基于机器视觉的香烟小包装在线检测算法研究

在香烟包装过程中会出现包装不合格现象，通过对包装不合格的烟包图像特征进行分析，设计了香烟小包装的正面和侧面图像检测的快速算法，尤其对图像的快速配准进行了研究.文中将序贯相似检测算法、模板匹配及能量识别方法引入检测过程，对算法的流程进行了详细介绍，并将算法在MATLAB中编程实现.MATLAB上的仿真结果表明该检测算法合理可行，能够满足香烟小包装在线检测的需要。

针对实时对象的新型控制方法的讨论

介绍了一种模糊控制器,其控制方法是将模糊控制、神经元网络和遗传算法有机地结合在一起,充分利用它们的优点,以修正各自的缺点。同时,充分考虑实时控制对象的特点,紧紧地抓住此类控制对象对控制系统性能的要求,即控制系统的收敛性和反应速度。这种控制方法被证明是实际可行的,具有广泛的发展前景。

基于神经网络和小波变换的车型识别方法研究

车型自动识别分类在不停车收费系统中起着关键的作用，决定了不停车收费系统的可靠性和智能化程度，对提高公路交通系统的管理水平和车辆通行速度具有重要的意义。 本文对现有车型自动识别分类方法进行了分析比较，在此基础上，对采用雷达微波进行车型识别进行了探索和研究，雷达微波车型识别技术与车载电子标签有机结合起来，起到车型二次识别的作用，有效防止各种舞弊行为，控制收费损失。 本文通过MATLAB产生仿真的雷达微波信号，信号中包含了车型的特征信息。再采用小波变换的方法消除噪声，由于车型大小与信号经过小波变换后得到的各层能量分布有关，所以提取其能量分布作为分类识别的特征矢量。设计了BP神经网络的分类器，车型的能量分布特征由车型分类器进行分类，最终得到车辆的类型。 本文在对所设计的神经网络分类器进行训练的时候，对样本采用了改进的模糊C均值算法进行聚类分析，有效地避免了样本集不理想情况下对各类中心隶属度过小的情况，用隶属度作为网络输出训练,使网络容错性更强，更加符合实际分类情况，三个网络分别训练，最后综合判断，提高了分类质量。 本文首先介绍了已有车型自动识别的方法，分析讨论了存在的弊端，然后提出采用雷达微波进行识别的方法，详细介绍了对回波信号进行处理所用到的算法，分析比较各种算法，选择合适的算法用于信号的处理，最后介绍了车型识别硬件仿真平台及软件实现。

海上时移地震综合解释技术研究与应用

The practical application and development of the time-lapse seismic reservoir monitor technology has indicated which has already become one of most important development technologies in seeking the surplus oil distribution and improving the reservoir recovering. The paper, first obtained the rock physics experiment analysis data according to the Bohai Sea loose sandstone in-situ measure technical, and determined the feasibility research of the S oil-field on the time-lapse seismic reservoir monitoring combining with the time-lapse numeric simulation technology, which was used to analyze the time-lapse seismic respond raw of the reservoir parameters change and pointed out the attentive problems during the real time-lapse seismic processing and interpretation. Next, simply introduced the technical link and the effect of the time-lapse mutual constrained fidelity and match processing aiming at the local complex gathering condition, geological condition, development engineering condition. Third, introduced the time-lapse integrated interpretation and the technical system with the innovative key technology that includes the time-lapse difference explanation technology, the time-lapse seismic multi-attributes integrated interpretation technology, and the time-lapse constrained reservoir parameters inversion technology, and so on. Using the time-lapse difference direct explanation technology, directly obtained the surplus oil macroscopic distribution through the difference seismic data; Using the presenting 8 big principles of the sublayer isochronisms comparison, carried on the time-lapse integrated interpretation analysis on the fine sublayer comparison and the thin oil-layer(group) contrast and the oil layer (group); The paper putted up the research, contrast, applications of the multi-sides sensitive attribute analysis and the RBF nerve network on the nearest study algorithm, and predicted the reservoir parameters and the surplus oil distribution with them; Combining with innovative researches and the time-lapse seismic constrained reservoir parameters inversion technology realized the good combination of the seismic and the reservoir engineering. Fourth, under fully analyzing the geology condition, the reservoir condition, the exploit dynamic data, and the seismic data of the S oil-field, and analyzing the time-lapse difference factors with reservoir dynamic exploit data, calibrated the oil-gas saturation change, the pressure change, the water saturation change, and determined the rationality of the time-lapse seismic difference, and finally obtained the surplus oil distribution, the water flood characteristic understanding, reservoir degasification, and pressure drop raw, and so on, which had been used in the well pattern tightening plan proof of the S oil-field development adjustment plan. Finally, the paper summarized the knowledge and understanding of the marine time-lapse seismic integrated interpretation, also had pointed out the further need researched question.

微动勘查方法在煤矿采区勘探中的应用研究

The conventional microtremor survey is based on the single point of exploration, which includes collecting field data，estimating the phase velocity, investing the dispersion curve and obtaining the S–wave velocity structure. In the case of large-scale exploration, and when making the two-dimensional velocity section, the inversion is quite time-consuming, laborious and its precision depends on the subjective interpretation, which makes the results differently from person to person. In fact，we do not need the S-wave velocity values but only need the relative variation of velocity. For these reasons, this paper is desired to calculate the apparent S-wave velocity (Vx) to replace the S-wave velocity inversion and to obtain the relative variation of the S-wave velocity. Using this method, we can decrease the analysts’ effect, shorten the data processing time and improve work efficiency. The apparent S-wave velocity is a variable of the surface wave property, which can clearly reflect the downcast columns, mined-out areas and other unusual geological bodies. In this paper, Matlab is used to establish the three-dimensional data volume of the apparent S-wave velocity, from which we can get any apparent S-wave velocity section we need. Through the application case, the designed method is proved to be reliable and effective. The downcast columns, mined-out areas and other unusual geological bodies can be clearly showed in the apparent S-wave velocity section. And from the contour of the apparent S-wave velocity, the interface shape of the major target layers can be controlled basically.

Robust Photo-topography by Fusing Shape-from-Shading and Stereo

Methods for fusing two computer vision methods are discussed and several example algorithms are presented to illustrate the variational method of fusing algorithms. The example algorithms seek to determine planet topography given two images taken from two different locations with two different lighting conditions. The algorithms each employ assingle cost function that combines the computer vision methods of shape-from-shading and stereo in different ways. The algorithms are closely coupled and take into account all the constraints of the photo-topography problem. The algorithms are run on four synthetic test image sets of varying difficulty.

Error-driven active learning in growing radial basis function networks for early robot learning

Q. Meng and M.H. Lee, 'Error-driven active learning in growing radial basis function networks for early robot learning', 2006 IEEE International Conference on Robotics and Automation (IEEE ICRA 2006), 2984-90, Orlando, Florida, USA.

Construction of Robot Intra-modal and Inter-modal Coordination Skills by Developmental Learning

Q. Meng and M. H. Lee, 'Construction of Robot Intra-modal and Inter-modal Coordination Skills by Developmental Learning', Journal of Intelligent and Robotic Systems, 48(1), pp 97-114, 2007.

A hybrid power system for remote areas in Jordan

This paper presents a techno-economic assessment for a unique Isolated Hybrid Power System (IHPS) design for remote areas isolated from the grid which also has the capability of being operated as a smart μ-grid. The share of renewable energy sources in resource poor developing countries is low. In these countries an increase in the share of alternative energy (wind, water and sun) delivered with inexpensive operationally robust generation and delivery systems is seen to the way forward. In our design also incorporates a novel storage system to increase the effectiveness of the Isolated IHPSs previously reported in the literature. The configuration reported is a system consisting of, the wind and sun powered generation complemented with batteries, fuel cell unit and a diesel generator. The modelling design and simulations were based on Simulations conducted using MATLAB/SIMULINK, and HOMER Energy Planning and Design software tools. The design and simulation of a new storage approach incorporating Hydrogen Peroxide (H2O2) fuel cell (increasing the efficiency of the fuel cell from 35% to 65%) and a single board computer (Raspberry Pi) used for the energy management and control the system are the novel features of our design. The novel control strategy implemented also includes a synchronization capability that facilitates IHPS to IHPS or IHPS to Main-Grid connection. In the paper after briefly but comprehensively detailing the design and simulations we will present the results on which we conclude that smart independent systems that can utilize indigenous renewable energy with a capability of being able to synchronize with the grid or each other are the most optimal way of electrifying resource poor developing countries in a sustainable way with minimum impact on the environment and also achieve reductions in Green House Gases.

Sistemas fotovoltaicos este-oeste con capacidad de almacenamiento en la industria

El objetivo de este proyecto fin de carrera es ajustar el perfil generado por un sistema fotovoltaico con orientación este-oeste que dispone de una batería al perfil de demanda de distintas industrias en Alemania. Se ha puesto especial énfasis a los siguientes paquetes de trabajo: • Comparación de la eficiencia de un sistema fotovoltaico este-oeste frente a los resultados obtenidos con la típica orientación sur • Simulación de una instalación fotovoltaica este-oeste con una batería en una industria, basada en el software MATLAB / Simulink • Optimización económica. Los resultados obtenidos muestran que nunca es económico instalar un campo fotovoltaico este-oeste en vez de una instalación con orientación sur, en caso de que la única ventaja esperada sea el ensanche de la curva de generación de potencia.

Energy storage systems for wave energy converters and microgrids

The thesis initially gives an overview of the wave industry and the current state of some of the leading technologies as well as the energy storage systems that are inherently part of the power take-off mechanism. The benefits of electrical energy storage systems for wave energy converters are then outlined as well as the key parameters required from them. The options for storage systems are investigated and the reasons for examining supercapacitors and lithium-ion batteries in more detail are shown. The thesis then focusses on a particular type of offshore wave energy converter in its analysis, the backward bent duct buoy employing a Wells turbine. Variable speed strategies from the research literature which make use of the energy stored in the turbine inertia are examined for this system, and based on this analysis an appropriate scheme is selected. A supercapacitor power smoothing approach is presented in conjunction with the variable speed strategy. As long component lifetime is a requirement for offshore wave energy converters, a computer-controlled test rig has been built to validate supercapacitor lifetimes to manufacturer’s specifications. The test rig is also utilised to determine the effect of temperature on supercapacitors, and determine application lifetime. Cycle testing is carried out on individual supercapacitors at room temperature, and also at rated temperature utilising a thermal chamber and equipment programmed through the general purpose interface bus by Matlab. Application testing is carried out using time-compressed scaled-power profiles from the model to allow a comparison of lifetime degradation. Further applications of supercapacitors in offshore wave energy converters are then explored. These include start-up of the non-self-starting Wells turbine, and low-voltage ride-through examined to the limits specified in the Irish grid code for wind turbines. These applications are investigated with a more complete model of the system that includes a detailed back-to-back converter coupling a permanent magnet synchronous generator to the grid. Supercapacitors have been utilised in combination with battery systems for many applications to aid with peak power requirements and have been shown to improve the performance of these energy storage systems. The design, implementation, and construction of coupling a 5 kW h lithium-ion battery to a microgrid are described. The high voltage battery employed a continuous power rating of 10 kW and was designed for the future EV market with a controller area network interface. This build gives a general insight to some of the engineering, planning, safety, and cost requirements of implementing a high power energy storage system near or on an offshore device for interface to a microgrid or grid.

Financial modelling with 2-EPT probability density functions

The class of all Exponential-Polynomial-Trigonometric (EPT) functions is classical and equal to the Euler-d’Alembert class of solutions of linear differential equations with constant coefficients. The class of non-negative EPT functions defined on [0;1) was discussed in Hanzon and Holland (2010) of which EPT probability density functions are an important subclass. EPT functions can be represented as ceAxb, where A is a square matrix, b a column vector and c a row vector where the triple (A; b; c) is the minimal realization of the EPT function. The minimal triple is only unique up to a basis transformation. Here the class of 2-EPT probability density functions on R is defined and shown to be closed under a variety of operations. The class is also generalised to include mixtures with the pointmass at zero. This class coincides with the class of probability density functions with rational characteristic functions. It is illustrated that the Variance Gamma density is a 2-EPT density under a parameter restriction. A discrete 2-EPT process is a process which has stochastically independent 2-EPT random variables as increments. It is shown that the distribution of the minimum and maximum of such a process is an EPT density mixed with a pointmass at zero. The Laplace Transform of these distributions correspond to the discrete time Wiener-Hopf factors of the discrete time 2-EPT process. A distribution of daily log-returns, observed over the period 1931-2011 from a prominent US index, is approximated with a 2-EPT density function. Without the non-negativity condition, it is illustrated how this problem is transformed into a discrete time rational approximation problem. The rational approximation software RARL2 is used to carry out this approximation. The non-negativity constraint is then imposed via a convex optimisation procedure after the unconstrained approximation. Sufficient and necessary conditions are derived to characterise infinitely divisible EPT and 2-EPT functions. Infinitely divisible 2-EPT density functions generate 2-EPT Lévy processes. An assets log returns can be modelled as a 2-EPT Lévy process. Closed form pricing formulae are then derived for European Options with specific times to maturity. Formulae for discretely monitored Lookback Options and 2-Period Bermudan Options are also provided. Certain Greeks, including Delta and Gamma, of these options are also computed analytically. MATLAB scripts are provided for calculations involving 2-EPT functions. Numerical option pricing examples illustrate the effectiveness of the 2-EPT approach to financial modelling.

Improved kinematic sensing for motion control applications

New compensation methods are presented that can greatly reduce the slit errors (i.e. transition location errors) and interval errors induced due to non-idealities in optical incremental encoders (square-wave). An M/T-type, constant sample-time digital tachometer (CSDT) is selected for measuring the velocity of the sensor drives. Using this data, three encoder compensation techniques (two pseudoinverse based methods and an iterative method) are presented that improve velocity measurement accuracy. The methods do not require precise knowledge of shaft velocity. During the initial learning stage of the compensation algorithm (possibly performed in-situ), slit errors/interval errors are calculated through pseudoinversebased solutions of simple approximate linear equations, which can provide fast solutions, or an iterative method that requires very little memory storage. Subsequent operation of the motion system utilizes adjusted slit positions for more accurate velocity calculation. In the theoretical analysis of the compensation of encoder errors, encoder error sources such as random electrical noise and error in estimated reference velocity are considered. Initially, the proposed learning compensation techniques are validated by implementing the algorithms in MATLAB software, showing a 95% to 99% improvement in velocity measurement. However, it is also observed that the efficiency of the algorithm decreases with the higher presence of non-repetitive random noise and/or with the errors in reference velocity calculations. The performance improvement in velocity measurement is also demonstrated experimentally using motor-drive systems, each of which includes a field-programmable gate array (FPGA) for CSDT counting/timing purposes, and a digital-signal-processor (DSP). Results from open-loop velocity measurement and closed-loop servocontrol applications, on three optical incremental square-wave encoders and two motor drives, are compiled. While implementing these algorithms experimentally on different drives (with and without a flywheel) and on encoders of different resolutions, slit error reductions of 60% to 86% are obtained (typically approximately 80%).

Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.

We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.

Laminar Free Convection from a Vertically-Oriented Concentrated Photovoltaic Cell with Uniform Surface Heat Flux

This research project uses field measurements to investigate the cooling of a triple-junction, photovoltaic cell under natural convection when subjected to various amounts of insolation. The team built an experimental apparatus consisting of a mirror and Fresnel lens to concentrate light onto a triple-junction photovoltaic cell, mounted vertically on a copper heat sink. Measurements were taken year-round to provide a wide range of ambient conditions. A surface was then generated, in MATLAB, using Sparrow’s model for natural convection on a vertical plate under constant heat flux. This surface can be used to find the expected operating temperature of a cell at any location, given the ambient temperature and insolation. This research is an important contribution to the industry because it utilizes field data that represents how a cell would react under normal operation. It also extends the use of a well-known model from a one-sun environment to a multi-sun one.