一种基于深度学习引导的自适应搜索的智能谐波锁模方法及系统
By combining deep learning and adaptive optimization algorithms, fully automatic high-harmonic mode-locking control of fiber lasers was achieved, solving the problems of insufficient automation and poor stability in existing technologies, and improving the automation level and response speed of lasers.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTHEAST UNIV
- Filing Date
- 2026-05-11
- Publication Date
- 2026-07-17
AI Technical Summary
Existing passively mode-locked fiber lasers rely on manual experience for polarization control parameters and pump power adjustment, resulting in insufficient automation. It is difficult to quickly establish and maintain high-order harmonic mode-locking states. Traditional methods are inefficient and cannot meet the requirements of rapid mode-locking and long-term stability.
An adaptive search method based on deep learning is adopted. By monitoring spectral, temporal, and radio frequency signals and combining residual neural networks to identify the laser state, the optimal polarization control parameters and pump power are searched through an adaptive optimization algorithm to achieve fully automatic and rapid control of high-order harmonic mode-locking.
This method enables fully automatic and rapid control of fiber lasers from fundamental frequency mode-locking to target high repetition frequency harmonic mode-locking, significantly improving the automation level and stability of the laser and solving the problems of low efficiency and insufficient stability of traditional methods.
Smart Images
Figure CN122159036B_ABST