The invention relates to the technical field of
tire manufacturing, and discloses an early warning control method and
system for preventing sidewall wear-resistant rubber from being folded, the method is based on
dynamic time warping and multi-
modal data fusion analysis, multi-
modal data such as sidewall wear-resistant rubber pressure distribution,
temperature gradient and vibration signals are collected, and after denoising and
feature extraction, the sidewall wear-resistant rubber is subjected to early warning control. And calculating the similarity with a standard deformation mode, and constructing a graph neural
network model to evaluate the deformation
risk probability. Self-adaptive early warning rules are generated through
reinforcement learning, and whether early warning is conducted or not is monitored and judged in real time. And if the early warning is triggered, adjusting parameters of the sidewall forming
machine, recording data, updating the standard deformation mode
library, and iteratively optimizing the graph neural
network model. The method can accurately monitor the risk, timely control and adjust, continuously optimize the model, effectively prevent the sidewall wear-resistant rubber from being folded, improve the tire
production quality and efficiency, and reduce the production cost.