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28 Φεβ 2014 · The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°.
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A Multirate Control Strategy to the Slow Sensors Problem: An...
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A Multirate Control Strategy to the Slow Sensors Problem: An...
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In high precission static force calibration by dead weight machines this issue is covered to some degree by using polynomials of third order to model the sensor characteristics. The problem of non-linear sensor characteristics has been ignored in the case of dynamic calibration so far.
Did you know that the resolution, non-linearity and accuracy are amongst the most important features of a measuring sensor system? These vary significantly depending on the application requirement and the measuring principle. We will explain the terms now.
28 Φεβ 2014 · Using the finite element method (FEM) and particle swarm optimization (PSO), a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor.
1 Νοε 2009 · According to these results, the method can be used in sensors with a maximum nonlinearity relative error of 21%, yielding a maximum nonlinearity relative error output less than 1%. The best performance is achieved with eight calibration points in Case 2.
Guay (1996) introduced a nonlinearity measure based on the evaluation of the in- duced local curvature of the process response assuming a process can be represented by a twice-differentiable process map.
Abstract—This paper describes a method of linearizing the nonlinear characteristics of many sensors using an embedded neural network. The proposed method allows for complex neural networks with very powerful architectures to be embedded on a very inexpensive 8-bit microcontroller.
