Digital twin driven soft sensing for key variables in zinc rotary kiln

Zinc rotary kiln is an important equipment in the nonferrous metallurgical industry. Due to unclear internal working conditions, its operation based on experience is random. Digital twin (DT) with virtual–real integration and synchronization ability is a necessary method to realize real-time and accurate monitoring for key variables, while its nowadays practical application face challenge about accuracy and consistency. Therefore, this article proposes a DT driven soft sensing method for key variables in rotary kiln. First, a thermodynamics and chemical reactions coupling model is built after analyzing the mechanism in kiln. Second, key parameters of DT were identified through analysis of limited and multisource data to ensure its consistency. Finally, in DT deployment stage, to realize the DT soft-sensing real-timely, a model reduction and DT distributed computing method was proposed to improve simulation timeliness. Practical application proved that soft sensing method based on DT can accurately and effectively obtain real-time monitoring results of key variables in the rotary kiln.