Work

Flexible Monte Carlo method for sensor calibration

Year: 2024

Type: article

Abstract: Sensor/system calibration is a crucial step in every measurement system. To perform the calibration the system/sensor input is changed, and its output is measured. The device calibration is obtained from the measured input and output values. When the input/output relation is a straight line, a linear regression is the most common method to obtain the relation. However, this method does not consider uncertainties in the system/sensor input. In this paper, an alternative process based on the Monte Carlo method is proposed. This method can be used considering the uncertainties of the measured inputs and outputs and is flexible to deal with situations for any type of probability density functions of the measured values.

Source: Measurement Sensors

DOI: 10.1016/j.measen.2024.101439

Authors: Pedro M. Ramos, Nuno M. Rodrigues, Fernando M. Janeiro

Institutions: University of Lisbon, Instituto de Telecomunicações, Instituto Superior Técnico, University of Évora

Language: English

Topic: Scientific Measurement and Uncertainty Evaluation

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,800

Funders: Ministério da Ciência, Tecnologia e Ensino Superior, Fundação para a Ciência e a Tecnologia