一种光伏螺旋桩桩位偏差检测方法、系统及终端
By using drones equipped with lidar and cameras combined with deep learning-based multi-source data fusion technology, the deviation of photovoltaic spiral pile positions can be automatically detected. This solves the problems of low detection efficiency and high cost in existing technologies, and achieves efficient and accurate deviation detection and data support.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHEJIANG HUADONG ENG CONSTR MANAGEMENT CO LTD
- Filing Date
- 2025-12-22
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, the detection of photovoltaic spiral pile positions relies on manual measurement or fixed equipment, resulting in low efficiency and high cost, making it difficult to meet the rapid construction needs of large-area photovoltaic projects.
By using drones equipped with LiDAR and cameras, combined with deep learning and multi-source data fusion technology, the center point of the spiral pile is automatically identified and the deviation is calculated through the collaborative processing of visual images and LiDAR data. A data quality monitoring and re-sampling mechanism is introduced to ensure data accuracy.
It achieves efficient and accurate detection of photovoltaic helical pile position deviation, reduces false detections and missed detections, lowers rework costs and time, adapts to complex terrain, and provides multi-dimensional engineering quality data support.
Smart Images
Figure CN121366162B_ABST