Wireless position sensing and normalization of embedded resonant sensors using a resonator array

https://doi.org/10.1016/j.sna.2020.111853Get rights and content

Highlights

  • An array of four resonators is sufficient to wirelessly determine X, Y, and angular position of a portable reader.

  • Position prediction is improved by taking multiple readings along a linear, ‘flyby’ path.

  • A resonant sensor can be embedded with the resonator array as long as the response signal is in a different frequency window.

  • The resonant array can correct for sensor signal changes caused by positional changes.

  • Useful when the sensor and reader cannot be fixed in place through the entire monitoring period, such as re-reading embedded sensors.

Abstract

In this work, four square, planar resonators with unique frequency windows were used to form a 2 by 2 array for wireless position determination and normalization of position-dependent, embedded resonant sensors. First, a master table of S|21| gain and phase data was collected at 8100 positions. Automated scripts extracted the characteristic gain and phase peaks and used cubic interpolation to expand the master table to 7,157,160 unique angle and coordinate positions. An unknown position is then determined by comparing its S|21| measurements to this table. To further improve the position accuracy, multiple measurements are collected on linear flyby trajectories. The average and standard deviation of predicted position offset from true value using this method were 3.2 and 2.3 mm, respectively. To test normalization of a position dependent sensor, a spiral resonant sensor was placed underneath the square array. The sensor signal was modulated using varying amounts of water on the sensor surface. A corrected reading was determined using four different flyby trajectories using the position array data to adjust the signal based on position. We found that average errors of the normalized signals were between 0.04 to 0.15 MHz at lower water volume (0.5 mL) and -0.53 to -0.74 MHz at higher water volume (2.0 mL). In its current state, the positional array can be used for asset tracking or feedback control and the sensor normalization can be used to improve the measurement accuracy of embedded sensors. This technique can be further improved by collecting more accurate master calibration data using an automated system.

Introduction

Resonant sensors, also known as LC sensors or LCR tanks, have been used in many applications such as wireless monitoring of temperatures [1,2], pressures [3,4], dielectrics [5,6], and enzyme activities [7]. They are composed of an inductor (L) and capacitor (C) which tune the circuit to resonate at a specific frequency. Upon interaction or activity of the analyte, the inductance and/or capacitance of the circuit modulates and the response is reported in a shift or attenuation of the resonant signal [8]. The resonant signal can be interrogated wirelessly using a vector network analyzer, observing the one-port (S11) or two-port (S21) scattering parameters (magnitude and phase of RF signal over a set frequency range). Typically these are very large, expensive benchtop units [8,9]. Because the resonator is energized by the vector network analyzer antennas via near-field coupling, there is no need for on-board power; however, the read range is typically limited to the <10 cm range [10]. The use of a periodic array can improve this read range [9]. If the resonators are tuned to the sub-microwave range (especially <150 Mhz), they have the added benefit of penetration into aqueous and biological systems [11], thus allowing for embedded sensors in traditionally opaque systems such as tissue [12], soil [13], and plastic parts [14].

One limitation of resonant sensors is the high-degree of positional sensitivity between the vector network analyzer reader antennas and the resonator. The scattering parameters and resonant frequency response are dependent upon the mutual inductance which is a function of the system geometry and separation distance [15]. All studies to date mitigate this problem by fixing the reader and resonant sensor in place or ensuring that they return to the same position via mechanical or optical alignment marks [6,13,14]. For example, a recent work demonstrated the ability to wirelessly measure alignment angle and angular velocity using a split ring resonator, but the method requires the X and Y positions to be fixed [16]. This works for static systems, or systems which allow for installation of positional cues, however there is no solution for systems which are completely embedded and do not allow for careful repositioning. An example of such a system would be resonant sensors embedded in the ground to measure the hydrolytic activity of soils in which an agronomist or tractor would return to the proximal site of the sensor and take a reading [13]. Without any method of position-based normalization, the user would not know if an observed signal shift was due to a change in the sensor or a change in the position of the reader in relation to the embedded sensor.

It is the purpose of this work to overcome this long-standing limitation through the design and demonstration of an array of resonators, that can be embedded with the resonant sensor and 1) provide positional feedback in a closed system and 2) allow for normalization of the resonant sensor. First, positional sensing is demonstrated using a 2 × 2 array of resonators fabricated with resonant frequencies in the 25−100 MHz range. These frequencies were chosen to match a low-cost portable VNA capable of measuring 0.1–180 MHz, which leaves the 100−180 MHz range for the resonant sensor response. Linear flyby paths with six measurements in the range of the array are then used to improve the spatial predictions. The spatial predictions are then used to normalize the response of a central resonant sensor, tuned to respond to volume of water, that is embedded with the array. Finally, next steps and intended applications of this work are discussed.

Section snippets

Results and discussion

To test position sensing using an embedded resonator array, an acrylic sheet was placed above four resonators at a step-off distance of 6 mm (Fig. 1). The sheet was patterned with a 14 × 14 cm major grid with 1 mm minor tick lines (using a laser cutter) to enable accurate reader placement. A handheld, two-port vector network analyzer with a custom co-planar two loop coil reader (Fig. 1c) is then used to measure the transmission scattering parameters, S21 gain and phase, as the sensor response (

Conclusions

In this work we demonstrate the use of a resonant array to accomplish wireless positional sensing, resolving both x–y location and angle. We found that with our manually-collected, interpolation data we can achieve an accuracy of 3.2 mm in x and y and 1.5° in angular. This could be further improved by collecting the master calibration data with an automated system, including more resonators in the array, or by increasing the number of S21 features that are used in the algorithm. We have also

Resonator fabrication

Four square spirals with pitch sizes of 1.2, 1.5, 2.5, and 3 mm were designed in Rhinoceros ® 5 software. These designs were written as mask on Pyralux (copper coated polyimide) sheets using an indelible marker and an x–y plotter (Curio printer). After air-drying for 1 h, the Pyralux sheets were submerged into solution containing 2:1 ratio of 3 wt% hydrogen peroxide and 31.45 wt% hydrochloric acid. Once the unmasked copper is etched away (approximately 10 min, observed by eye), the sample is

CRediT authorship contribution statement

Yee Jher Chan: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization. Adam R. Carr: Validation, Investigation, Writing - original draft, Visualization. Sadaf Charkhabi: Validation, Visualization. Mason Furnish: Validation, Visualization. Andee M. Beierle: Resources. Nigel F. Reuel: Conceptualization, Methodology, Validation, Formal analysis, Resources, Writing - original

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

Funding for this project was provided by NSF Award #1827578.

Yee Jher Chan – is a PhD student in the Department of Chemical and Biological Engineering at Iowa State University (ISU). His project explores the biological application of radio wave resonant sensors, including the sensing of physical attributes of cells. His project also involves the development of resonant sensor through design and sensing technique. He received his BS in Chemical Engineering from ISU in 2018.

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Yee Jher Chan – is a PhD student in the Department of Chemical and Biological Engineering at Iowa State University (ISU). His project explores the biological application of radio wave resonant sensors, including the sensing of physical attributes of cells. His project also involves the development of resonant sensor through design and sensing technique. He received his BS in Chemical Engineering from ISU in 2018.

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