Fiber laying process parameter model construction method and system based on imitation learning

Abstract

The invention discloses a fiber laying process parameter model construction method and system based on imitation learning. The system comprises a manual laying demonstration module and the like, and is characterized in that a demonstrator holds a small fiber laying device to carry out the fiber laying operation on the surface of a die, an action capturing module records the real-time position of alaying point on the die, a video recording module records the operation process in real time, a process parameter sensing module records the fiber laying process parameters in real time, the data istransmitted to an industrial personal computer for data storage and processing, the learning process of manual laying teaching operation is completed by simulating a learning algorithm module, a probability mapping model of the process parameter-surface curvature is output, According to the automatic fiber laying system based on the cooperative mechanical arm, the learned model result is combinedwith an intelligent control algorithm, and automatic laying work of fibers on a curved surface is achieved. According to the invention, the control precision of the laying path and process parametersin the composite material laying process is improved, so that the laying defects are reduced.

Description

technical field [0001] The invention provides a method and system for constructing a fiber laying process parameter model based on imitation learning, and relates to the fields of advanced composite material manufacturing, artificial intelligence and robot technology. Background technique [0002] Fiber-reinforced composite materials refer to composite materials composed of high-strength fibers and matrix materials. Because of their advantages such as high specific strength, fatigue resistance, corrosion resistance, and strong designability, they are widely used in aerospace, marine, automotive, sports, medical and other fields. There are a wide range of application requirements. [0003] Automatic placement of composite materials is one of the widely used high-performance and low-cost forming methods. According to different prepregs and processing methods, it is mainly divided into automatic fiber tape placement and automatic fiber filament placement. In the process of aut...

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Problems solved by technology

[0005] Aiming at the problems that the acquisition of the current fiber placement process parameters depends on a large number of experiments, and the obtained parameters have poor generalization ability and the control accuracy of the process parameters of the robotic fiber automatic placement system is not high, the present invention proposes a fiber placement method based on imitation learning. The construction method and system of the laying process parameter model, through the manual teaching and imitation learning method, constructs the probability mapping model of the fiber laying process parameters; combined with the designed intelligent control algorithm, the robust force / power of the multi-axis robotic arm in the complex laying environment is realized. Bit mixing control and multivariable decoupling control of fiber placement head to improve precise regulation of laying path and process parameters

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