Standard

Early Detection of Discrepancies in Multichannel Monitoring Systems. / Макшанов, Андрей; Мусаев, Александр Азерович; Григорьев, Дмитрий Алексеевич.

Proceedings - 2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024. Institute of Electrical and Electronics Engineers Inc., 2024. p. 506-511.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Макшанов, А, Мусаев, АА & Григорьев, ДА 2024, Early Detection of Discrepancies in Multichannel Monitoring Systems. in Proceedings - 2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024. Institute of Electrical and Electronics Engineers Inc., pp. 506-511, 2024 International Conference on Industrial Engineering, Applications and Manufacturing, Sochi, Russian Federation, 20/05/24. https://doi.org/10.1109/icieam60818.2024.10553662

APA

Макшанов, А., Мусаев, А. А., & Григорьев, Д. А. (2024). Early Detection of Discrepancies in Multichannel Monitoring Systems. In Proceedings - 2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024 (pp. 506-511). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icieam60818.2024.10553662

Vancouver

Макшанов А, Мусаев АА, Григорьев ДА. Early Detection of Discrepancies in Multichannel Monitoring Systems. In Proceedings - 2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024. Institute of Electrical and Electronics Engineers Inc. 2024. p. 506-511 https://doi.org/10.1109/icieam60818.2024.10553662

Author

Макшанов, Андрей ; Мусаев, Александр Азерович ; Григорьев, Дмитрий Алексеевич. / Early Detection of Discrepancies in Multichannel Monitoring Systems. Proceedings - 2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024. Institute of Electrical and Electronics Engineers Inc., 2024. pp. 506-511

BibTeX

@inproceedings{0a27d80b1c3540e9a04bb00692eb95c5,
title = "Early Detection of Discrepancies in Multichannel Monitoring Systems",
abstract = "This study addresses a comprehensive set of issues related to the construction and use of sequential algorithms for detecting spontaneous changes (discrepancies) in the probabilistic characteristics of multidimensional time series. The research is motivated by the challenges of mathematical support for decision-making processes based on multichannel monitoring of large systems and is dedicated to the analysis of the spatio-temporal dynamics of multidimensional time series measurements. As an alternative to traditional approaches, new technologies for anlyzing inter-channel connections are proposed. Dimensionality reduction technologies are used, based on the representation of data matrices in the first singular basis and multiple regression in the space of projections. The application of the developed approach is demonstrated in the task of analyzing the characteristics of turbulent flow based on pressure deviation measurements at various points in the volume.",
keywords = "MANOVA, dimensionality reduction, discrepancy detection, multivariate statistical analysis, singular decomposition",
author = "Андрей Макшанов and Мусаев, {Александр Азерович} and Григорьев, {Дмитрий Алексеевич}",
year = "2024",
month = may,
day = "20",
doi = "10.1109/icieam60818.2024.10553662",
language = "English",
isbn = "9798350395013",
pages = "506--511",
booktitle = "Proceedings - 2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
note = "null ; Conference date: 20-05-2024 Through 24-05-2024",
url = "https://icie-rus.org/",

}

RIS

TY - GEN

T1 - Early Detection of Discrepancies in Multichannel Monitoring Systems

AU - Макшанов, Андрей

AU - Мусаев, Александр Азерович

AU - Григорьев, Дмитрий Алексеевич

PY - 2024/5/20

Y1 - 2024/5/20

N2 - This study addresses a comprehensive set of issues related to the construction and use of sequential algorithms for detecting spontaneous changes (discrepancies) in the probabilistic characteristics of multidimensional time series. The research is motivated by the challenges of mathematical support for decision-making processes based on multichannel monitoring of large systems and is dedicated to the analysis of the spatio-temporal dynamics of multidimensional time series measurements. As an alternative to traditional approaches, new technologies for anlyzing inter-channel connections are proposed. Dimensionality reduction technologies are used, based on the representation of data matrices in the first singular basis and multiple regression in the space of projections. The application of the developed approach is demonstrated in the task of analyzing the characteristics of turbulent flow based on pressure deviation measurements at various points in the volume.

AB - This study addresses a comprehensive set of issues related to the construction and use of sequential algorithms for detecting spontaneous changes (discrepancies) in the probabilistic characteristics of multidimensional time series. The research is motivated by the challenges of mathematical support for decision-making processes based on multichannel monitoring of large systems and is dedicated to the analysis of the spatio-temporal dynamics of multidimensional time series measurements. As an alternative to traditional approaches, new technologies for anlyzing inter-channel connections are proposed. Dimensionality reduction technologies are used, based on the representation of data matrices in the first singular basis and multiple regression in the space of projections. The application of the developed approach is demonstrated in the task of analyzing the characteristics of turbulent flow based on pressure deviation measurements at various points in the volume.

KW - MANOVA

KW - dimensionality reduction

KW - discrepancy detection

KW - multivariate statistical analysis

KW - singular decomposition

UR - https://www.mendeley.com/catalogue/6d3b76fd-1c03-3dc7-9593-9c0f0e4d7e54/

U2 - 10.1109/icieam60818.2024.10553662

DO - 10.1109/icieam60818.2024.10553662

M3 - Conference contribution

SN - 9798350395013

SP - 506

EP - 511

BT - Proceedings - 2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 20 May 2024 through 24 May 2024

ER -

ID: 123947504