一种基于深度学习立体匹配的PCBA元件高度测量方法
By using a deep learning-based stereo matching method, combined with the ERH-Stereo stereo matching network and a binocular camera moving platform, the problems of low efficiency and insufficient accuracy in PCBA component height measurement are solved, achieving high-precision and fast component height measurement and meeting the design requirements of test fixtures.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTH CHINA UNIV OF TECH
- Filing Date
- 2024-08-08
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies for measuring PCBA component height are inefficient and prone to errors, making it difficult to meet the design requirements of modular and flexible test fixtures.
A deep learning-based stereo matching method is adopted. By using the ECA attention mechanism, RAFT-Stereo and UHRNet high-resolution network ERH-Stereo stereo matching network structure, combined with the baseline distance and focal length parameters of the stereo camera, a two-degree-of-freedom stereo camera moving platform is designed to achieve high-precision component height measurement.
It improves the accuracy and efficiency of PCBA component height measurement, meeting the requirements of rapid, reliable, and reduced installation force deformation in test fixture design.
Smart Images
Figure CN119027479B_ABST