Intelligent Fault Diagnosis in Lead-zinc Smelting Process

According to the fault characteristic of the imperial smelting process （ISP）, a novel intelligent integrated fault diagnostic system is developed. In the system fuzzy neural networks are utilized to extract fault symptom and expert system is employed for effective fault diagnosis of the process. Fur...

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Bibliographic Details
Published inInternational journal of automation and computing Vol. 4; no. 2; pp. 135 - 140
Main Authors Gui, Wei-Hua, Yang, Chun-Hua, Teng, Jing
Format Journal Article
LanguageEnglish
Published Heidelberg Springer Nature B.V 01.04.2007
School of Information Science & Engineering, Central South University, Changsha 410083, PRC
Subjects
Diagnostic systems
Expert systems
Fault diagnosis
Faults
Fuzzy
Fuzzy logic
Fuzzy set theory
Smelting
Studies
Zinc
专家系统
智能化故障诊断
神经网络
铅-锌熔炼过程
Fault diagnosis
expert system
inference
neural network
fuzzy logic
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Summary:According to the fault characteristic of the imperial smelting process （ISP）, a novel intelligent integrated fault diagnostic system is developed. In the system fuzzy neural networks are utilized to extract fault symptom and expert system is employed for effective fault diagnosis of the process. Furthermore, fuzzy abductive inference is introduced to diagnose multiple faults. Feasibility of the proposed system is demonstrated through a pilot plant case study.
Bibliography:TP277
11-5350/TP
Fault diagnosis, fuzzy logic, expert system, neural network, inference.
TF125.21
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1476-8186
2153-182X
1751-8520
2153-1838
DOI:10.1007/s11633-007-0135-z