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Drift is a significant issue that undermines the reliability of gas sensors. This paper introduces a probabilistic model to distinguish between environmental variation and instrumental drift, using low-cost non-dispersive infrared (NDIR) CO2 sensors as a case study. Data from a long-term field experiment is analyzed to evaluate both sensor performance and environmental changes over time. Our approach employs importance sampling to isolate instrumental drift from environmental variation, providing a more accurate assessment of sensor performance. The results show that failing to account for environmental variation can significantly affect the evaluation of sensor drift, leading to improper calibration processes.
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Yang et al. (Tue,) studied this question.
www.synapsesocial.com/papers/68e636c5b6db6435875c8b59 — DOI: https://doi.org/10.48550/arxiv.2406.17488
Cheng Yang
Gustav Bohlin
Tobias J. Oechtering
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