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Title: On-line early fault detection and diagnosis of municipal solid waste incinerators

Abstract

A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows that automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI.

Authors:
 [1];  [2];  [3]
  1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029 (China), E-mail: jinsongzhao@mail.tsinghua.edu.cn
  2. College of Information Science and Technology, Beijing Institute of Technology, Beijing 10086 (China)
  3. College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China)
Publication Date:
OSTI Identifier:
21153957
Resource Type:
Journal Article
Journal Name:
Waste Management
Additional Journal Information:
Journal Volume: 28; Journal Issue: 11; Other Information: DOI: 10.1016/j.wasman.2007.11.014; PII: S0956-053X(07)00426-6; Copyright (c) 2007 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0956-053X
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; COMPUTER CODES; DIAGNOSIS; FAULT TREE ANALYSIS; FORECASTING; INCINERATORS; MULTIVARIATE ANALYSIS; POLAR-CAP ABSORPTION; RECOMMENDATIONS; SOLID WASTES

Citation Formats

Zhao Jinsong, Huang Jianchao, and Sun Wei. On-line early fault detection and diagnosis of municipal solid waste incinerators. United States: N. p., 2008. Web. doi:10.1016/j.wasman.2007.11.014.
Zhao Jinsong, Huang Jianchao, & Sun Wei. On-line early fault detection and diagnosis of municipal solid waste incinerators. United States. doi:10.1016/j.wasman.2007.11.014.
Zhao Jinsong, Huang Jianchao, and Sun Wei. Sat . "On-line early fault detection and diagnosis of municipal solid waste incinerators". United States. doi:10.1016/j.wasman.2007.11.014.
@article{osti_21153957,
title = {On-line early fault detection and diagnosis of municipal solid waste incinerators},
author = {Zhao Jinsong and Huang Jianchao and Sun Wei},
abstractNote = {A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows that automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI.},
doi = {10.1016/j.wasman.2007.11.014},
journal = {Waste Management},
issn = {0956-053X},
number = 11,
volume = 28,
place = {United States},
year = {2008},
month = {11}
}