Estimators for Inductive-Coupling Based Batteryless Wireless High-Frequency Sensing

Sivaramakrishnan, S.; Rajamani, Rajesh

doi:10.1109/acc.2007.4282811

Cited by 2 publications

(4 citation statements)

References 6 publications

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“…For the simplicity of analysis, let us replace and with and , respectively. Then, (14) becomes (15) It is noted that if there is no error in the parameters and , then but the capacitance estimation still suffers from the detrimental effects stemming from other parameter error such as and the selected parameter values and which are all included in and in (15). Equation (15) seems to provide a clue for determining how to compensate the undesirable mismatch resulting from the parameter uncertainties so that the inverse of the estimated capacitance affected by some parameter errors and the corresponding error functions is linearly approximated by the inverse of the true capacitance in such a linear manner as where and are defined as follows: (16) Assuming the telemetry distance is constant, that is, two functions and are constant, the scaling deviation is proportional to the error in while the offset is proportional to the resistance , the inductance and the corresponding errors as well as the operating frequency .…”

Section: B Robustness Of Sensormentioning

confidence: 98%

“…Recall that the parameter errors in and do not change and as confirmed with their definitions in (10). Based on this observation, the capacitance estimation formula in (11) combined with some parameter errors ( and ) and the corresponding error functions ( and ) must be recast as follows: (14) where corresponds to the estimated capacitance that is affected by some parameter errors and the corresponding error functions. For the simplicity of analysis, let us replace and with and , respectively.…”

Section: B Robustness Of Sensormentioning

confidence: 99%

“…The mathematical model of the inductive coupling-based wireless sensor system is given in (1) which is derived based on the coil equations of two magnetically coupled coils [14] (1)…”

Section: Operating Principle Of Inductivementioning

confidence: 99%

See 2 more Smart Citations

A Novel Real-Time Capacitance Estimation Methodology for Battery-Less Wireless Sensor Systems

et al. 2010

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This paper presents a novel method to read a passive capacitive sensor in telemetry by using inductive coupling. While classical inductive coupling approaches measure sensor capacitance by identifying the resonant frequency of the sensor with a sweep of radio frequency (RF) signals, the proposed method estimates the capacitance change in real-time by algebraically manipulating two measurements (the magnitude and the phase of the reflected sensor impedance). Only one RF signal is used in the proposed method instead of a frequency sweep. Analysis is provided to show that some physical parameter errors can deteriorate the capability of the proposed method in accurately measuring sensor capacitance. However, the use of a first order calibration procedure based on error analysis overcomes this shortcoming. Extensive experimental results with the proposed method combined with a first order calibration show that multifrequency and rapid changes in sensor capacitance can be estimated reliably under varying locations and orientations of the interrogator. The battery-less wireless sensors enabled by the developed technology in this paper can be widely used for measurement of fluid pressure, force, acceleration and other capacitance-change based sensor measurements.

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Section: B Robustness Of Sensormentioning

confidence: 98%

Section: B Robustness Of Sensormentioning

confidence: 99%

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A Novel Real-Time Capacitance Estimation Methodology for Battery-Less Wireless Sensor Systems

et al. 2010

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“…Radiofrequency (RF) sensing offers an alternative wireless method which can overcome the issues associated with these other techniques. Inductor-capacitor ( LC ) resonant circuits have been utilized in many wireless sensing applications [ 10 – 23 ]. Various physical parameters such as temperature [ 10 , 11 ], pressure [ 12 , 13 ], strain [ 14 ] and pH [ 16 ] have been wirelessly measured with the resonant RF approach.…”

Section: Introductionmentioning

confidence: 99%

Wireless Displacement Sensing of Micromachined Spiral-Coil Actuator Using Resonant Frequency Tracking

Ali

AbuZaiter

Schlosser

et al. 2014

Sensors

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This paper reports a method that enables real-time displacement monitoring and control of micromachined resonant-type actuators using wireless radiofrequency (RF). The method is applied to an out-of-plane, spiral-coil microactuator based on shape-memory-alloy (SMA). The SMA spiral coil forms an inductor-capacitor resonant circuit that is excited using external RF magnetic fields to thermally actuate the coil. The actuation causes a shift in the circuit's resonance as the coil is displaced vertically, which is wirelessly monitored through an external antenna to track the displacements. Controlled actuation and displacement monitoring using the developed method is demonstrated with the microfabricated device. The device exhibits a frequency sensitivity to displacement of 10 kHz/μm or more for a full out-of-plane travel range of 466 μm and an average actuation velocity of up to 155 μm/s. The method described permits the actuator to have a self-sensing function that is passively operated, thereby eliminating the need for separate sensors and batteries on the device, thus realizing precise control while attaining a high level of miniaturization in the device.

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Estimators for Inductive-Coupling Based Batteryless Wireless High-Frequency Sensing

Cited by 2 publications

References 6 publications

A Novel Real-Time Capacitance Estimation Methodology for Battery-Less Wireless Sensor Systems

A Novel Real-Time Capacitance Estimation Methodology for Battery-Less Wireless Sensor Systems

Wireless Displacement Sensing of Micromachined Spiral-Coil Actuator Using Resonant Frequency Tracking

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