Sensors: Sensing Rich Drive Trains for Modern Mechatronic Systems

传感器：传感现代机电系统的丰富传动系统

• 批准号: 0529451
• 负责人: Masayoshi Tomizuka
• 金额: --
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-15 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0529451&HistoricalAwards=false
• 关键词: Sensors; Sensing; Rich; Drive; Trains

AbstractCMS-0529451PI: Masayoshi Tomizuka (University California, Berkeley)This research develops mechatronic approaches to the design of drive trains for mechanical systems based on heavy sensing. A typical drive train includes an actuator (electrical motor), a set of gears, bearings and an inertia load (link), which may be connected to another drive train or an end effecter. The technical objectives of the research are to 1) study sensing of various signals in the drive train, in particular, those not utilized in conventional practice such as acceleration signals, force signal in the drive train and end effector's position, 2) develop signal processing and decision making algorithms that take advantages of the sensed signals for betterment of performance and other mechatonic advantages, and 3) demonstrate these benefits experimentally. New signal processing and decision making algorithms will handle nonlinearities and uncertainties in drive train mechanisms as well as the environment in which drive trains and entire mechanical systems operate. This will bring advantages to both producers and end users of mechanical systems, e.g. robots, assembly machines and other manufacturing equipment. The broader impacts will be from education, outreach and international collaboration. The project team includes the Principal Investigator, graduate student researchers and undergraduate researchers. Undergraduate students will be involved in this project through participation in experiments and mechatronics design. This is a sensor award under the solicitation NSF 05-526.

摘要CMS-0529451PI：Masayoshi Tomizuka（加州大学伯克利分校）这项研究开发了基于重传感的机械系统传动系统设计的机电一体化方法。 典型的传动系统包括致动器（电动机）、一组齿轮、轴承和惯性负载（连杆），它们可以连接到另一个传动系统或末端执行器。研究的技术目标是 1) 研究传动系统中各种信号的传感，特别是传统实践中未使用的信号，例如加速度信号、传动系统中的力信号和末端执行器的位置，2) 开发信号处理以及利用感测信号来改善性能和其他机电优势的决策算法，以及 3）通过实验证明这些优势。新的信号处理和决策算法将处理传动系统机构以及传动系统和整个机械系统运行环境中的非线性和不确定性。 这将为机械系统的生产商和最终用户带来优势，例如机器人、装配机和其他制造设备。 更广泛的影响将来自教育、推广和国际合作。 项目团队包括首席研究员、研究生研究员和本科生研究员。本科生将通过参与实验和机电一体化设计来参与该项目。 这是 NSF 05-526 征集下的传感器奖项。