"Tennessee-Eastman-Process" Alarm Management Case Study

This is an alarm management case study based on the “Tennessee-Eastman-Process” (TEP). The presented case study aims to provide a suitable benchmark dataset for the development and validation of alarm management methods in complex industrial processes using both quantitative data and qualitative information from different sources. Unlike real industrial processes, simulation of the TEP allows to design and generate abnormal sequences, which can be repeated and varied without risking the loss of equipment or harming the environment. In addition, as the simulation is supervised, all induced faults and process normalizations are explicitly known and therefore act as a ground truth, facilitating the utilization of external evaluation metrics (e.g. when using cluster analysis). Further details are described in a supplementary technical report.本研究为基于田纳西-伊斯曼过程（Tennessee-Eastman-Process，TEP）的报警管理案例研究，旨在为复杂工业过程中的报警管理方法开发与验证提供适配的基准数据集，该数据集整合了多源定量数据与定性信息。与真实工业过程不同，TEP仿真可支持设计并生成异常工况序列，且可对该序列进行重复复现与调整，无需面临设备损坏或环境污染的风险。此外，由于该仿真为监督式仿真，所有引入的故障与过程正常工况均为明确已知，可作为真实标签（ground truth）使用，便于借助外部评估指标（例如聚类分析场景中）开展模型验证工作。更多详细信息可参阅配套补充技术报告。

搜集汇总

背景与挑战

背景概述

该数据集是基于'Tennessee-Eastman-Process'的报警管理案例研究，旨在为复杂工业过程的报警管理方法提供基准数据集，结合定量和定性数据。它通过模拟TEP生成可重复的异常序列，无设备或环境风险，且所有故障和正常化信息明确，可作为真实基准，便于外部评估。