A method of driving a crane jib
By combining multimodal perception and digital twin models, the intelligent control method solves the problems of adaptability and safety in traditional crane telescopic boom drive control, achieving smooth, efficient and safe drive under complex working conditions, reducing system impact and energy consumption, and improving equipment reliability and operation quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- LUZHOU HUICHENG HYDRAULIC MASCH CO LTD
- Filing Date
- 2026-05-07
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional crane telescopic boom drive control methods cannot adaptively adjust under complex dynamic working conditions, resulting in uneven control, large impact, high energy consumption and safety hazards. Existing AI decision-making lacks real-time safety verification.
A multimodal sensing deep neural network model is used to predict the optimal driving parameters in real time, and the results are verified by virtual simulation using a digital twin model. The parameters are optimized by combining a gradient fine-tuning algorithm to ensure safety and performance. An LSTM model is used to assess the health status of the hydraulic valve and predict its failure.
It achieves high smoothness, low impact, and high energy efficiency of crane telescopic boom under complex working conditions, reducing the risk of failure and improving the quality of operation and equipment life.
Smart Images
Figure CN122403291A_ABST