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Underwater tracking of a moving dipole source using an artificial lateral line: Algorithm and experimental validation with ionic polymer-metal composite flow sensors

机译:使用人工侧线在水下跟踪移动偶极子源:使用离子聚合物-金属复合材料流量传感器的算法和实验验证

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Motivated by the lateral line system of fish, arrays of flow sensors have been proposed as a new sensing modality for underwater robots. Existing studies on such artificial lateral lines (ALLs) have been mostly focused on the localization of a fixed underwater vibrating sphere (dipole source). In this paper we examine the problem of tracking a moving dipole source using an ALL system. Based on an analytical model for the moving dipole-generated flow field, we formulate a nonlinear estimation problem that aims to minimize the error between the measured and model-predicted magnitudes of flow velocities at the sensor sites, which is subsequently solved with the Gauss-Newton scheme. A sliding discrete Fourier transform (SDFT) algorithm is proposed to efficiently compute the evolving signal magnitudes based on the flow velocity measurements. Simulation indicates that it is adequate and more computationally efficient to use only the signal magnitudes corresponding to the dipole vibration frequency. Finally, experiments conducted with an artificial lateral line consisting of six ionic polymer-metal composite (IPMC) flow sensors demonstrate that the proposed scheme is able to simultaneously locate the moving dipole and estimate its vibration amplitude and traveling speed with small errors.
机译:在鱼的侧线系统的激励下,流量传感器阵列被提出作为水下机器人的一种新的传感方式。对这样的人工横线(ALL)的现有研究主要集中在固定的水下振动球(偶极子源)的定位上。在本文中,我们研究了使用ALL系统跟踪运动偶极子源的问题。基于运动偶极子产生的流场的分析模型,我们制定了一个非线性估计问题,旨在最小化传感器位置处流速的实测值与模型预测值之间的误差,随后用高斯方程求解。牛顿方案。提出了一种滑动离散傅立叶变换(SDFT)算法,可以根据流速测量结果有效地计算信号的演变幅度。仿真表明仅使用与偶极子振动频率相对应的信号幅度是足够的,并且在计算上更加有效。最后,使用由六个离子聚合物-金属复合材料(IPMC)流量传感器组成的人工侧向线进行的实验表明,该方案能够同时定位运动偶极子并估计其振动幅度和行进速度,且误差很小。

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