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An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches. / Angelov, Plamen; Giglio, V; Guardiola, C et al.
In: Measurement Science and Technology, Vol. 17, No. 7, 07.2006, p. 1809-1818.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Angelov, P, Giglio, V, Guardiola, C, Lughofer, E & Lujan, JM 2006, 'An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches.', Measurement Science and Technology, vol. 17, no. 7, pp. 1809-1818. https://doi.org/10.1088/0957-0233/17/7/020

APA

Angelov, P., Giglio, V., Guardiola, C., Lughofer, E., & Lujan, J. M. (2006). An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches. Measurement Science and Technology, 17(7), 1809-1818. https://doi.org/10.1088/0957-0233/17/7/020

Vancouver

Angelov P, Giglio V, Guardiola C, Lughofer E, Lujan JM. An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches. Measurement Science and Technology. 2006 Jul;17(7):1809-1818. doi: 10.1088/0957-0233/17/7/020

Author

Angelov, Plamen ; Giglio, V ; Guardiola, C et al. / An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches. In: Measurement Science and Technology. 2006 ; Vol. 17, No. 7. pp. 1809-1818.

Bibtex

@article{92929c5ebf494014b0aa21e9371d79f1,
title = "An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches.",
abstract = "An approach to fault detection (FD) in industrial measurement systems is proposed in this paper which includes an identification strategy for early detection of the appearance of a fault. This approach is model based, i.e. nominal models are used which represent the fault-free state of the on-line measured process. This approach is also suitable for off-line FD. The framework that combines FD with isolation and correction (FDIC) is outlined in this paper. The proposed approach is characterized by automatic threshold determination, ability to analyse local properties of the models, and aggregation of different fault detection statements. The nominal models are built using data-driven and hybrid approaches, combining first principle models with on-line data-driven techniques. At the same time the models are transparent and interpretable. This novel approach is then verified on a number of real and simulated data sets of car engine test benches (both gasoline—Alfa Romeo JTS, and diesel—Caterpillar). It is demonstrated that the approach can work effectively in real industrial measurement systems with data of large dimensions in both on-line and off-line modes.",
keywords = "measurement systems, model-based failure detection, data-driven and hybrid modelling, data quality, combustion engines, engine test benches, DCS-publications-id, art-766, DCS-publications-credits, dsp-fa, DCS-publications-personnel-id, 82",
author = "Plamen Angelov and V Giglio and C Guardiola and Edwin Lughofer and Lujan, {J M}",
year = "2006",
month = jul,
doi = "10.1088/0957-0233/17/7/020",
language = "English",
volume = "17",
pages = "1809--1818",
journal = "Measurement Science and Technology",
issn = "0957-0233",
publisher = "IOP Publishing Ltd.",
number = "7",

}

RIS

TY - JOUR

T1 - An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches.

AU - Angelov, Plamen

AU - Giglio, V

AU - Guardiola, C

AU - Lughofer, Edwin

AU - Lujan, J M

PY - 2006/7

Y1 - 2006/7

N2 - An approach to fault detection (FD) in industrial measurement systems is proposed in this paper which includes an identification strategy for early detection of the appearance of a fault. This approach is model based, i.e. nominal models are used which represent the fault-free state of the on-line measured process. This approach is also suitable for off-line FD. The framework that combines FD with isolation and correction (FDIC) is outlined in this paper. The proposed approach is characterized by automatic threshold determination, ability to analyse local properties of the models, and aggregation of different fault detection statements. The nominal models are built using data-driven and hybrid approaches, combining first principle models with on-line data-driven techniques. At the same time the models are transparent and interpretable. This novel approach is then verified on a number of real and simulated data sets of car engine test benches (both gasoline—Alfa Romeo JTS, and diesel—Caterpillar). It is demonstrated that the approach can work effectively in real industrial measurement systems with data of large dimensions in both on-line and off-line modes.

AB - An approach to fault detection (FD) in industrial measurement systems is proposed in this paper which includes an identification strategy for early detection of the appearance of a fault. This approach is model based, i.e. nominal models are used which represent the fault-free state of the on-line measured process. This approach is also suitable for off-line FD. The framework that combines FD with isolation and correction (FDIC) is outlined in this paper. The proposed approach is characterized by automatic threshold determination, ability to analyse local properties of the models, and aggregation of different fault detection statements. The nominal models are built using data-driven and hybrid approaches, combining first principle models with on-line data-driven techniques. At the same time the models are transparent and interpretable. This novel approach is then verified on a number of real and simulated data sets of car engine test benches (both gasoline—Alfa Romeo JTS, and diesel—Caterpillar). It is demonstrated that the approach can work effectively in real industrial measurement systems with data of large dimensions in both on-line and off-line modes.

KW - measurement systems

KW - model-based failure detection

KW - data-driven and hybrid modelling

KW - data quality

KW - combustion engines

KW - engine test benches

KW - DCS-publications-id

KW - art-766

KW - DCS-publications-credits

KW - dsp-fa

KW - DCS-publications-personnel-id

KW - 82

U2 - 10.1088/0957-0233/17/7/020

DO - 10.1088/0957-0233/17/7/020

M3 - Journal article

VL - 17

SP - 1809

EP - 1818

JO - Measurement Science and Technology

JF - Measurement Science and Technology

SN - 0957-0233

IS - 7

ER -