A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature
In this paper, we present a method for signal change/event/anomaly detection based on a novel time-domain feature termed “conditional local peaks rate” (CLPR). First, the CLPR feature is described and further the method is introduced based on it. The CLPR calculation algorithm is implemented in the...
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Format: | Article |
Language: | English |
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Editura Universităţii din Oradea
2022-10-01
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Series: | Journal of Electrical and Electronics Engineering |
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Online Access: | http://electroinf.uoradea.ro/images/articles/CERCETARE/Reviste/JEEE/JEEE_V15_N2_OCT_2022/ZHIVOMIROV_JEEE.pdf |
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author | ZHIVOMIROV Hristo KOSTOV Nikolay |
author_facet | ZHIVOMIROV Hristo KOSTOV Nikolay |
author_sort | ZHIVOMIROV Hristo |
collection | DOAJ |
description | In this paper, we present a method for signal change/event/anomaly detection based on a novel time-domain feature termed “conditional local peaks rate” (CLPR). First, the CLPR feature is described and further the method is introduced based on it. The CLPR calculation algorithm is implemented in the Matlab® software environment as a user-defined function and several numerical experiments are conducted with real-world data for sake of verification and validation. The performance of the proposed method is compared with three other classic detection methods based on the short-time energy, short-time zero-crossing rate and short-time kurtosis and the obtained results indicate its advantages. The accessibility of the Matlab® implementation allows repeatability of the experiments and facilitates the real practical application of the method. |
first_indexed | 2024-04-09T23:36:25Z |
format | Article |
id | doaj.art-a07095f7fb9d48bba9436a6f40478f6f |
institution | Directory Open Access Journal |
issn | 1844-6035 2067-2128 |
language | English |
last_indexed | 2024-04-09T23:36:25Z |
publishDate | 2022-10-01 |
publisher | Editura Universităţii din Oradea |
record_format | Article |
series | Journal of Electrical and Electronics Engineering |
spelling | doaj.art-a07095f7fb9d48bba9436a6f40478f6f2023-03-20T11:21:16ZengEditura Universităţii din OradeaJournal of Electrical and Electronics Engineering1844-60352067-21282022-10-01152106109A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate FeatureZHIVOMIROV Hristo0KOSTOV Nikolay1Technical University of Varna, Bulgaria, Department of Theory of Electrical Engineering and Measurements, Faculty of Electrical Engineering, 1 Studentska Str., 9010 Varna, BulgariaTechnical University of Varna, Bulgaria, Department of Communication Engineering and Technologies, Faculty of Computer Sciences and Automation, 1 Studentska Str., 9010 Varna, BulgariaIn this paper, we present a method for signal change/event/anomaly detection based on a novel time-domain feature termed “conditional local peaks rate” (CLPR). First, the CLPR feature is described and further the method is introduced based on it. The CLPR calculation algorithm is implemented in the Matlab® software environment as a user-defined function and several numerical experiments are conducted with real-world data for sake of verification and validation. The performance of the proposed method is compared with three other classic detection methods based on the short-time energy, short-time zero-crossing rate and short-time kurtosis and the obtained results indicate its advantages. The accessibility of the Matlab® implementation allows repeatability of the experiments and facilitates the real practical application of the method.http://electroinf.uoradea.ro/images/articles/CERCETARE/Reviste/JEEE/JEEE_V15_N2_OCT_2022/ZHIVOMIROV_JEEE.pdftime domainsignaldatachangeeventanomalydetection |
spellingShingle | ZHIVOMIROV Hristo KOSTOV Nikolay A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature Journal of Electrical and Electronics Engineering time domain signal data change event anomaly detection |
title | A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature |
title_full | A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature |
title_fullStr | A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature |
title_full_unstemmed | A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature |
title_short | A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature |
title_sort | method for signal change detection via short time conditional local peaks rate feature |
topic | time domain signal data change event anomaly detection |
url | http://electroinf.uoradea.ro/images/articles/CERCETARE/Reviste/JEEE/JEEE_V15_N2_OCT_2022/ZHIVOMIROV_JEEE.pdf |
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