Model-Based Correction of Temperature-Dependent Measurement Errors in Frequency Domain Electromagnetic Induction...

Area of Science:

• Geophysics
• Environmental Science
• Instrumentation

Background:

• Electromagnetic induction (EMI) data are prone to drift caused by ambient temperature fluctuations, impacting measurement reproducibility.
• Current drift correction methods often rely on static calibration, which may not fully capture dynamic thermal effects.
• Accurate temperature drift correction is crucial for reliable EMI data acquisition in various environmental applications.

Purpose of the Study:

• To develop and validate a novel method for correcting temperature-induced drift in EMI data.
• To compare the effectiveness of a dynamic drift correction model against a static calibration approach.
• To enhance the accuracy and reproducibility of EMI measurements under varying temperature conditions.

Main Methods:

• A customized EMI device with multiple internal temperature sensors was utilized.
• Outdoor calibration measurements were conducted over 16 days across a wide temperature range.
• A novel correction method employing a low-pass filter to model dynamic thermal drift characteristics was developed and applied.
• The performance of the dynamic correction method was evaluated against a static correction method and uncorrected data.

Main Results:

• The uncorrected temperature-dependent apparent electrical conductivity (ECa) drift was measured at approximately 2.27 mSm⁻¹K⁻¹.
• The novel dynamic correction method reduced the root mean square error (RMSE) from 15.7 mSm⁻¹ to 0.48 mSm⁻¹.
• Static drift characterization improved the RMSE to 1.97 mSm⁻¹, significantly less effective than the dynamic method.
• The dynamic modeling approach improved accuracy by a factor of four compared to static characterization.

Conclusions:

• Modeling the dynamic thermal characteristics of EMI systems is essential for effective drift correction.
• The proposed low-pass filter-based method offers a significant improvement in EMI data accuracy over static correction techniques.
• This advancement is critical for ensuring the reliability and reproducibility of geophysical and environmental measurements using EMI technology.