Research on Structured Light Signal Processing Optimization Algorithm for Mechanical and Electronic Equipment

This paper proposes an innovative structured light signal processing optimization algorithm, aiming to improve the application effect in mechanical and electronic equipment. The algorithm performs signal preprocessing based on adaptive filtering technology, effectively suppresses noise and enhances signal quality; at the same time, through optimized feature extraction and signal reconstruction methods, the accuracy and processing efficiency of the signal are significantly improved. Experimental simulation results show that the proposed algorithm improves signal noise suppression by 22% compared with traditional methods, reconstruction accuracy by 18%, and computational efficiency by 15%. Through comparative analysis with existing algorithms, the optimization algorithm proposed in this paper has significant advantages in both accuracy and efficiency, and its robustness in complex environments is significantly enhanced. In addition, this paper also explores the practical application potential of the algorithm in mechanical and electronic equipment, and points out possible future research directions, including combining deep learning technology to intelligently optimize signal processing to further improve the overall performance of the algorithm.