A Review on Basic Data-Driven Approaches for Industrial Process Monitoring

作者：Shen Yin, Steven X. Ding, Xiaochen Xie, Hao Luo · 发表于：IEEE Transactions on Industrial Electronics · 年份：2014 · DOI：10.1109/tie.2014.2301773 · 被引用次数：1709 · 研究领域：Fault Detection and Control Systems、Mineral Processing and Grinding、Advanced Control Systems Optimization

Recently, to ensure the reliability and safety of modern large-scale industrial processes, data-driven methods have been receiving considerably increasing attention, particularly for the purpose of process monitoring. However, great challenges are also met under different real operating conditions by using the basic data-driven methods. In this paper, widely applied data-driven methodologies suggested in the literature for process monitoring and fault diagnosis are surveyed from the application point of view. The major task of this paper is to sketch a basic data-driven design framework with necessary modifications under various industrial operating conditions, aiming to offer a reference for industrial process monitoring on large-scale industrial processes.