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首页> 外文期刊>Sensors and Actuators, A. Physical >Nanoforce estimation based on Kalman filtering and applied to a force sensor using diamagnetic levitation
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Nanoforce estimation based on Kalman filtering and applied to a force sensor using diamagnetic levitation

机译:基于卡尔曼滤波的纳米力估计,并应用于抗磁悬浮力传感器

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摘要

Nanoforce sensors based on passive diamagnetic levitation with a macroscopic seismic mass are a possible alternative to classical Atomic Force Microscopes when the force bandwidth to be measured is limited to a few Hertz. When an external unknown force is applied to the levitating seismic mass, this one acts as a transducer that converts this unknown input into a displacement that is the measured output signal. Because the under-damped and long transient response of this kind of macroscopic transducer cannot be neglected for time-varying force measurement, it is then necessary to deconvolve the output to correctly estimate the unknown input force. The deconvolution approach proposed in this paper is based on a Kalman filter that use an uncertain a priori model to represent the unknown nanoforce to be estimated. The main advantage of this approach is that the end-user can directly control the unavoidable trade-off that exists between the wished resolution on the estimated force and the response time of the estimation.
机译:当要测量的力带宽限制在几赫兹时,基于具有宏观地震质量的被动反磁悬浮的Nanoforce传感器可能是经典原子力显微镜的替代方案。当外部未知力施加到悬浮的地震质量上时,该外部力将作为一种传感器,将未知输入转换为位移,该位移即测得的输出信号。因为对于时变力测量而言,这种宏观传感器的阻尼不足和较长的瞬态响应是不能忽略的,因此有必要对输出进行解卷积以正确估计未知输入力。本文提出的反卷积方法基于卡尔曼滤波器,该卡尔曼滤波器使用不确定的先验模型来表示要估计的未知纳米力。这种方法的主要优点是,最终用户可以直接控制在对力估计的期望分辨率与响应时间之间不可避免的折衷。

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