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Titolo:
Generic monitoring system in the biological wastewater treatment process
Autore:
Choi, SW; Yoo, CK; Lee, KH; Lee, IB;
Indirizzi:
Pohang Univ Sci & Technol, Sch Environm Engn, Pohang 790784, South Korea Pohang Univ Sci & Technol Pohang South Korea 790784 790784, South Korea Pohang Univ Sci & Technol, Dept Chem Engn, Pohang 790784, South Korea Pohang Univ Sci & Technol Pohang South Korea 790784 790784, South Korea
Titolo Testata:
JOURNAL OF CHEMICAL ENGINEERING OF JAPAN
fascicolo: 10, volume: 34, anno: 2001,
pagine: 1218 - 1228
SICI:
0021-9592(200110)34:10<1218:GMSITB>2.0.ZU;2-V
Fonte:
ISI
Lingua:
ENG
Soggetto:
PRINCIPAL COMPONENT ANALYSIS; PARTIAL LEAST-SQUARES; FAULT-DETECTION; DIAGNOSIS; PLS; MODEL; PCA;
Keywords:
biological wastewater treatment process; disturbance detection; disturbance isolation; modified dissimilarity measure; on-line monitoring;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
24
Recensione:
Indirizzi per estratti:
Indirizzo: Lee, IB Pohang Univ Sci & Technol, Sch Environm Engn, Pohang 790784, SouthKorea Pohang Univ Sci & Technol Pohang South Korea 790784 South Korea
Citazione:
S.W. Choi et al., "Generic monitoring system in the biological wastewater treatment process", J CHEM EN J, 34(10), 2001, pp. 1218-1228

Abstract

In this paper a new monitoring algorithm utilizing a change in time-seriesdistribution of process data is presented since the distribution reflects the corresponding operating condition. In order to quantitatively evaluate the difference between two data sets, a modified dissimilarity index is defined. It represents the degree of dissimilarity between data-sets. In training step the confidence interval of each eigenvalue is obtained from the data taken in normal operation. Then, current operating condition is monitored by checking whether dissimilarity index abruptly changes and whether eacheigenvalue is contained within its confidence interval. This approach is used to identify various internal and external disturbances in the data fromthe simulated activated sludge process. Simulation results have clearly shown that the detection performance of the proposed method can detect the various faults and disturbances, and can automatically discriminate between serious and minor anomalies of faults. That is, it can detect not only the disturbances, but isolate the sources of them. These results confirm that the proposed method is a proper monitoring technique for the wastewater treatment process which has nonstationary property and various disturbances.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 15/07/20 alle ore 19:58:34