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Application of unsupervised anomaly detection techniques to moisture content data from wood constructions [Elektronski vir]García-Faura, Álvaro ...Wood is considered one of the most important construction materials, as well as a natural material prone to degradation, with fungi being the main reason for wood failure in a temperate climate. ... Visual inspection of wood or other approaches for monitoring are time-consuming, and the incipient stages of decay are not always visible. Thus, visual decay detection and such manual monitoring could be replaced by automated real-time monitoring systems. The capabilities of such systems can range from simple monitoring, periodically reporting data, to the automatic detection of anomalous measurements that may happen due to various environmental or technical reasons. In this paper, we explore the application of Unsupervised Anomaly Detection (UAD) techniques to wood Moisture Content (MC) data. Specifically, data were obtained from a wood construction that was monitored for four years using sensors at different positions. Our experimental results prove the validity of these techniques to detect both artificial and real anomalies in MC signals, encouraging further research to enable their deployment in real use cases.Source: Forests [Elektronski vir]. - ISSN 1999-4907 (Vol. 12, iss. 2, 2021, 1-19 str.)Type of material - e-articlePublish date - 2021Language - englishCOBISS.SI-ID - 50590467
Author
García-Faura, Álvaro |
Štepec, Dejan |
Cankar, Matija |
Humar, Miha
Topics
vlažnost lesa |
monitoring vlažnosti lesa |
lesena okna |
lesena fasada |
enadzorovano odkrivanje nepravilnosti |
wood moisture monitoring |
Unsupervised Anomaly Detection |
moisture content data |
wooden facade |
wooden windows
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Database name | Field | Year |
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Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
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García-Faura, Álvaro | |
Štepec, Dejan | 50981 |
Cankar, Matija | 31118 |
Humar, Miha | 19106 |
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