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排序方式: 共有1347条查询结果,搜索用时 15 毫秒
41.
The sensitivity of the suspended sediment flux is tested with respect to rapid changes in bed-level across the surf zone of a sandy beach. The suspended flux was computed using a fixed instrument array, but bed-level changes due to ripple migration caused the instrument elevations to be significantly changed during the course of the experiment. The nominal elevations of the instruments were adjusted during data processing (using the MOBS array) to maintain a fixed elevation with respect to bed-level changes. The resultant suspended sediment concentrations and fluxes were significantly different from the unadjusted data, and for the present data set O(35%) less when averaged over the tide. The maximum difference between adjusted and unadjusted fluxes may be O(260%). The results indicate that changes in bed-level, particularly those due to bedform migration, must be accounted for when processing OBS data if reliable estimates of suspended sediment transport are to be obtained in the field. 相似文献
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The drilling parameter monitor is an important tool in drilling engineering applied to monitoring drilling process, carrying out scientific analysis and decision-making. Based on discussing the present development situation of the domestic and foreign drilling machine parameter monitors, the metering scheme for vehicle-loaded drilling parameter monitor was designed. By using detection system for MSP430 single-chip microcomputer (SCM) in combination with peripheral circuit such as sensors, the drilling-rig control system was obtained to detect, and for every parameter in real-time display in order to keep operating the drilling rig status. The experiment shows that the drilling parameter monitor reaches design requirements and can be applied to drilling engineering monitoring, which has characters such as simple structure, high credibility and low cost. 相似文献
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基于模糊控制的快速循迹智能车的设计与实现 总被引:1,自引:0,他引:1
提出基于模糊控制的快速循迹智能车的实现方法.利用转速传感器、线阵CCD、舵机等构成一个闭环控制系统,并采用PI算法控制智能车后轮速度.采用模糊控制算法将线阵CCD返回的误差模糊化,然后按照MAX-MIN规则进行逻辑推理,最后将推理结果反模糊化后以控制舵机转向.实验结果证明了该方法的有效性. 相似文献
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随着全球范围移动互联网的高速发展,人们作为"传感器"行走在真实社会中制造实时的、实地环境的、大范围的地理信息,特别是具有互动性和实时性的区域环境状况的地理信息。这类数据具有交互性、实时性、丰富性、社会性等特点,成为数据科学家眼中的金矿。基于"互联网+"时代背景,随着移动互联网、移动GIS技术和LBS技术日趋成熟,本文提出了基于移动GIS的生态环境智能感知方法,开发基于Android平台的APP,实现查询环境质量指数、查看环境污染地图、污染一键分享和解决等功能,从大众的视角感知和获取生态环境信息,为大众提供实时动态环境信息查询方式,引导鼓励公众参与环境保护,提供治理环境污染和地理信息资源获取的新思路。 相似文献
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Catia Real Ehrlich 《地球空间信息科学学报》2019,22(2):73-88
ABSTRACTThe localization of persons or objects usually refers to a position determined in a spatial reference system. Outdoors, this is usually accomplished with Global Navigation Satellite Systems (GNSS). However, the automatic positioning of people in GNSS-free environments, especially inside of buildings (indoors) poses a huge challenge. Indoors, satellite signals are attenuated, shielded or reflected by building components (e.g. walls or ceilings). For selected applications, the automatic indoor positioning is possible based on different technologies (e.g. WiFi, RFID, or UWB). However, a standard solution is still not available. Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions, e.g. additional infrastructures or sensor technologies. Smartphones, as popular cost-effective multi-sensor systems, is a promising indoor localization platform for the mass-market and is increasingly coming into focus. Today’s devices are equipped with a variety of sensors that can be used for indoor positioning. In this contribution, an approach to smartphone-based pedestrian indoor localization is presented. The novelty of this approach refers to a holistic, real-time pedestrian localization inside of buildings based on multi-sensor smartphones and easy-to-install local positioning systems. For this purpose, the barometric altitude is estimated in order to derive the floor on which the user is located. The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors. In order to minimize the strong error accumulation in the localization caused by various sensor errors, additional information is integrated into the position estimation. The building model is used to identify permissible (e.g. rooms, passageways) and impermissible (e.g. walls) building areas for the pedestrian. Several technologies contributing to higher precision and robustness are also included. For the fusion of different linear and non-linear data, an advanced algorithm based on the Sequential Monte Carlo method is presented. 相似文献
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