In the ethylene industry, the high purity of the ethylene product depends on hydrogenation in acetylene hydrogenation reactor. Because the catalyst deactivation leads to the moving of the operating point, the operation scheme must be adjusted continually according to the catalyst activity. It is necessary to estimate the catalyst activity online. Based on the discrete dynamic model of the acetylene hydrogenation reactor, the extended Kalman filter (EKF) is used to build the soft sensor for catalyst activity. Considering that EKF involves the large computation costs, we propose a method that estimates the parameters of the time‐varying deactivation kinetics model for the tradeoff of accuracy and complexity. The method is effective to reduce computation complexity of estimation, and simultaneously, the accuracy satisfies the process requirement.

中文翻译：

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在线估算乙炔加氢反应器的催化剂活性

在乙烯工业中，乙烯产物的高纯度取决于在乙炔加氢反应器中的加氢。由于催化剂失活导致操作点的移动，因此必须根据催化剂活性连续调整操作方案。有必要在线估算催化剂活性。基于乙炔加氢反应器的离散动态模型，扩展卡尔曼滤波器（EKF）用于构建催化剂活性的软传感器。考虑到EKF涉及大量的计算成本，我们提出了一种估计时变失活动力学模型参数的方法，以权衡准确性和复杂性。该方法有效地降低了估计的计算复杂度，同时精度满足了过程要求。