An automatic identification method of high-temperature particle stray radiation sources

Infrared stray radiation adversely impacts the imaging performance of optical systems and affects detection accuracy. The suppression of stray radiation is regarded as essential in the design process of optical systems. Currently, most stray radiation analysis methods employ the Monte Carlo ray tracing approach, which is used to simulate the influence of stray radiation sources on the imaging process in a forward manner. However, for cases where the stray radiation source is unknown, such as high-temperature particles, forward simulation makes it challenging to accurately determine the location of the stray radiation source. To address this issue, a rapid tracing method is proposed in this study, which identifies stray radiation sources based on interference information obtained from the detection surface. This method combines the Monte Carlo approach with a genetic algorithm, enabling rapid determination of the location and size of stray radiation sources. The Monte Carlo ray tracing method is applied to characterize the imaging process within the optical system. A genetic algorithm is employed to localize the particles, with the objective function defined based on specific parameters of the image, including the inner and outer diameters and the offset position. Parameter identification is then performed to determine the size and position of the particles. The identified parameters are validated by comparing the generated images with real images. Then the results show that the maximum radius error is approximately 3%, while the largest offset error is about 3.5%. Based on this automatic identification method, the stray radiation source caused by particles can be quickly and accurately identified, providing valuable support for subsequent stray radiation suppression and optical system design.