Resistive sensors are constrained by an inherent parasitic capacitance, which varies depending on different parameters. Additionally, a resistive sensor’s base offset resistance is quite high compared to the change in the sensor’s resistance, lowering the measuring system’s resolution. Not considering these undesired inherent resistive sensor parameters results in the wrong quantification of the sensor resistance value. The relaxation oscillator is a class of resistance-to-frequency configurations employed for frequency modulation based on correspondence to resistance change. This paper proposes a relaxation oscillator-based circuit for converting resistance to frequency change. In the proposed design, parasitic capacitance elimination is achieved using a single op-amp as a front end. The proposed scheme is immune to variation in parasitic capacitance variation in the range of 1–140 pF, yielding a relative error as low as 0.2%.

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Relaxation-Oscillator Based Interface Circuit for Leaky Resistive Sensors

  • Mohamad Idris Wani,
  • Tarikul Islam,
  • Laxmeesha Somappa,
  • Sameer Sonuksale,
  • Shahid Malik

摘要

Resistive sensors are constrained by an inherent parasitic capacitance, which varies depending on different parameters. Additionally, a resistive sensor’s base offset resistance is quite high compared to the change in the sensor’s resistance, lowering the measuring system’s resolution. Not considering these undesired inherent resistive sensor parameters results in the wrong quantification of the sensor resistance value. The relaxation oscillator is a class of resistance-to-frequency configurations employed for frequency modulation based on correspondence to resistance change. This paper proposes a relaxation oscillator-based circuit for converting resistance to frequency change. In the proposed design, parasitic capacitance elimination is achieved using a single op-amp as a front end. The proposed scheme is immune to variation in parasitic capacitance variation in the range of 1–140 pF, yielding a relative error as low as 0.2%.