Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy
This study proposes a probabilistic principal component analysis- (PPCA-) based method for online monitoring of water-quality contaminant events by UV-Vis (ultraviolet-visible) spectroscopy. The purpose of this method is to achieve fast and sound protection against accidental and intentional contami...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2014/150636 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850106133590573056 |
|---|---|
| author | Dibo Hou Shu Liu Jian Zhang Fang Chen Pingjie Huang Guangxin Zhang |
| author_facet | Dibo Hou Shu Liu Jian Zhang Fang Chen Pingjie Huang Guangxin Zhang |
| author_sort | Dibo Hou |
| collection | DOAJ |
| description | This study proposes a probabilistic principal component analysis- (PPCA-) based method for online monitoring of water-quality contaminant events by UV-Vis (ultraviolet-visible) spectroscopy. The purpose of this method is to achieve fast and sound protection against accidental and intentional contaminate injection into the water distribution system. The method is achieved first by properly imposing a sliding window onto simultaneously updated online monitoring data collected by the automated spectrometer. The PPCA algorithm is then executed to simplify the large amount of spectrum data while maintaining the necessary spectral information to the largest extent. Finally, a monitoring chart extensively employed in fault diagnosis field methods is used here to search for potential anomaly events and to determine whether the current water-quality is normal or abnormal. A small-scale water-pipe distribution network is tested to detect water contamination events. The tests demonstrate that the PPCA-based online monitoring model can achieve satisfactory results under the ROC curve, which denotes a low false alarm rate and high probability of detecting water contamination events. |
| format | Article |
| id | doaj-art-3133e586b19747dcb88349d2b527992e |
| institution | OA Journals |
| issn | 2314-4920 2314-4939 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Spectroscopy |
| spelling | doaj-art-3133e586b19747dcb88349d2b527992e2025-08-20T02:38:53ZengWileyJournal of Spectroscopy2314-49202314-49392014-01-01201410.1155/2014/150636150636Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption SpectroscopyDibo Hou0Shu Liu1Jian Zhang2Fang Chen3Pingjie Huang4Guangxin Zhang5Department of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, ChinaDepartment of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, ChinaDepartment of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, ChinaDepartment of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, ChinaDepartment of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, ChinaDepartment of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, ChinaThis study proposes a probabilistic principal component analysis- (PPCA-) based method for online monitoring of water-quality contaminant events by UV-Vis (ultraviolet-visible) spectroscopy. The purpose of this method is to achieve fast and sound protection against accidental and intentional contaminate injection into the water distribution system. The method is achieved first by properly imposing a sliding window onto simultaneously updated online monitoring data collected by the automated spectrometer. The PPCA algorithm is then executed to simplify the large amount of spectrum data while maintaining the necessary spectral information to the largest extent. Finally, a monitoring chart extensively employed in fault diagnosis field methods is used here to search for potential anomaly events and to determine whether the current water-quality is normal or abnormal. A small-scale water-pipe distribution network is tested to detect water contamination events. The tests demonstrate that the PPCA-based online monitoring model can achieve satisfactory results under the ROC curve, which denotes a low false alarm rate and high probability of detecting water contamination events.http://dx.doi.org/10.1155/2014/150636 |
| spellingShingle | Dibo Hou Shu Liu Jian Zhang Fang Chen Pingjie Huang Guangxin Zhang Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy Journal of Spectroscopy |
| title | Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy |
| title_full | Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy |
| title_fullStr | Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy |
| title_full_unstemmed | Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy |
| title_short | Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy |
| title_sort | online monitoring of water quality anomaly in water distribution systems based on probabilistic principal component analysis by uv vis absorption spectroscopy |
| url | http://dx.doi.org/10.1155/2014/150636 |
| work_keys_str_mv | AT dibohou onlinemonitoringofwaterqualityanomalyinwaterdistributionsystemsbasedonprobabilisticprincipalcomponentanalysisbyuvvisabsorptionspectroscopy AT shuliu onlinemonitoringofwaterqualityanomalyinwaterdistributionsystemsbasedonprobabilisticprincipalcomponentanalysisbyuvvisabsorptionspectroscopy AT jianzhang onlinemonitoringofwaterqualityanomalyinwaterdistributionsystemsbasedonprobabilisticprincipalcomponentanalysisbyuvvisabsorptionspectroscopy AT fangchen onlinemonitoringofwaterqualityanomalyinwaterdistributionsystemsbasedonprobabilisticprincipalcomponentanalysisbyuvvisabsorptionspectroscopy AT pingjiehuang onlinemonitoringofwaterqualityanomalyinwaterdistributionsystemsbasedonprobabilisticprincipalcomponentanalysisbyuvvisabsorptionspectroscopy AT guangxinzhang onlinemonitoringofwaterqualityanomalyinwaterdistributionsystemsbasedonprobabilisticprincipalcomponentanalysisbyuvvisabsorptionspectroscopy |