触觉传感器及感知技术研究现状与发展趋势

触觉感知技术可用于对物体的探索和操作,对环境的交互作用具有重要意义。本文从介绍触觉传感器应满足的机械手操作任务要求出发,全面综述了不同类型触觉传感器的结构和工作原理,并分析了它们的优缺点。分析讨论触觉传感器在人工皮肤和生物医学领域的应用现状,最后总结了先进的机器学习算法和信号处理技术在触觉传感系统中的应用。     

传感器信号失准原因分析与研究

通过对典型故障实例深入分析,研究微机控制系统中传感器信号失准的原因,详细介绍由传感器本身电器性能、电磁干扰、线路故障等因素引起的传感器信号失准现象及产生的故障机理。     

错位交叉口信号控制优化研究

从错位交叉口自身特点及其对交通流的影响方面讨论了错位交叉口2个T形口距离与信号控制方式的关系,确定了控制方式选择的T形口距离阈值,并从信号控制相位优化和配时优化方面重点介绍了将错位交叉口作为一个大型交叉口进行综合控制的信号优化方法.     

十字环形交叉口两种信号控制设计方法比较

为了对环形交叉口进行合理信号配时设计,提高信号控制环形交叉口服务水平,对"多进口道放行协同环道控制"和"单口放行控制"两种较为常用的环形交叉口信号控制设计方法进行了比较分析.首先介绍了两种信号控制设计基本方法,并从通行能力、延误和可靠性3个方面进行对比,最后通过实例分析对结果进行验证.研究结果表明:"多进口道放行协同环道控制"方法在信号配时良好且环道有足够左转待行空间的情况下,对于通行能力和延误而言有着更强的适应性,但该控制方法对配时设计的要求更高,且不能完全避免交通"死锁",需制定紧急预案予以应对.     

Automatic artist recognition of songs for advanced retrieval

Automatic recognition of artists is very important in acoustic music indexing, browsing, and contentbased acoustic music retrieving, but synchronously it is still a challenging errand to extract the most representative and salient attributes to depict diversiform artists. In this paper, we developed a novel system to complete the reorganization of artist automatically. The proposed system can efficiently identify the artist's voice of a raw song by analyzing substantive features extracted from both pure music and singing song mixed with accompanying music. The experiments on different genres of songs illustrate that the proposed system is possible.     

Probability-based clustering and its application to WLAN location estimation

Wireless local area networks (WLAN) localization based on received signal strength is becoming an important enabler of location based services. Limited efficiency and accuracy are disadvantages to the deterministic location estimation techniques. The probabilistic techniques show their good accuracy but cost more computation overhead. A Gaussian mixture model based on clustering technique was presented to improve location determination efficiency. The proposed clustering algorithm reduces the number of candidate locations from the whole area to a cluster. Within a cluster, an improved nearest neighbor algorithm was used to estimate user location using signal strength from more access points. Experiments show that the location estimation time is greatly decreased while high accuracy can still be achieved.     

Multi-objective signal control of urban junctions – Framework and a London case study

This paper presents an approach to multi-objective signal control using fuzzy logic. The signal control uses fuzzy logic where the membership functions are optimised according to the Bellman–Zadeh principle of fuzzy decision-making. This approach is both practical for the decision-maker and efficient, as it leads directly to a Pareto-optimal solution. Signal control priorities are ultimately a political decision. Therefore the tool developed in this research allows the traffic engineer to balance the objectives easily by setting acceptability and unacceptability thresholds for each objective. Particular attention is given in the example to pedestrian delays. The membership functions of the fuzzy logic are optimised by a genetic algorithm coupled to the VISSIM microscopic traffic simulator. The concept is illustrated with a case study of the Marylebone Road–Baker Street intersection in London at which pedestrians as well as vehicle flows are high. The results prove the feasibility of the framework and show the vehicle delays for a more pedestrian friendly signal control strategy.     

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公交信号优先系统在投入使用以前要经过严格的测试分析。交通仿真虽然在这方面是一个很好的工具,但它往往需要大量的路网输入,数据采集以及模型校准等工作。而且,交通仿真模型的开发都是根据不同的项目“量身定做”,项目完成即被丢弃,很难再重复使用到其它项目上去。本文探讨用交叉口容量分析的方法来评价公交信号优先对公交车以及其它车辆的影响。就目前最常用的两种公交信号优先方法,即“绿信号先导”和“绿信号延长”展开分析,用大家熟知的韦伯思特的图形方法来诠释这两种方法对公交车辆和其它车辆交叉口延迟的影响.采用交通仿真对分析结果进行的统计验证表明,用分析方法得到的结论是可靠的。     

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北京2008年奥运会期间,北京市采取了一系列奥运交通保障措施,交叉口公交信号优先是其中重要的一项内容。本文首先介绍了交叉口公交优先和紧急优先的控制逻辑和控制策略,然后讲述了奥体中心区利用射频技术进行交叉口公交车信号优先和奥运VIP车辆信号紧急优先的实现方式和实现过程,简述了海信信号机公交优先和紧急优先信号配置方法;最后,对奥体中心区公交优先和紧急优先的实施效果进行了总结和评价,并给出了城市公交信号优先方面的几点建议。     

基于时-频相干与 RBF 网络的气缸压力识别研究

针对从缸盖振动信号中分离燃烧激励引起的振动信号及其他干扰信号的问题,提出一种基于时‐频相干与神经网络的气缸压力识别方法。首先采用 Morlet 连续小波变换分别将缸盖振动信号和缸压信号在时‐频域内展开,然后采用交叉小波对两信号进行时‐频相干分析,设定相干系数阈值并进行掩膜处理,对所得结果重构便可得到燃烧激励引起的缸盖振动信号。最后,选取8个参数作为评价燃烧效果的特征指标,利用径向基函数（RBF）神经网络估计缸压。研究结果表明：该方法有效地提取了缸盖上的燃烧特征信号,通过 RBF 神经网络估计缸压,逼近于实际缸压变化。