Year: 2025
Type: conference-paper
Abstract: This paper addresses the limitations of traditional multi-spectral temperature measurement methods, such as low computational efficiency and sensitivity to noise, by introducing an efficient temperature inversion method based on a collaborative design of an adaptive wavelength selection mechanism and a differential evolution optimization algorithm. By dynamically eliminating wavelength channels with low signal-to-noise ratios, the method reduces ineffective computation by over 30%. Furthermore, the global search and parallel processing capabilities of the differential evolution algorithm significantly enhance the accuracy and efficiency of temperature inversion. Experimental results demonstrate that, when applied to black powder data, the temperature standard deviation is optimized from ±85 K using the traditional dual annealing algorithm to ±23 K. The processing time for a single frame (149×280 pixels) is reduced from 22.5 minutes to 4.1 minutes. This research provides a high-precision, high-efficiency temperature measurement solution for scenarios with strict real-time requirements, such as industrial combustion diagnostics and high-temperature material detection.
Source: MATEC Web of Conferences
Authors: Yuqian Dong, Xiaojian Hao, Shenxiang Feng, Tong Wei, Hongkai Wei
Institution: North University of China
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
Awards: G168388580, G7501720330, G8392587871
OpenAlex ID: W4414708334