Detection and Identification of Faulty Sensors with Maximized Sensitivity

S. Joe Qin; Weihua Li

doi:10.1109/acc.1999.782901

Detection and Identification of Faulty Sensors with Maximized Sensitivity

S. Joe Qin, Weihua Li

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

11 Citations (Scopus)

Abstract

In this paper we propose a new method for the detection, identification and reconstruction of faulty seniors using a generalized normal process model. The model residual is used to detect sensor faults, and a structured residual approach with maximized sensitivity (SRAMS) is proposed to identify the faulty sensor. An exponentially weighted moving average (EWMA) filter is applied to reducing the effects of noise and dynamic transients. Three different indices are proposed and compared for the identification of faulty sensors. Faulty sensor is reconstructed based on the normal process model and faulty data. The effectiveness of the proposed scheme is tested using the data from an industrial boiler process, where four types of faults are simulated.

Original language	English
Title of host publication	Proceedings of the 1999 American Control Conference
Publisher	IEEE
Pages	613-617
Volume	1
ISBN (Electronic)	0780349938
ISBN (Print)	0780349903 , 0780349911
DOIs	https://doi.org/10.1109/acc.1999.782901
Publication status	Published - Jun 1999
Externally published	Yes
Event	1999 American Control Conference (99ACC) - San Diego, CA., United States Duration: 2 Jun 1999 → 4 Jun 1999

Publication series

Name	Proceedings of the American Control Conference
ISSN (Print)	0743-1619

Conference

Conference	1999 American Control Conference (99ACC)
Place	United States
City	San Diego, CA.
Period	2/06/99 → 4/06/99

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10.1109/acc.1999.782901

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@inproceedings{b4fe6b81b79e414f9e7c78aae02066cb,

title = "Detection and Identification of Faulty Sensors with Maximized Sensitivity",

abstract = "In this paper we propose a new method for the detection, identification and reconstruction of faulty seniors using a generalized normal process model. The model residual is used to detect sensor faults, and a structured residual approach with maximized sensitivity (SRAMS) is proposed to identify the faulty sensor. An exponentially weighted moving average (EWMA) filter is applied to reducing the effects of noise and dynamic transients. Three different indices are proposed and compared for the identification of faulty sensors. Faulty sensor is reconstructed based on the normal process model and faulty data. The effectiveness of the proposed scheme is tested using the data from an industrial boiler process, where four types of faults are simulated.",

author = "Qin, {S. Joe} and Weihua Li",

year = "1999",

month = jun,

doi = "10.1109/acc.1999.782901",

language = "English",

isbn = "0780349903 ",

volume = "1",

series = "Proceedings of the American Control Conference",

publisher = "IEEE",

pages = "613--617",

booktitle = "Proceedings of the 1999 American Control Conference",

address = "United States",

note = "1999 American Control Conference (99ACC) ; Conference date: 02-06-1999 Through 04-06-1999",

}

Detection and Identification of Faulty Sensors with Maximized Sensitivity. / Qin, S. Joe; Li, Weihua.
Proceedings of the 1999 American Control Conference. Vol. 1 IEEE, 1999. p. 613-617 (Proceedings of the American Control Conference).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

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AU - Li, Weihua

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N2 - In this paper we propose a new method for the detection, identification and reconstruction of faulty seniors using a generalized normal process model. The model residual is used to detect sensor faults, and a structured residual approach with maximized sensitivity (SRAMS) is proposed to identify the faulty sensor. An exponentially weighted moving average (EWMA) filter is applied to reducing the effects of noise and dynamic transients. Three different indices are proposed and compared for the identification of faulty sensors. Faulty sensor is reconstructed based on the normal process model and faulty data. The effectiveness of the proposed scheme is tested using the data from an industrial boiler process, where four types of faults are simulated.

AB - In this paper we propose a new method for the detection, identification and reconstruction of faulty seniors using a generalized normal process model. The model residual is used to detect sensor faults, and a structured residual approach with maximized sensitivity (SRAMS) is proposed to identify the faulty sensor. An exponentially weighted moving average (EWMA) filter is applied to reducing the effects of noise and dynamic transients. Three different indices are proposed and compared for the identification of faulty sensors. Faulty sensor is reconstructed based on the normal process model and faulty data. The effectiveness of the proposed scheme is tested using the data from an industrial boiler process, where four types of faults are simulated.

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DO - 10.1109/acc.1999.782901

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0780349903

SN - 0780349911

VL - 1

T3 - Proceedings of the American Control Conference

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BT - Proceedings of the 1999 American Control Conference

PB - IEEE

T2 - 1999 American Control Conference (99ACC)

Y2 - 2 June 1999 through 4 June 1999

ER -

Detection and Identification of Faulty Sensors with Maximized Sensitivity

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