一种内嵌导磁槽的圆感应同步器

圆感应同步器是一种高精度角度传感器,传统的圆感应同步器的转子需外引激励线以驱动其工作,鉴于圆感应同步器在使用过程中需要连续旋转,这将使得外引激励线存在绞线的问题,本文提出一种新的设计方法,在圆感应同步器的定、转子基体上嵌有环状的金属导磁槽,导磁槽内放入环状金属导线.通过给定子导磁槽内的环状金属导线施加激励信号,此激励信号可耦合到转子导磁槽内的环状金属导线中以驱动转子工作,这使得转子无需外引激励线,进而提高了系统应用的便利性以及可靠性.     

关于高校美术基础素描教与学的思考

素描是绘画的入门知识,素描教学是美术教学的基础课程,素描教学在美术教学中极为重要。当前高校素描教学中存在诸多问题,且主要表现在教法与观念、艺术真实性等方面。有效进行素描教学需要从以下几个方面着手,整合素描教学的内容;重视观察环节;创设良好的教学环境。     

浅谈高职院校创新型教师的培养和建设

职业教育是我国高等院校的重要组成部分,培养高职院校创新型人才需要中有创新能力的教师。本文从创新意识和创新精神的培养、实践提高创新能力、优化制度建设等方面阐述高职院校创新型教师的培养和建设。     

自主-合作教学模式在C++程序设计教学改革中的应用

针对在C++程序设计课程教学中存在的问题,结合对自主-合作教学模式的研究,提出以自主学习教学模式贯穿教学始终;案例驱动的精讲与泛读相结合;手写程序与机器调试相结合;自主学习与合作学习相结合的教学新思路。并阐述了上述方法在教学改革实践中的具体应用及效果。     

基于机器视觉的微片状物厚度检测

针对片状颗粒厚度检测的实际需求,结合机器视觉、图像处理和嵌入式技术,设计与实现了一套基于高性能ARM11的微片状颗粒厚度检测系统。该系统以QT和S3C6410为软硬件平台,提出了利用轮廓提取和最小矩形边界框相结合的方法计算片状颗粒厚度。结果表明,该检测系统具有处理速度快,测量精度高和成本低廉等优点,满足了对颗粒厚度测量的需求。     

Perceptual image preview

Image preview is a convenient way to browse large or multiple images on small displays. However, current signal-level image resampling algorithms may remove many features of interest in the preview image. In this paper, we propose perceptual image preview which retains more perceptual features such that users can inspect features of interest by viewing the preview image only and without zooming in. This technology has two components, structure enhancement and perceptual feature visualization. Structure enhancement enhances the image structure while suppressing subtle details using a gradient modulation method, thus making the succedent perceptual features more apparent. For perceptual feature visualization, features of interest detected in the picture is visualized on the structure enhanced preview image. We demonstrate with two examples of most commonly used image quality features, image blur and noise. The effectiveness of the proposed method is validated by experimental results.     

Fuzzy-Basis-Function-Network-Based $H_infty$ Tracking Control for Robotic Manipulators Using Only Position Feedback

This paper presents an H _infin fuzzy output-feedback tracking-control scheme for robotic manipulators without measuring joint velocities. The developed controller and observer are based on a fuzzy basis function network (FBFN), which is employed to approximate nonlinear functions in the dynamics of controller and observer. The FBFN-based observer that estimates joint velocities can remove the needs of full-state measurements. According to the inevitable approximation errors and external disturbances, an H _infin auxiliary control signal is used to suppress the effects of the uncertainties. Moreover, all parameters of the fuzzy basis functions (FBFs) and FBF-to-output weights can be tuned online. The proposed controller requires no prior knowledge about the dynamics of the robot manipulator and no offline learning phase. Finally, comparative simulations on a three-link robot manipulator are provided to illustrate the tracking performance of the H _infin FBFN-based output-feedback control approach.     

Auto-tuning strategy for evolutionary algorithms: balancing between exploration and exploitation

Genetic Algorithms (GAs) and other Evolutionary Algorithms (EAs), as powerful and broadly applicable stochastic search and optimization techniques have been successfully applied in the area of management science, operations research and industrial engineering. In the past few years, researchers gave lots of great idea for improvement of evolutionary algorithms, which include population initialization, individual selection, evolution, parameter setting, hybrid approach with conventional heuristics etc. However, though lots of different versions of evolutionary computations have been created, all of them have turned most of its attention to the development of search abilities of approaches. In this paper, for improving the search ability, we focus on how to take a balance between exploration and exploitation of the search space. It is also very difficult to solve problem, because the balance between exploration and exploitation is depending on the characteristic of different problems. The balance also should be changed dynamically depend on the status of evolution process. Purpose of this paper is the design of an effective approach which it can correspond to most optimization problems. In this paper, we propose an auto-tuning strategy by using fuzzy logic control. The main idea is adaptively regulation for taking the balance among the stochastic search and local search probabilities based on the change of the average fitness of parents and offspring which is occurred at each generation. In addition, numerical analyses of different type optimization problems show that the proposed approach has higher search capability that improve quality of solution and enhanced rate of convergence.