基于机器学习的起重机械吊具姿态安全控制方法及系统
By combining multi-source data fusion through machine learning and dynamic models with an attention-based safety assessment network, real-time spreader attitude control commands are generated. This solves the problems of insufficient real-time performance and adaptability to working conditions in existing spreader attitude control systems, and achieves refined safety control of spreader attitude.
CN122403293APending Publication Date: 2026-07-17
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Filing Date
- 2026-05-22
- Publication Date
- 2026-07-17
Smart Images
Figure CN122403293A_ABST
Abstract
本发明公开了基于机器学习的起重机械吊具姿态安全控制方法及系统，涉及起重机械控制技术领域，包括采集起重机械吊具全球导航卫星系统定位数据、惯性测量单元数据构成多源感知数据集。采用改进多源数据融合估计算法处理卫星原始定位数据，解算吊具全局位置与速度信息，对惯性测量单元数据开展导航解算与误差补偿，得到姿态角、角速度及惯性推算位移信息。依托吊具动力学模型实时估计负载摆角与摆角速度，将多类状态信息输入注意力机制安全评估与决策网络生成姿态控制指令，转换为底层驱动信号完成吊具姿态实时闭环控制。
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