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2012 IEEE 6th International Conference on Information and Automation for Sustainability最新文献

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A study on effects of muscle fatigue on EMG-based control for human upper-limb power-assist 肌肉疲劳对基于肌电图的上肢助力控制的影响研究
T. Lalitharatne, Y. Hayashi, K. Teramoto, K. Kiguchi
It may be difficult task for physically weak elderly, disabled and injured individuals to perform the day to day activities in their life. Therefore, many assistive devices have been developed in order to improve the quality of life of those people. Especially upper-limb power-assist exoskeletons have been developed since the upper limb motions are vital for the daily activities. Electromyography (EMG) signals of the upper limb muscles have sometimes been used as a primary signal to control the power assist exoskeletons since the EMG signals directly reflect the motion intention of the user. But one of the main obstacles for EMG based controller is the muscle fatigue, because the muscle fatigue might change the EMG patterns. It is important for power-assist exoskeleton to correctly assist the user for longer period of time. But it has high probability of user muscles been fatigued because users getting more and more exhausted at the end of the day. Therefore it is necessary to consider the variations of EMG signals due to the effect of muscle fatigue. In this paper it demonstrates the study which was conducted to find out the effects of muscle fatigue on the three EMG features derived from the raw EMG signals of the Bicep brachii, Deltoid-posterior, Deltoid-anterior and Supinator muscles of the upper limb. Shoulder vertical flexion/extension, shoulder abduction/adduction, elbow flexion/extension and forearm pronation/supination motions were carried out before and after a set of muscle fatiguing exercises. The three features computed in this experiment were RMS (Root Mean Square), MPF (Mean Power Frequency) and a spectral feature (FInsm5) which was proposed by Dimitrov. Comparison results of these three features of all muscles before and after the fatiguing exercises showed an percentage increase of the RMS and FInsm5 features whereas MPF showed a percentage decrease with respect to the before fatiguing conditions. The result showed that the EMG RMS may not a reliable feature to use as the only input signal in EMG based control for human upper-limb power assist in the muscle fatiguing conditions. Therefore, it is suggested that a modification method for compensating the effect of muscle fatigue is required on the EMG based control in order to have a long and reliable use of the human upper-limb power assist exoskeletons.
对于身体虚弱的老年人、残疾人和受伤的人来说,在他们的生活中进行日常活动可能是一项困难的任务。因此,许多辅助设备被开发出来,以提高这些人的生活质量。由于上肢运动对日常活动至关重要,因此上肢动力辅助外骨骼已经得到了发展。上肢肌肉肌电图(EMG)信号有时被用作控制动力辅助外骨骼的主要信号,因为EMG信号直接反映了使用者的运动意图。但肌疲劳是肌电控制的主要障碍之一,因为肌疲劳可能会改变肌电模式。对于动力辅助外骨骼来说,长时间正确地辅助使用者是非常重要的。但是用户肌肉疲劳的可能性很大,因为用户在一天结束的时候会越来越疲惫。因此,有必要考虑肌疲劳对肌电信号的影响。本文阐述了肌肉疲劳对上肢肱二头肌、三角肌后肌、三角肌前肌和旋后肌三个肌电信号的影响的研究。在一组肌肉疲劳训练前后分别进行肩部垂直屈伸、肩部外展/内收、肘关节屈伸和前臂旋前运动。本实验计算的三个特征分别是均方根(RMS)、平均功率频率(MPF)和Dimitrov提出的频谱特征(FInsm5)。疲劳运动前后所有肌肉的这三个特征的比较结果显示,相对于疲劳前,RMS和FInsm5特征有百分比的增加,而MPF有百分比的减少。结果表明,在肌肉疲劳状态下,肌电均方根作为基于肌电的上肢助力控制的唯一输入信号可能不是一个可靠的特征。因此,建议在基于肌电图的控制中需要一种补偿肌肉疲劳影响的改进方法,以便长期可靠地使用人类上肢动力辅助外骨骼。
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引用次数: 31
Disturbance observer based current controller for a brushed DC motor 基于扰动观测器的有刷直流电动机电流控制器
A. Abeykoon, H. R. Senevirathne
Current control is essential for torque control. But available current controllers don't provide the required facilities for torque control. Often they produce a sluggish response. In this paper we propose an embedded system based current controlling method using the disturbance observer. Dynamic model of the DC motor is analyzed electrically and mechanically. Then the proposed method is analyzed by introducing the concept of disturbance observer. Real Time Operating System (RTOS) is used in the experiment. Results show the response current variation with and without the disturbance observer. Validity of the proposed method is verified by the results.
电流控制是转矩控制的必要条件。但现有的电流控制器不提供扭矩控制所需的设施。它们通常会产生迟钝的反应。本文提出了一种基于干扰观测器的嵌入式系统电流控制方法。对直流电机的动态模型进行了电气和机械分析。然后通过引入扰动观测器的概念对所提出的方法进行了分析。实验采用实时操作系统(RTOS)。结果显示了有和没有扰动观测器时响应电流的变化。实验结果验证了该方法的有效性。
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引用次数: 11
An efficient and speeded-up tree for multi-class classification 一种高效、快速的多类分类树
P. Ranganathan, A. Ramanan, M. Niranjan
Support vector machine is a state-of-the-art learning machine that is used in areas, such as pattern recognition, computer vision, data mining and bioinformatics. SVMs were originally developed for solving binary classification problems, but binary SVMs have also been extended to solve the problem of multi-class pattern classification. There are different techniques employed by SVMs to tackle multi-class problems, namely oneversus-one (OVO), one-versus-all (OVA), and directed acyclic graph (DAG). When dealing with multi-class classification, one needs an appropriate technique to effectively extend these binary classification methods for multi-class classification. We address this issue by extending a novel architecture that we refer to as unbalanced decision tree (UDT). UDT is a binary decision tree arranged in a top-down manner, using the optimal margin classifier at each split to relieve the excessive time in classifying the test data when compared with the DAG-SVMs. The initial version of the UDT required a longer training time in finding the optimal model for each decision node of the tree. In this work, we have drastically reduced the excessive training time by finding the order of classifiers based on their performances during the selection of the root node and fix this order to form the hierarchy of the decision tree. UDT involves fewer classifiers than OVO, OVA and DAG -SVMs, while maintaining accuracy comparable to those standard techniques.
支持向量机是一种先进的学习机器,应用于模式识别、计算机视觉、数据挖掘和生物信息学等领域。支持向量机最初是为解决二元分类问题而开发的,但二元支持向量机也被扩展到解决多类模式分类问题。支持向量机使用不同的技术来处理多类问题,即一对一(OVO)、一对一全(OVA)和有向无环图(DAG)。在处理多类分类问题时,需要适当的技术将这些二值分类方法有效地扩展到多类分类中。我们通过扩展一种我们称之为不平衡决策树(UDT)的新体系结构来解决这个问题。UDT是一种自顶向下排列的二叉决策树,与dag - svm相比,UDT在每个分割处使用最优边际分类器,以减轻对测试数据进行分类的过多时间。UDT的初始版本需要更长的训练时间来为树的每个决策节点找到最优模型。在这项工作中,我们通过在根节点的选择过程中根据分类器的表现找到分类器的顺序并固定这个顺序来形成决策树的层次结构,从而大大减少了过多的训练时间。UDT涉及比OVO、OVA和DAG - svm更少的分类器,同时保持与这些标准技术相当的准确性。
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引用次数: 5
Investigating individual game-play patterns using a self-organzing map 使用自组织地图调查个人游戏模式
M. Wickramasinghe, K. Gunawardana, J. Rajapakse, D. Alahakoon
Computer games are played by a diverse range of players which has as diverse preferences and strategies to overcome the game. Most of these strategies are forecasted by the developers and is addressed accordingly in game AI, so the feeling of engagement with the game is not lost. However, with time, these game AI strategies become mundane and repetitive which generally results in exploitation by the players. This could be avoided if game AI is catered towards individual user's preferences and quirks. However, this type of adaptation seems distant with the current game AI methods. One viable approach of achieving this level of personalization is to learn player tactics from the player itself and use it to adapt the game AI to create an absorbing play experience. This paper investigates the possibility of understanding decision making patterns of an individual player using play data from the 2D arcade game Pacman via an unsupervised learning approach.
电脑游戏是由各种各样的玩家玩的,他们有不同的偏好和策略来克服游戏。大多数这些策略都是由开发者预测的,并在游戏AI中得到相应的处理,所以玩家对游戏的沉浸感不会消失。然而,随着时间的推移,这些游戏AI策略会变得单调和重复,这通常会导致玩家利用这些策略。如果游戏AI能够迎合个人用户的喜好和怪癖,这便能够避免这种情况。然而,这种类型的适应似乎与当前的游戏AI方法相去甚远。实现这种个性化水平的一个可行方法是,从玩家身上学习玩家策略,并利用它来调整游戏AI,创造吸引人的游戏体验。本文利用2D街机游戏《吃豆人》中的游戏数据,通过无监督学习方法研究了理解个体玩家决策模式的可能性。
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引用次数: 3
Defect classification of TFT-LCD with bag of visual words approach 基于视觉词袋法的TFT-LCD缺陷分类
Wei Huang, Hongtao Lu
A defect classification algorithm with bag of visual words approach for thin film transistor liquid crystal display (TFT-LCD) manufacturing is proposed in this paper. Color and SIFT features are introduced to describe defect region. Visual words vocabularies are learnt separated for each features. The two features are separately coded in bag of visual words and combined by multiple chi-square kernel SVM. Classifier performances with different parameters are compared in experiments. Finally a good enough classifier for identifying 5 classes of defect is achieved.
提出了一种基于视觉词袋法的薄膜晶体管液晶显示器缺陷分类算法。引入颜色特征和SIFT特征来描述缺陷区域。视觉词汇是根据每个特征分开学习的。将这两个特征分别编码到视觉词包中,并用多个卡方核支持向量机进行组合。实验中比较了不同参数下分类器的性能。最后得到了一个足够好的分类器,可以识别5类缺陷。
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引用次数: 0
DecisionAI: A framework to automate the decision making process DecisionAI:自动化决策制定过程的框架
K. T. Buddhika, D. Jayamanne, P. P. Wljegunawardana, R. C. Gunasekera, U. Kohomban
Accurate decision making is the key to make a business profitable. Decision support systems are used to make the decision making process accurate and easy. Even though there are many business specific decision support systems they cannot be used for general purpose decision making or outside their domain. DecisionAI provides a framework which can be used in any decision making domain with similar decision types. DecisionAI provides a good solution to many decision making problems in the industry allowing detailed analysis of data with the integrated intelligence.
准确的决策是企业盈利的关键。决策支持系统用于使决策过程准确和容易。尽管有许多业务特定的决策支持系统,但它们不能用于通用决策制定或其领域之外的决策制定。DecisionAI提供了一个框架,该框架可用于具有类似决策类型的任何决策制定领域。DecisionAI为行业中的许多决策问题提供了很好的解决方案,允许使用集成智能对数据进行详细分析。
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引用次数: 0
Research of smart charging management system for Electric Vehicles based on wireless communication networks 基于无线通信网络的电动汽车智能充电管理系统研究
Zengquan Yuan, Haiping Xu, Huachun Han, Yingjie Zhao
With the rapid development of Electric Vehicles (EVs), large-scale charging requirement will heavily impact the existing power grid. So there is an urgent need for coordinating control to avoid it in smart grids. Demand side management reducing charging rate at peak load and rescheduling charging process at appropriate time such as low grid load can be used to solve this issue. This paper proposed a coordinating control charging management system for EVs charging station, which is comprised of single-node charging controllers and a centralized management system. Electric Vehicle Charging Controller (EVCC) implemented via PWM signal to control charging current and charging time. As a crucial component of centralized control, Smart Electric Vehicles Charging Management System (EVCMS) obtains charging data and transmits control instructions via ZigBee and GPRS wireless communication networks technology. For calculating the charging current that each EV needs, a model of battery State-Of-Charge (SOC) is included, and each EVCC gets initial battery SOC, battery capacity and other data through CAN-Bus. In the end, the design of ZigBee and GPRS is discussed, and this two-way wireless communication networks is low power consumption, small size, high reliability, and easy expansion.
随着电动汽车的快速发展,大规模充电需求将对现有电网造成严重冲击。因此,在智能电网中迫切需要协调控制来避免这一问题。通过需求侧管理,降低高峰负荷时的充电率,在电网低负荷时重新安排充电过程,可以解决这一问题。提出了一种由单节点充电控制器和集中管理系统组成的电动汽车充电站协调控制充电管理系统。电动汽车充电控制器(EVCC)通过PWM信号控制充电电流和充电时间。智能电动汽车充电管理系统(EVCMS)作为集中控制的重要组成部分,通过ZigBee和GPRS无线通信网络技术获取充电数据并传输控制指令。为了计算每辆电动汽车所需的充电电流,引入了电池SOC (State-Of-Charge)模型,每个EVCC通过CAN-Bus获得初始电池SOC、电池容量等数据。最后讨论了ZigBee和GPRS的设计,这种双向无线通信网络具有功耗低、体积小、可靠性高、易于扩展等特点。
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引用次数: 17
Disturbance rejection analysis of a disturbance observer based velocity controller 基于扰动观测器的速度控制器抗扰性分析
H. R. Senevirathne, A. Abeykoon, M. Pillai
Motion control usually includes the precise control of position/velocity and acceleration control while accurate acceleration control is not useful in many applications. Traditional position/velocity control is derived by feedback based, PID controllers. However the disturbance observer further increases the stability and robustness of the controller. In this paper we assess the effectiveness of the Disturbance Observer working together with a tuned PID controller. Velocity response is compared with and without the disturbance observer. The proposed disturbance observer based velocity controller produce better results than the traditional velocity controller.
运动控制通常包括位置/速度的精确控制和加速度控制,而精确的加速度控制在许多应用中是没有用的。传统的位置/速度控制是由基于反馈的PID控制器导出的。而扰动观测器进一步提高了控制器的稳定性和鲁棒性。在本文中,我们评估了扰动观测器与调谐PID控制器一起工作的有效性。比较了有和没有扰动观测器时的速度响应。所提出的基于扰动观测器的速度控制器比传统的速度控制器具有更好的控制效果。
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引用次数: 11
Classification model of seed cotton grade based on least square support vector machine regression method 基于最小二乘支持向量机回归方法的种棉品级分类模型
Si Chen, Li-na Ling, Rong-chang Yuan, Long-qing Sun
Grade classification of seed cotton is a major problem that has an significant impact on the agricultural economy. According to characteristics like impurities, yellowness and brightness that extract from images of seed cotton, constructing classification model of seed cotton base on the least square method. Using support vector machine regression to come up with a well improved algorithm. After full learning, seed cotton classification accuracy satisfy the actual application needs.
种棉等级分级是影响我国农业经济的重大问题。根据从籽棉图像中提取的杂质、黄度、亮度等特征,基于最小二乘法构建籽棉分类模型。利用支持向量机回归提出了一种很好的改进算法。经过充分学习,种棉分类精度满足实际应用需要。
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引用次数: 3
Design and development of power optimized satellite elephant collar with over the air programmability 具有空中可编程能力的功率优化卫星象项圈的设计与研制
B. Annasiwaththa, R. Munasinghe, P. Fernando, P. Leimgruber
A satellite elephant collar is a device mounted on an elephant's neck to track its position and movements. This information is essential for conservation and management of this highly endangered species. Currently available units are proprietary designs by few manufacturers and no literature can be found about their internal operation. This lack of published information hampers the evolution and development of future collaring systems with increased features and functionalities for research, conservation and management. Critical issues for improvement include live time of the collar, which is related to power consumption and operational modes of the unites, and remote programmability allowing for changes in data acquisition during deployment. Most commercially available collars lack the ability to change data acquisition schedules remotely over the air, and therefore data acquisition is un-optimized, which is directly responsible for un-optimized power consumption. This research was conducted to develop a satellite elephant collar with improved lifetime and remote programmability. A second purpose of our research was to make information on how to built elephant collars needs to become widely available to the user community,. This paper presents the particular issue of power optimization of satellite elephant collars. A functional test collar was designed using general purpose electronic components and a number of software and hardware optimization methods used during development which are presented in this paper. An expected life time over 580 days was achieved with eight D size Ultralife U10015 batteries for the prototype collar.
卫星大象项圈是一种安装在大象脖子上的装置,用于跟踪大象的位置和运动。这些信息对于保护和管理这种高度濒危物种至关重要。目前可用的单位是少数制造商的专有设计,没有关于其内部操作的文献可以找到。缺乏公开的信息阻碍了未来项圈系统的演变和发展,这些系统具有更多的特征和功能,可用于研究、保护和管理。改进的关键问题包括接箍的使用时间,这与单元的功耗和操作模式有关,以及远程可编程性,允许在部署过程中更改数据采集。大多数商用项圈缺乏通过无线远程更改数据采集计划的能力,因此数据采集没有得到优化,这直接导致了未优化的功耗。本研究旨在开发一种具有改进寿命和远程可编程性的卫星象项圈。我们研究的第二个目的是使如何制造大象项圈的信息能够广泛地提供给用户社区。本文研究了卫星象项圈的功率优化问题。本文采用通用电子元件设计了一个功能测试环,并介绍了开发过程中使用的一些软硬件优化方法。使用8块D尺寸的Ultralife U10015电池,原型项圈的预期使用寿命超过580天。
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引用次数: 1
期刊
2012 IEEE 6th International Conference on Information and Automation for Sustainability
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