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<p>A novel Tri Split Complementary Oval Resonator (TSCOR) embedded in a Koch snowflake with a defective ground plane is proposed for the non-invasive detection of moisture content present ranging from 10.2% to 19.6% in the grains. The primary challenge in measuring the moisture content in grains using existing invasive methods is the limited sample size, which leads to inaccurate measurements. The novel resonator configuration demonstrates effectiveness through non-invasive measurement in detecting moisture for a variety of grains, including rice, wheat, and corn, regardless of whether they are stored in plastic or jute bags. Fractal geometry is analyzed using an Iterated Function System (IFS), resulting in a self-similar structure that increases field confinement and sensitivity across multiple scales. Theoretical modelling validates the sensor’s multiple resonance behaviors with real-time measurements. A significant variation in moisture content results in a substantial frequency shift of 270–400&#xa0;MHz at a resonant frequency of 3.2–3.4&#xa0;GHz with a low error rate of 0.05%. The sensor’s non-invasiveness, high sensitivity, and cost-effectiveness make it an ideal choice for industrial Internet of Things applications.</p>

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Characterization of non-intrusive moisture detection in grains using multiple split resonators

  • 期刊论文

  • 发表日期：

    2026年3月7日

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  • Abirami Karthikeyan,
  • Rajesh Anbazhagan,
  • Suguna Gunasekaran,
  • Manikandan Chinnusami

摘要

A novel Tri Split Complementary Oval Resonator (TSCOR) embedded in a Koch snowflake with a defective ground plane is proposed for the non-invasive detection of moisture content present ranging from 10.2% to 19.6% in the grains. The primary challenge in measuring the moisture content in grains using existing invasive methods is the limited sample size, which leads to inaccurate measurements. The novel resonator configuration demonstrates effectiveness through non-invasive measurement in detecting moisture for a variety of grains, including rice, wheat, and corn, regardless of whether they are stored in plastic or jute bags. Fractal geometry is analyzed using an Iterated Function System (IFS), resulting in a self-similar structure that increases field confinement and sensitivity across multiple scales. Theoretical modelling validates the sensor’s multiple resonance behaviors with real-time measurements. A significant variation in moisture content results in a substantial frequency shift of 270–400 MHz at a resonant frequency of 3.2–3.4 GHz with a low error rate of 0.05%. The sensor’s non-invasiveness, high sensitivity, and cost-effectiveness make it an ideal choice for industrial Internet of Things applications.