A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection

Paolo Mercorelli

doi:10.2495/Intelsys130021

A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection

Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

Standard

A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection. / Mercorelli, Paolo.
Advances in Intelligent Systems . ed. / Ford Lumban Gaol; Zenon Chaczko; Kiyota Hashimoto; Tokoro Matsuo; William Grosky. Southampton (UK): WIT Press, 2014. p. 9-16 (WIT Transactions on Information and Communication Technologies; Vol. 53).

Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

Harvard

Mercorelli, P 2014, A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection. in FL Gaol, Z Chaczko, K Hashimoto, T Matsuo & W Grosky (eds), Advances in Intelligent Systems . WIT Transactions on Information and Communication Technologies, vol. 53, WIT Press, Southampton (UK), pp. 9-16. https://doi.org/10.2495/Intelsys130021

APA

Mercorelli, P. (2014). A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection. In F. L. Gaol, Z. Chaczko, K. Hashimoto, T. Matsuo, & W. Grosky (Eds.), Advances in Intelligent Systems (pp. 9-16). (WIT Transactions on Information and Communication Technologies; Vol. 53). WIT Press. https://doi.org/10.2495/Intelsys130021

Vancouver

Mercorelli P. A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection. In Gaol FL, Chaczko Z, Hashimoto K, Matsuo T, Grosky W, editors, Advances in Intelligent Systems . Southampton (UK): WIT Press. 2014. p. 9-16. (WIT Transactions on Information and Communication Technologies). doi: 10.2495/Intelsys130021

Bibtex

@inbook{2c6b64816174430989fd0c74c0fa90e0,

title = "A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection",

abstract = "This paper deals with Gross Error Detection using a signal-based approach and proposes an algorithm to be applied in industrial processes. The developed algorithm is used in some industrial software platforms to detect sensor outliers. A validation of this algorithm through computer simulations is shown. At the end of the paper, results using real sensor measurements from industrial processes are presented.",

keywords = "Engineering, Fault detection, Industrial applications, Wavelets",

author = "Paolo Mercorelli",

note = "Extended paper from the International Conference on Advances in Intelligent Systems in Bioinformatics (2013), Atlantis Press.",

year = "2014",

doi = "10.2495/Intelsys130021",

language = "English",

isbn = "978-184564869-5",

series = "WIT Transactions on Information and Communication Technologies",

publisher = "WIT Press",

pages = "9--16",

editor = "Gaol, {Ford Lumban } and Chaczko, {Zenon } and Kiyota Hashimoto and Tokoro Matsuo and Grosky, {William }",

booktitle = "Advances in Intelligent Systems",

address = "United Kingdom",

}

RIS

TY - CHAP

T1 - A wavelet-based algorithm without a priori knowledge of noise level for gross errors detection

AU - Mercorelli, Paolo

N1 - Extended paper from the International Conference on Advances in Intelligent Systems in Bioinformatics (2013), Atlantis Press.

PY - 2014

Y1 - 2014

N2 - This paper deals with Gross Error Detection using a signal-based approach and proposes an algorithm to be applied in industrial processes. The developed algorithm is used in some industrial software platforms to detect sensor outliers. A validation of this algorithm through computer simulations is shown. At the end of the paper, results using real sensor measurements from industrial processes are presented.

AB - This paper deals with Gross Error Detection using a signal-based approach and proposes an algorithm to be applied in industrial processes. The developed algorithm is used in some industrial software platforms to detect sensor outliers. A validation of this algorithm through computer simulations is shown. At the end of the paper, results using real sensor measurements from industrial processes are presented.

KW - Engineering

KW - Fault detection

KW - Industrial applications

KW - Wavelets

UR - http://www.scopus.com/inward/record.url?scp=84903448910&partnerID=8YFLogxK

U2 - 10.2495/Intelsys130021

DO - 10.2495/Intelsys130021

M3 - Contributions to collected editions/anthologies

SN - 978-184564869-5

T3 - WIT Transactions on Information and Communication Technologies

SP - 9

EP - 16

BT - Advances in Intelligent Systems

A2 - Gaol, Ford Lumban

A2 - Chaczko, Zenon

A2 - Hashimoto, Kiyota

A2 - Matsuo, Tokoro

A2 - Grosky, William

PB - WIT Press

CY - Southampton (UK)

ER -

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