.     

变压器隔离方式的安全栅

论文介绍爆炸产生原因,综合比较自动化仪表各种防爆方法,介绍了最切实有效,最安全可靠的本质安全防爆方法,以本质安全防爆的原理为基础,设计利用隔离变压器来实现安全区和危险区隔离的一种新型的无源隔离式安全栅.     

强夯法在湿陷性黄土加固工程中的应用分析

本文从热电厂的盈亏分析入手，找出了最佳的盈亏平衡点，从而给出热价函数和电价函数，在一定程度上解决了热价制定难的问题。     

电缆材料绿色化的两大指标——毒性和有害元素的检测和分析

采用了电缆材料绿色化的两大指标———毒性和有害元素含量的两种检测方法,即细胞毒性试验和电感耦合等离子体发射光谱仪法,认为这两种方法具有简便、精确、快速和省钱等优点,文中也提供了某电缆阻水膏和某种电缆护套料分别进行毒性试验和有害元素检测和分析。