Linearization of inverse-capacitance-based displacement transducers

Lányi, Š.; Hruškovic, Miloslav

doi:10.1088/0957-0233/12/1/310

Cited by 8 publications

(6 citation statements)

References 8 publications

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“…Feasibility of feedback compensation methods using trans-impedance amplifier, Miller theorem, inverse capacitance-based displacement transducers have been explored in many works (Azhari and Kaabi, 2000;Lanyi and Hruskovic, 2001;Ghallab and Badawy, 2006;Farshidi, 2011;Maundy and Gift, 2013;Sen et al, 2018). The trans-impedance amplifier feedback circuit has been reported for the compensation of single element, multi-element resistive, and capacitive sensors with high accuracy (0.4%) (de Graaf and Wolffenbuttel, 2006).…”

Section: Linearization By Feedback Methodsmentioning

confidence: 99%

Linearization of the sensors characteristics: a review

Islam¹,

Mukhopadhyay

2019

International Journal on Smart Sensing and Intelligent Systems

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Today, the sensing devices play an important role for various system automation and monitoring of different physical and chemical parameters. Nonlinearity is an important long-time issue for most of the sensors, so to compensate nonlinearity, various linearization schemes are reported in the literature. The accuracy of linearization schemes depends on the type and the nonlinearity value of the sensor output. Since it is difficult to find an exact polynomial equation or other functions to represent the response curve; it gives more error when the measurement parameter is determined from the inverse approximation functions. As many sensors are used for different applications, the linearized characteristics will simplify the design, calibration, and accuracy of the measurement. This paper presents a review of different methods applied to linearize sensor characteristics reported in the literature. Due to availability of high-performance analog devices, analog methods are still popular among many researchers. However, due to the advancement of IC technologies, hardware implementation of the software methods can be done easily with reduced time, cost, and more accuracy, so the digital methods combined with software techniques perform the job with better flexibility and efficiency.

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Section: Linearization By Feedback Methodsmentioning

confidence: 99%

Linearization of the sensors characteristics: a review

Islam¹,

Mukhopadhyay

2019

International Journal on Smart Sensing and Intelligent Systems

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“…It may be any impedance, e.g. a noiseless capacitance [5][6][7][8]10]. Since the individual noise contributions are uncorrelated, the resulting output voltage is the square root of the sum of their squares.…”

Section: The Buffermentioning

confidence: 99%

“…Let us mention e.g. measurements of cell potentials [1][2][3], contact potentials [4][5] and inverse capacitance-position transducers [6][7][8]. At low frequencies electrometric amplifiers or sensitive current-tovoltage converters, based on field-effect transistor (FET)-input operational amplifiers, may give satisfactory results, or the frequency range and/or sensitivity achieved is accepted as a compromise.…”

Section: Introductionmentioning

confidence: 99%

The noise of input stages with low parasitic capacitance

Lányi

2001

Meas. Sci. Technol.

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The noise of two types of input stages, that of a high-input-impedance buffer and that of a current-to-voltage converter, operated with high-impedance sources at relatively high frequencies, was analysed. It was found that the noise may achieve, at first sight, unexpectedly high values. In buffers the biasing circuit's noise is multiplied by the bootstrap. The input capacitance and the parasitic capacitance of the biasing circuit reduce the bandwidth but without affecting the signal-to-noise ratio. The input capacitance or any other capacitance connected to the input of the current-to-voltage converters may increase the noise gain by orders of magnitude and significantly reduce the signal-to-noise ratio. The results throw doubt on the frequently accentuated advantage of using current-to-voltage converters for amplifying low-level signals from high-impedance sources, at least at high frequencies.

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“…For practical applications, deviations from an ideal displacement measurement are determined by a calibration [ 5 ] and compensated electronically [ 19 ]. The general objective of this project is the systematic analysis of the different errors of capacitive displacement sensors in order to gain a comprehensive overview of the uncertainties and to compare them with the primary method for realizing the meter, the interferometry.…”

Section: Introductionmentioning

confidence: 99%

Influence of Geometric Properties of Capacitive Sensors on Slope Error and Nonlinearity of Displacement Measurements

Daul

Jin

Busch

et al. 2021

Sensors

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Capacitive sensors are widely used in industrial applications, such as CNC machine tools, where reliable positioning in the micrometer range with nanometer accuracy is required. Hence, these sensors are operated in harsh industrial environments. The accuracy of these sensors is mainly limited by slope errors and nonlinearities. In practice, the required accuracy of these sensors is achieved by a calibration against a metrological high-quality reference such as interferometric displacement measurement systems. This usually involves the use of high-order polynomials as calibration functions based on empirical data. In metrology, this is only the second-best approach and has disadvantages in terms of stability over the measurement range of the instrument. In addition, the validity of these empirical calibrations over time is questionable, and the associated uncertainty can only be roughly estimated. This makes regular recalibration of such sensors at short intervals mandatory to ensure the reliability of the displacement measurement. In this paper, we report on our investigations of the different parameters that affect the accuracy of capacitive sensors. Since the capacitance of these sensors results from the electric fields that build up between the electrodes, these field lines are calculated using FEM simulation models for typical commercial sensors. In the following the influence of various geometric parameters such as edge radius, guard ring size and shape, or thickness of the electrodes are individually analyzed according to their impact on the accuracy of these sensors. Based on these simulations, the deviations of the capacitance as they arise for real detector geometries can then be compared with idealized, de facto unrealizable parallel plate capacitors. This methodology allows overall uncertainty of capacitive sensors to be decomposed into their individual components and sorted in terms of their contribution to the uncertainty budget. The individual FEM-based analysis then enables a systematic analysis of the sources of uncertainty and, thus, reveals possibilities to improve manufacturing processes for capacitive sensors, to put these sensors on a solid metrological basis, and to improve the performance of these displacement measurement systems in the long run, i.e., to provide better sensors for the application.

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Linearization of inverse-capacitance-based displacement transducers

Cited by 8 publications

References 8 publications

Linearization of the sensors characteristics: a review

Linearization of the sensors characteristics: a review

The noise of input stages with low parasitic capacitance

Influence of Geometric Properties of Capacitive Sensors on Slope Error and Nonlinearity of Displacement Measurements

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