A Review on Data-Driven Learning Approaches for Fault Detection and Diagnosis in Chemical Processes,ChemBioEng Reviews

当前位置： X-MOL 学术 › ChemBioEng Rev. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

A Review on Data-Driven Learning Approaches for Fault Detection and Diagnosis in Chemical Processes
ChemBioEng Reviews ( IF 6.2 ) Pub Date : 2021-02-26 , DOI: 10.1002/cben.202000027
Syed Ali Ammar Taqvi _{1,

2} , Haslinda Zabiri ₃ , Lemma Dendena Tufa ₄ , Fahim Uddin ₁ , Syeda Anmol Fatima ₃ , Abdulhalim Shah Maulud ₃

Affiliation

Fault detection and diagnosis for process plants has been an active area of research for many years. This review presents a concise overview on supervised and unsupervised data-driven approaches for fault detection and diagnosis in chemical processes. Methods based on supervised and unsupervised data-driven techniques are reviewed, and the challenges in the field of fault detection and diagnosis have also been highlighted. It is observed that most of the data-driven approaches are application specific, in that no single method can be used to obtain a generalized solution for nearly all purposes. The methods reviewed differ significantly from one to the other, and hence it is difficult to generalize any key similarity. The majority of the works proposed in the literature focused mainly on single fault detection, and do not cover the root-cause diagnosis of the detected faults. In cases where both detection and diagnosis are performed, the focus is mainly for a single fault. In addition, majority of the articles do not extend to the diagnosis of the root cause for multiple and simultaneous faults.

中文翻译：

用于化学过程故障检测和诊断的数据驱动学习方法综述

多年来，过程工厂的故障检测和诊断一直是一个活跃的研究领域。本综述简要概述了用于化学过程故障检测和诊断的有监督和无监督数据驱动方法。回顾了基于有监督和无监督数据驱动技术的方法，并强调了故障检测和诊断领域的挑战。据观察，大多数数据驱动方法都是特定于应用程序的，因为没有一种方法可以用于获得几乎所有用途的通用解决方案。所审查的方法各不相同，因此很难概括任何关键的相似性。文献中提出的大多数工作主要集中在单一故障检测上，并且不包括检测到的故障的根本原因诊断。在同时进行检测和诊断的情况下，重点主要是针对单个故障。此外，大多数文章都没有扩展到对多个同时发生的故障的根本原因的诊断。

更新日期：2021-02-26

点击分享查看原文

点击收藏

阅读更多本刊最新论文