Project Overview
Led a systematic evaluation and characterization of industrial-grade thermal sensors (RTD and BME280) to maximize measurement precision. This project focused on identifying non-linearity in environmental sensors and engineering high-fidelity signal conditioning circuits to improve data integrity.
Technical Responsibilities & Methodologies
Signal Conditioning Design: Engineered and implemented Wheatstone bridge circuits and voltage dividers to translate resistive changes into high-resolution voltage signals for ADC acquisition.
Precision Calibration: Developed custom calibration protocols to neutralize cable resistance and environmental noise, achieving high-linearity RTD readings with an $R^2$ value $\approx 1$.
Statistical Performance Analysis: Utilized Python to calculate critical reliability metrics, including Signal-to-Noise Ratio (SNR), gain, and error margins across varying temperature ranges.
Root Cause Analysis: Conducted a detailed performance audit of the BME280 sensor, identifying and documenting specific accuracy degradation thresholds to inform system operational limits.
Key Achievements
Enhanced Measurement Precision: Significantly reduced temperature reading errors through innovative calibration and noise-reduction techniques.
Optimized Signal Processing: Maximized sensor output resolution by optimizing amplification stages to match ADC input limits without saturation.
Data Integrity: Validated sensor linearity and repeatability through extensive experimental testing, providing a clear foundation for reliable thermal monitoring.