Outline of a fault diagnosis system for a large-scale board machine

被引：13

作者：

Jamsa-Jounela, Sirkka-Liisa ^{[1
]}

Tikkala, Vesa-Matti ^{[1
]}

Zakharov, Alexey ^{[1
]}

Garcia, Octavio Pozo ^{[1
]}

Laavi, Helena ^{[1
]}

Myller, Tommi ^{[2
]}

Kulomaa, Tomi ^{[2
]}

Hamalainen, Veikko ^{[3
]}

机构：

[1] Aalto Univ, Dept Biotechnol & Chem Technol, Aalto 00076, Finland

[2] Stora Enso Oyj, Imatra Mills 55800, Imatra, Finland

[3] Efora Oy, Imatra 55800, Finland

来源：

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2013年 / 65卷 / 9-12期

关键词：

Fault monitoring; Fault diagnosis; Large-scale systems; Paper industry; Industrial application; Board machine; QUANTITATIVE MODEL;

D O I：

10.1007/s00170-012-4296-8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Global competition forces the process industries to continuously optimize plant operation. One of the latest trends in efficiency and plant availability improvement is to set up fault diagnosis and maintenance systems for online industrial use. This paper presents a methodology for developing industrial fault detection and diagnosis (FDD) systems. Since model- or data-based diagnosis of all components cannot be achieved online on a large-scale basis, the focus must be narrowed down to the most likely faulty components responsible for abnormal process behavior. One of the key elements here is fault analysis. The paper describes and briefly discusses also other development phases, process decomposition and the selection of FDD methods. The paper ends with an FDD case study of a large-scale industrial board machine including a description of the fault analysis and FDD algorithms for the resulting focus areas. Finally, the testing and validation results are presented and discussed.

引用

页码：1741 / 1755

页数：15

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