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An Efficient Inductance-to-Digital Converter Insensitive to Coil Resistance of Differential Type Inductive Sensors

Publication Type : Journal Article

Publisher : Springer Nature Switzerland

Source : Lecture Notes in Electrical Engineering

Url : https://doi.org/10.1007/978-3-031-29871-4_28

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication

Year : 2023

Abstract : This paper proposes an Inductance-to-Digital Converter (LDC) that measures the change in inductance ∆L of a Differential-type Inductive Sensor (DIS) independent of its coil resistance. The ∆L is measured using a ratio metric approach that eliminates error due to the tolerances of the components used in the circuit. The proposed LDC is realized using a simple dual-slope conversion technique and possesses advantages such as noise immunity and high accuracy. Existing schemes for measuring differential inductance assume the coil resistance is negligible or equally matched. This assumption may not be practical always, and hence a noticeable error in inductance measurement will be introduced in the existing architectures, while the proposed design does not suffer from this limitation. In addition, the final output provided by the proposed LDC will always be proportional to the measurand, irrespective of whether the measurand has a linear or inverse relationship with the sensor inductance. The prototype developed showed superior performance with a worst-case error of 0.72% when the series coil resistance was varied from 0 to 1000 Ω in steps of 100 Ω. Moreover, the developed architecture showed a good resolution of 3.5 µH and high linearity, with a worst-case error of 0.55% when ∆L was varied from –6 mH to +6mH.

Cite this Research Publication : P. P. Narayanan, Sreenath Vijaykumar, R. Rahul Raja, V. Sowbaranic Raj, Karthi Balasubramanian, An Efficient Inductance-to-Digital Converter Insensitive to Coil Resistance of Differential Type Inductive Sensors, Lecture Notes in Electrical Engineering, Springer Nature Switzerland, 2023, https://doi.org/10.1007/978-3-031-29871-4_28

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