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Related Concept Videos

Random Error01:04

Random Error

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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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A Multi-Band Temperature Measurement Data Retrieval Method Based on the Chaotic Artificial Hummingbird Algorithm

Wenxiang You1, Xiaojian Hao1, Rui Jia1

  • 1School of Instrument and Electronics, North University of China, Taiyuan 030000, China.

Sensors (Basel, Switzerland)
|April 14, 2026
PubMed
Summary

This study introduces a novel temperature retrieval method using the Chaotic Artificial Hummingbird Algorithm (CAHA) for multispectral radiation thermometry. CAHA accurately determines temperature by identifying emissivity without prior models, proving effective even with noise.

Keywords:
chaotic artificial hummingbird algorithmmultispectral radiation thermometrytemperature retrieval

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Area of Science:

  • Thermometry
  • Optical Engineering
  • Artificial Intelligence

Background:

  • Uncertain emissivity poses significant challenges in multispectral radiation thermometry.
  • Accurate temperature retrieval is crucial for various industrial and scientific applications.

Purpose of the Study:

  • To develop a robust temperature retrieval method for multispectral radiation thermometry that overcomes emissivity uncertainties.
  • To enhance the accuracy and reliability of temperature measurements in dynamic environments.

Main Methods:

  • A novel temperature retrieval approach utilizing the Chaotic Artificial Hummingbird Algorithm (CAHA).
  • CAHA automatically identifies emissivity distribution without requiring an assumed emissivity model.
  • Iterative optimization process to select the most accurate temperature output.

Main Results:

  • High accuracy in temperature retrieval was demonstrated in simulations and offline tests on rocket nozzles, even with up to 5% noise.
  • Experimental validation on blackbody sources yielded a relative temperature error below 0.93%.
  • Outer flame temperature measurements of candle flames showed a low relative error of 0.66% compared to thermocouple data.

Conclusions:

  • The CAHA-based method offers a precise and computationally efficient solution for radiation thermometry.
  • The algorithm's ability to handle uncertain emissivity makes it suitable for practical, real-world applications.
  • This approach significantly advances the field of non-contact temperature measurement.