Research on Online Detection Method for Irregular Crystal Rod Cross-Section Dimensions in the Czochralski Process

In the Czochralski method for crystal growth, the uniformity of diameter growth is critical for ensuring crystal quality. Currently, this process predominantly depends on manual visual inspection, which is inherently subjective and lacks precision. To address these challenges, this paper proposes an online detection method for assessing the irregular cross-sectional dimensions of crystal rods through image monitoring. Initially, real-time monitoring data of crystal growth is processed to generate a sequence of images, followed by preprocessing steps that include denoising and contrast enhancement. Subsequently, the edges of the crystal rod are identified using weighted pixel values and gradients, with the similarity of radius sequences recorded in various directions serving as the fitness value for potential center points. The whale optimization algorithm is then utilized to identify the center point of the cross-section. Finally, the cross-sectional shape is delineated, and by incorporating camera calibration, pixel dimensions are converted to physical dimensions, thereby facilitating the online detection of the crystal rod's cross-sectional size. Experimental results obtained from neodymium-doped yttrium vanadate (Nd:YVO4) crystals indicate that this method achieves an average absolute error of 0.38 mm and 0.24 mm in measuring the long and short axes of the cross-section, respectively, with an average detection time of 0.81 seconds. This approach has the potential to assist or even replace the labor-intensive manual monitoring of crystal growth.