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Correction of nonlinearities in series structure-based resistance thermometry readouts
Jiong Ding1, Hanyi Yao1, Suijun Yang1
1Institute of Industry and Trade Measurement Technology, China Jiliang University, Xueyuan Street, No. 258, 310018 Hangzhou, China.
The Review of Scientific Instruments
|November 3, 2020
Summary
A new nonlinear error correction method improves resistance thermometry readouts for multi-point temperature measurements. This technique significantly reduces temperature reading errors, enhancing measurement accuracy in series structures.
Area of Science:
- Electrical Engineering
- Metrology
- Sensor Technology
Background:
- Series structure-based resistance thermometry enables multi-point temperature measurements but suffers from nonlinear errors.
- Existing nonlinear error correction methods are ineffective due to diverse error sources and channel variations.
Purpose of the Study:
- To propose and validate a novel nonlinear error correction method for series structure-based resistance thermometry readouts.
- To enhance the accuracy of multi-point temperature measurements by addressing inherent nonlinearities.
Main Methods:
- Analysis of circuit architecture to identify and quantify error source impacts.
- Utilizing resistance bridge calibrators to eliminate common-mode rejection ratio and exciting current mismatch contributions.
- Fitting residual errors to polynomial functions for correction.
Main Results:
- The proposed method reduced the maximum nonlinear readout error to 1.87 × 10-5.
- This represents a significant improvement over the classical method, which yielded an error of 4.01 × 10-5.
Conclusions:
- The proposed error source analysis-based nonlinear correction method is effective for series structure resistance thermometry.
- This advancement offers improved accuracy for multi-point temperature sensing applications.
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