Interference Factors and Compensation Methods when Using Infrared Thermography for Temperature Measurement: A Review

TL;DR

This review paper summarizes interference factors affecting infrared thermography accuracy and categorizes compensation methods, providing insights for improving temperature measurement reliability in various environments.

Contribution

It classifies interference factors and compensation methods for infrared thermography, offering a comprehensive framework for researchers and practitioners to enhance measurement accuracy.

Findings

Interference factors are categorized into environmental, object, and imager-related.

Compensation methods are classified into MMC, DDC, and MDC categories.

Discussion of current challenges and future research directions in temperature compensation.

Abstract

Infrared thermography (IRT) is a widely used temperature measurement technology, but it faces the problem of measurement errors under interference factors. This paper attempts to summarize the common interference factors and temperature compensation methods when applying IRT. According to the source of factors affecting the infrared temperature measurement accuracy, the interference factors are divided into three categories: factors from the external environment, factors from the measured object, and factors from the infrared thermal imager itself. At the same time, the existing compensation methods are classified into three categories: Mechanism Modeling based Compensation method (MMC), Data-Driven Compensation method (DDC), and Mechanism and Data jointly driven Compensation method (MDC). Furthermore, we discuss the problems existing in the temperature compensation methods and future research directions, aiming to provide some references for researchers in academia and industry when using IRT technology for temperature measurement.