Strands tension balance control method of cable twisting based on characteristics of priori time-delay
The balance control of strands tension is an important guarantee for the quality of cable twisting.To solve the problem of closed-loop tension control failure between tension detection of twisting end and the execution end caused by the time-delay effect during tension sensing process,the tension control strategy to cope with the time de-lay was proposed based on the real-time tension detection data combined with prior knowledge.The time-delay effect of tension data was analyzed theoretically combined with the actual working conditions of cable twisting.The tension signals were decomposed by variational mode decomposition method to obtain modal components with low complexi-ty and high stability that contained multiple original data characteristics.The deep learning method was used to in-tegrate the inherent modal components to realize the prediction and abnormal identification of the twisting tension of strands.Combined with the prior knowledge,a tension balance control system based on prior knowledge of cable twisting was designed.According to the predicted tension of the twisting end,the hysteresis tension of the pay-off wheel at the execution end was adjusted to avoid abnormal tension during the twisting process.The effectiveness of the method was verified by simulation experiments.It provided an effective solution to realize the balance control of tension of cable twisting strand.
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