Nanosecond laser cleaning method for high-capacity fast storage and data multiplexing in ARM architecture

As the application of laser cleaning technology continues to expand, various fields have put forward higher requirements for the performance and quality of the operation, and at present, laser cleaning has problems such as low efficiency in handling repetitive tasks, and the system deployment and maintenance costs are high. This paper proposes a nanosecond laser cleaning method based on ARM architecture with high-capacity fast storage and data reuse, integrating high-capacity fast storage technique and data reuse strategy to optimize the laser cleaning process. In this paper, SDRAM is used to store and record the laser scanning path, Cache is integrated to weaken the data calling delay and improve the system response speed, and the scanning cycle is finely adjusted by combining positional modulation laser frequency technology to avoid the edge erosion caused by the motor deceleration and to ensure the homogeneity and accuracy of laser cleaning. The results indicate that, under the same output point conditions, the dynamic phase difference spiral algorithm in this paper outperforms the linear filling algorithm in terms of speed and data filling efficiency, reducing the burden of repetitive task calculations. While maintaining surface erosion uniformity during cleaning, excessive erosion is prevented, leading to a comprehensive enhancement in the overall efficiency and performance of laser cleaning operations. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.