Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers
This study presents a novel approach for monitoring waste substrate digestion under high-density polyethylene (HDPE) geomembranes in sewage treatment plants. The method integrates infrared thermal imaging with a clustering algorithm to predict the distribution of various substrates beneath Tradition...
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MDPI AG
2024-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/24/8030 |
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| author | Yue Ma Benjamin Steven Vien Thomas Kuen Wing Kong Chiu |
| author_facet | Yue Ma Benjamin Steven Vien Thomas Kuen Wing Kong Chiu |
| author_sort | Yue Ma |
| collection | DOAJ |
| description | This study presents a novel approach for monitoring waste substrate digestion under high-density polyethylene (HDPE) geomembranes in sewage treatment plants. The method integrates infrared thermal imaging with a clustering algorithm to predict the distribution of various substrates beneath Traditional outdoor large-scale opaque geomembranes, using solar radiation as an excitation source. The technique leverages ambient weather conditions to assess the thermal responses of HDPE covers. Cooling constants are used to reconstruct thermal images, and clustering algorithms are explored to segment and identify different material states beneath the covers. Laboratory experiments have validated the algorithm’s effectiveness in accurately classifying varied regions by analyzing transient temperature variations caused by natural excitations. This method provides critical insights into scum characteristics and biogas collection processes, thereby enhancing decision-making in sewage treatment management. The methodology under development is anticipated to undergo rigorous evaluation across various floating covers at a large-scale sewage treatment facility in Melbourne. Subsequent to field validation, the implementation of an on-site, continuous thermography monitoring system is envisioned to be further advanced. |
| format | Article |
| id | doaj-art-a13a455ca400472287ab5f5be92dd2ff |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-a13a455ca400472287ab5f5be92dd2ff2024-12-27T14:52:46ZengMDPI AGSensors1424-82202024-12-012424803010.3390/s24248030Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating CoversYue Ma0Benjamin Steven Vien1Thomas Kuen2Wing Kong Chiu3Department of Mechanical & Aerospace Engineering, Monash University, Clayton, VIC 3800, AustraliaDepartment of Mechanical & Aerospace Engineering, Monash University, Clayton, VIC 3800, AustraliaDepartment of Integrated Planning, Melbourne Water Corporation, 990 La Trobe Street, Docklands, Melbourne, VIC 3008, AustraliaDepartment of Mechanical & Aerospace Engineering, Monash University, Clayton, VIC 3800, AustraliaThis study presents a novel approach for monitoring waste substrate digestion under high-density polyethylene (HDPE) geomembranes in sewage treatment plants. The method integrates infrared thermal imaging with a clustering algorithm to predict the distribution of various substrates beneath Traditional outdoor large-scale opaque geomembranes, using solar radiation as an excitation source. The technique leverages ambient weather conditions to assess the thermal responses of HDPE covers. Cooling constants are used to reconstruct thermal images, and clustering algorithms are explored to segment and identify different material states beneath the covers. Laboratory experiments have validated the algorithm’s effectiveness in accurately classifying varied regions by analyzing transient temperature variations caused by natural excitations. This method provides critical insights into scum characteristics and biogas collection processes, thereby enhancing decision-making in sewage treatment management. The methodology under development is anticipated to undergo rigorous evaluation across various floating covers at a large-scale sewage treatment facility in Melbourne. Subsequent to field validation, the implementation of an on-site, continuous thermography monitoring system is envisioned to be further advanced.https://www.mdpi.com/1424-8220/24/24/8030thermal imaging monitoringstructural health monitoringimage segmentationhigh-density polyethylene geomembranesfloating coverswater treatment plant |
| spellingShingle | Yue Ma Benjamin Steven Vien Thomas Kuen Wing Kong Chiu Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers Sensors thermal imaging monitoring structural health monitoring image segmentation high-density polyethylene geomembranes floating covers water treatment plant |
| title | Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers |
| title_full | Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers |
| title_fullStr | Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers |
| title_full_unstemmed | Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers |
| title_short | Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers |
| title_sort | clustering based thermography for detecting multiple substances under large scale floating covers |
| topic | thermal imaging monitoring structural health monitoring image segmentation high-density polyethylene geomembranes floating covers water treatment plant |
| url | https://www.mdpi.com/1424-8220/24/24/8030 |
| work_keys_str_mv | AT yuema clusteringbasedthermographyfordetectingmultiplesubstancesunderlargescalefloatingcovers AT benjaminstevenvien clusteringbasedthermographyfordetectingmultiplesubstancesunderlargescalefloatingcovers AT thomaskuen clusteringbasedthermographyfordetectingmultiplesubstancesunderlargescalefloatingcovers AT wingkongchiu clusteringbasedthermographyfordetectingmultiplesubstancesunderlargescalefloatingcovers |