Multispectral radiation thermometry approach based on feasible region constraints-divide and conquer optimization
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a novel collaborative optimization method for multispectral radiation thermometry, significantly improving non-contact temperature measurement accuracy by addressing unknown emissivity. The new approach achieves a 0.2% error rate, enabling real-time applications.
Area Of Science
- Thermophysics
- Metrology
- Optimization Algorithms
Background
- Multispectral radiation thermometry is crucial for non-contact temperature measurement, especially in extreme conditions.
- Accurate temperature retrieval is hindered by the challenge of unknown object emissivity.
- Existing methods often struggle with precision in complex environments.
Purpose Of The Study
- To develop a robust method for accurate temperature measurement in multispectral radiation thermometry.
- To overcome the limitations posed by unknown emissivity in non-contact temperature sensing.
- To enhance the precision and efficiency of temperature inversion algorithms.
Main Methods
- A collaborative optimization approach combining feasible region constraints (PCR-PSO) and divide and conquer optimization (multi-BFGS).
- Utilizing feasible domain constraints to refine temperature estimations.
- Employing a multi-BFGS algorithm within a divide and conquer framework for iterative refinement.
Main Results
- Simulation results demonstrated a reduction in temperature inversion error from 0.59% to 0.19% compared to the traditional BFGS algorithm.
- Experimental validation with stainless steel samples showed an average error of less than 0.2%.
- Achieved an average processing time of 0.2 seconds, indicating suitability for real-time applications.
Conclusions
- The proposed collaborative optimization approach significantly enhances the accuracy of multispectral radiation thermometry.
- The method effectively addresses the challenge of unknown emissivity, leading to more reliable temperature measurements.
- The approach shows strong potential for real-time, high-precision temperature monitoring in various engineering applications.
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