一种用于异步电机效率优化的混合搜索方法

针对异步电机效率优化问题,提出了一种混合搜索方法。该方法起始于模糊自适应搜索,然后切换至黄金分割法以获取确定收敛速度。这样的搜索步骤能够降低转矩波动,避免在最优点附近发生振荡。利用一个包含铁损和机械损耗的异步电机模型,对该方法进行了矢量控制下的性能验证。仿真结果验证了该方法的有效性。

异步电机非侵入式效率检测与节能控制

异步电机结构简单、坚固耐用，是主要工业动力设备。异步电机的运行节能问题是工业节能研究的重要内容和热点之一。本文分析了异步电机运行性能，对异步电机的转速和效率检测的非侵入式方法、各种运行方式下的节能控制方法进行了研究，主要贡献有： 对比研究异步电机转速检测的各种方法，采用高分辨率谱估计和混叠采样处理实现了准确的转速检测，给出了转速自动判断方法，为非侵入式效率检测提供了重要的支撑技术。 研究了异步电机的低成本非侵入式效率检测方法，研制了相应的测试装置并进行了相关实验，对检测方法进行精度分析并提出了减小误差的措施。 在非侵入式效率检测的基础上，对于异步电机工频运行、转速开环变频调速和转速闭环转差频率控制变频调速三种运行方式进行了基于效率反馈的节能控制研究。通过专门设计的效率优化模糊控制器实现这三种运行方式下的节能控制，仿真分析表明了所提方法是合理有效的。 针对矢量控制异步电机的效率优化问题，对比分析了模糊搜索和黄金分割法这两种主要效率优化策略的特性，提出了一种混合搜索效率优化方法。这种新方法发挥了前两种寻优策略的互补优势，既保证了收敛的确定性，又降低了对电机输出转矩的影响。仿真分析表明了这种混合搜索方法的可行性。同时，在对输入功率的精确检测条件下，提出了一种全新的效率优化方法，该方法能够在更短时间内实现效率寻优。 探讨了基于无线网络技术的工厂电能管理系统。本文说明了工业无线网络技术的优势，阐述了能够实现系统节能的电能检测与管理技术，如异步电机能效分析模型、异步电机状态监测与预测技术等，分析了基于IEEE802.15.4无线传输协议构建异步电机能效监测系统的可行性。

青藏高原东部长周期大地电磁测深研究

As a complement to conventional MT, Long-period Magnetotellurics (LMT) has been developed at low frequency for soundings of deep electric structures. Eastern Himalayan Syntaxis (EHS) and surrounding area is a key place for the study of dynamics of the uplift of Tibetan plateau. Experiments in the pioneer studies for EHS3D project showed that the study area shares an unusual low resistive crust and upper mantle. Conventional MT could not provide sufficient information about the deep structures of the study area that requested long period MT measurement to be complemented. This thesis presents the LMT studies in eastern Tibet along the EHS3D-3 Profile from Xiachayu to Yushu including data acquisition, processing, inversion and interpretation. The effective period of the measured LMT signals extend from 10s up to 30000s for the duration more than one week measurement. The resulting model shows that the LMT sounding coincides with the MT data in overlapped periods. Especially the induction arrows and tippers derived from LMT data provide more information about the base of the conductors beneath the plateau with higher resolution. Anomalous induction coefficients and 2-D model suggest extensive conductive bodies beneath Lhasa block and Qiangtang terrain which would be a possible evidence for partial melt and fluids at depth.

Homology Induction: the use of machine learning to improve sequence similarity searches

Karwath, A. King, R. Homology induction: the use of machine learning to improve sequence similarity searches. BMC Bioinformatics. 23rd April 2002. 3:11 Additional File Describes the title organims species declaration in one string [http://www.biomedcentral.com/content/supplementary/1471- 2105-3-11-S1.doc] Sponsorship: Andreas Karwath and Ross D. King were supported by the EPSRC grant GR/L62849.

Rough set feature selection and rule induction for prediction of malignancy degree in brain glioma

X. Wang, J. Yang, R. Jensen and X. Liu, 'Rough Set Feature Selection and Rule Induction for Prediction of Malignancy Degree in Brain Glioma,' Computer Methods and Programs in Biomedicine, vol. 83, no. 2, pp. 147-156, 2006.

Iterative vs Simultaneous Fuzzy Rule Induction

M. Galea and Q. Shen. Iterative vs Simultaneous Fuzzy Rule Induction. Proceedings of the 14th International Conference on Fuzzy Systems, pages 767-772.

Active paraplegics are protected against exercise-induced oxidative damage through the induction of antioxidant enzymes

Exercise improves functional capacity in spinal cord injury (SCI). However, exhaustive exercise, especially when sporadic, is linked to the production of reactive oxygen species that may have a detrimental effect on SCI. We aimed to study the effect of a single bout of exhaustive exercise on systemic oxidative stress parameters and on the expression of antioxidant enzymes in individuals with paraplegia. The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia. Sixteen paraplegic subjects were submitted to a graded exercise test (GET) until volitional exhaustion. They were divided into active or non-active groups. Blood samples were drawn immediately, 1 and 2 h after the GET. We determined plasma malondialdehyde (MDA) and protein carbonylation as markers of oxidative damage. Antioxidant gene expression (catalase and glutathione peroxidase-GPx) was determined in peripheral blood mononuclear cells. We found a significant increase in plasma MDA and protein carbonyls immediately after the GET (P<0.05). This increment correlated significantly with the lactate levels. Active paraplegics showed lower levels of exercise-induced oxidative damage (P<0.05) and higher exercise-induced catalase (P<0.01) and GPx (P<0.05) gene expression after the GET. These results suggest that exercise training may be useful in SCI patients to develop systemic antioxidant defenses that may protect them against exercise-induced oxidative damage.

Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light

Chungui Lu, Olga A. Koroleva, John F. Farrar, Joe Gallagher, Chris J. Pollock, and A. Deri Tomos (2002). Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light. Plant Physiology, 130 (3) pp.1335-1348 Sponsorship: BBSRC RAE2008

Self-Organizing Grammar Induction Using a Neural Network Model

This paper presents a self-organizing, real-time, hierarchical neural network model of sequential processing, and shows how it can be used to induce recognition codes corresponding to word categories and elementary grammatical structures. The model, first introduced in Mannes (1992), learns to recognize, store, and recall sequences of unitized patterns in a stable manner, either using short-term memory alone, or using long-term memory weights. Memory capacity is only limited by the number of nodes provided. Sequences are mapped to unitized patterns, making the model suitable for hierarchical operation. By using multiple modules arranged in a hierarchy and a simple mapping between output of lower levels and the input of higher levels, the induction of codes representing word category and simple phrase structures is an emergent property of the model. Simulation results are reported to illustrate this behavior.

Integrated magnetic components for high-power high-current dc-dc converters

This thesis is focused on the design and development of an integrated magnetic (IM) structure for use in high-power high-current power converters employed in renewable energy applications. These applications require low-cost, high efficiency and high-power density magnetic components and the use of IM structures can help achieve this goal. A novel CCTT-core split-winding integrated magnetic (CCTT IM) is presented in this thesis. This IM is optimized for use in high-power dc-dc converters. The CCTT IM design is an evolution of the traditional EE-core integrated magnetic (EE IM). The CCTT IM structure uses a split-winding configuration allowing for the reduction of external leakage inductance, which is a problem for many traditional IM designs, such as the EE IM. Magnetic poles are incorporated to help shape and contain the leakage flux within the core window. These magnetic poles have the added benefit of minimizing the winding power loss due to the airgap fringing flux as they shape the fringing flux away from the split-windings. A CCTT IM reluctance model is developed which uses fringing equations to accurately predict the most probable regions of fringing flux around the pole and winding sections of the device. This helps in the development of a more accurate model as it predicts the dc and ac inductance of the component. A CCTT IM design algorithm is developed which relies heavily on the reluctance model of the CCTT IM. The design algorithm is implemented using the mathematical software tool Mathematica. This algorithm is modular in structure and allows for the quick and easy design and prototyping of the CCTT IM. The algorithm allows for the investigation of the CCTT IM boxed volume with the variation of input current ripple, for different power ranges, magnetic materials and frequencies. A high-power 72 kW CCTT IM prototype is designed and developed for use in an automotive fuelcell-based drivetrain. The CCTT IM design algorithm is initially used to design the component while 3D and 2D finite element analysis (FEA) software is used to optimize the design. Low-cost and low-power loss ferrite 3C92 is used for its construction, and when combined with a low number of turns results in a very efficient design. A paper analysis is undertaken which compares the performance of the high-power CCTT IM design with that of two discrete inductors used in a two-phase (2L) interleaved converter. The 2L option consists of two discrete inductors constructed from high dc-bias material. Both topologies are designed for the same worst-case phase current ripple conditions and this ensures a like-for-like comparison. The comparison indicates that the total magnetic component boxed volume of both converters is similar while the CCTT IM has significantly lower power loss. Experimental results for the 72 kW, (155 V dc, 465 A dc input, 420 V dc output) prototype validate the CCTT IM concept where the component is shown to be 99.7 % efficient. The high-power experimental testing was conducted at General Motors advanced technology center in Torrence, Los Angeles. Calorific testing was used to determine the power loss in the CCTT IM component. Experimental 3.8 kW results and a 3.8 kW prototype compare and contrast the ferrite CCTT IM and high dc-bias 2L concepts over the typical operating range of a fuelcell under like-for-like conditions. The CCTT IM is shown to perform better than the 2L option over the entire power range. An 8 kW ferrite CCTT IM prototype is developed for use in photovoltaic (PV) applications. The CCTT IM is used in a boost pre-regulator as part of the PV power stage. The CCTT IM is compared with an industry standard 2L converter consisting of two discrete ferrite toroidal inductors. The magnetic components are compared for the same worst-case phase current ripple and the experimental testing is conducted over the operation of a PV panel. The prototype CCTT IM allows for a 50 % reduction in total boxed volume and mass in comparison to the baseline 2L option, while showing increased efficiency.

Theory of elasticity and electric polarization effects in the group-III nitrides

In this work, the properties of strained tetrahedrally bonded materials are explored theoretically, with special focus on group-III nitrides. In order to do so, a multiscale approach is taken: accurate quantitative calculations of material properties are carried out in a quantum first-principles frame, for small systems. These properties are then extrapolated and empirical methods are employed to make predictions for larger systems, such as alloys or nanostructures. We focus our attention on elasticity and electric polarization in semiconductors. These quantities serve as input for the calculation of the optoelectronic properties of these systems. Regarding the methods employed, our first-principles calculations use highly- accurate density functional theory (DFT) within both standard Kohn-Sham and generalized (hybrid functional) Kohn-Sham approaches. We have developed our own empirical methods, including valence force field (VFF) and a point-dipole model for the calculation of local polarization and local polarization potential. Our local polarization model gives insight for the first time to local fluctuations of the electric polarization at an atomistic level. At the continuum level, we have studied composition-engineering optimization of nitride nanostructures for built-in electrostatic field reduction, and have developed a highly efficient hybrid analytical-numerical staggered-grid computational implementation of continuum elasticity theory, that is used to treat larger systems, such as quantum dots.