The design of sensor networks for chemical plants is an important and complex task. In the context of data reconciliation, there are several desiderata for a sensor network, such as observability, redundancy (including hardware redundancy), and estimation precision, as well as good performance in the process optimization conducted after data reconciliation. While each of these aspects has been considered in the literature, there is no published method that addresses all of them simultaneously. In this work, we develop such a unified approach while also considering the performance of the selected sensor network across multiple operating scenarios. We formulate the problem as a mixed-integer nonlinear program and highlight the benefits of the proposed integrated model in three computational case studies. In particular, the results show that hardware redundancy can lead to improved performance at the same sensor cost and that a multiscenario approach can be crucial in achieving overall optimality.

中文翻译：

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用于数据协调的多场景传感器网络设计的统一方法

化工厂传感器网络的设计是一项重要而复杂的任务。在数据对账的背景下，传感器网络有几个要求，如可观察性、冗余（包括硬件冗余）和估计精度，以及在数据对账后进行的过程优化中的良好性能。虽然文献中已经考虑了这些方面中的每一个，但没有公开的方法可以同时解决所有这些问题。在这项工作中，我们开发了这样一种统一的方法，同时还考虑了所选传感器网络在多个操作场景中的性能。我们将问题表述为混合整数非线性程序，并在三个计算案例研究中强调了所提出的集成模型的好处。特别是，