Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China.
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China; Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China.
ISA Trans. 2022 Oct;129(Pt B):631-643. doi: 10.1016/j.isatra.2022.02.018. Epub 2022 Feb 15.
A rotary kiln is core equipment in cement calcination. Significant time delay, time-varying, and nonlinear characteristics cause challenges in the advance process control and operational optimization of the rotary kiln. However, the traditional mechanism model with many assumptions cannot accurately represent the dynamic kiln process because kinetic parameters are difficult to obtain. This paper proposes a novel hybrid strategy to develop a dynamic model of a rotary kiln by combining a process mechanism and a recurrent neural network to address this issue. A time delay mechanism is used to estimate the kiln's residence time to compensate for the time delay. A long short-term memory model that combines an attention mechanism and an ordinary differential equation solver is proposed to capture the time-varying and nonlinear behaviors of the kiln process. Case studies from two real-world cement plants with different processing loads are used to verify the effectiveness of the proposed hybrid modeling strategy. The results show that the proposed method has better accuracy and robustness than the traditional methods. The sensitivity analysis of the proposed model also makes it practical for t control system design and real-time optimization.
回转窑是水泥煅烧的核心设备。显著的时滞、时变和非线性特点给回转窑的先进过程控制和运行优化带来了挑战。然而，由于动力学参数难以获取，许多假设的传统机理模型无法准确地表示动态窑过程。本文提出了一种新颖的混合策略，通过结合过程机理和递归神经网络来开发回转窑的动态模型，以解决这个问题。使用时滞机制来估计窑的停留时间，以补偿时滞。提出了一种结合注意力机制和常微分方程求解器的长短期记忆模型，以捕捉窑过程的时变和非线性行为。使用来自两个具有不同加工负荷的实际水泥厂的案例研究来验证所提出的混合建模策略的有效性。结果表明，与传统方法相比，所提出的方法具有更好的准确性和鲁棒性。对所提出模型的敏感性分析也使其在控制系统设计和实时优化方面具有实际意义。
