Chapter
Nov 14, 2023

Non-Invasive 3D Imaging and Sensor Data-Based Diagnosis of Water Treatment Plant Filter Integrity

Publication: ASCE Inspire 2023

ABSTRACT

As a crucial component of water infrastructure, filtration is an imperative step in water treatment, removing particles to achieve targeted turbidity. Regular inspections of water filters are necessary to identify irregular, curved, or misaligned sections of gravel support and pipes within the filter. These geometric defects can lead to uneven water flow through the filtration layers, resulting in water quality that fails to meet established standards. Traditional filter inspection techniques involve puncturing or excavating the upper layers, can be time-consuming, and may necessitate plant shutdowns, negatively impacting operational efficiency. Aiming at addressing this issue, the authors used 3D laser scanning and time-series sensor data analysis for non-contact inspections, reducing time, costs, and errors associated with conventional field punctures of filtration media. The point clouds and time-series sensor data from six water filters before and after backwash were collected. The authors identified correlations between anomalous geometric change patterns on the surface and hidden geometric defects. Additionally, geometric information from point clouds and sensor data could be mutually interpreted, and uneven backwash processes and water flows caused by subsurface defects can produce irregular 3D geometric changes on the top surface and abnormal sensor data. Filter 2 exhibits higher surface elevations (a bump on one side of the filter surface) than the other five filters. According to the sensory time series analysis, the average production between each backwash of filter 2 is lower than that of the other five filters, Consequently, filter 2 is diagnosed as the outlier among the six filters.

Get full access to this article

View all available purchase options and get full access to this chapter.

REFERENCES

Chen, G., Liu, M., and Chen, J. (2020). “Frequency-temporal-logic-based bearing fault diagnosis and fault interpretation using Bayesian optimization with Bayesian neural networks.” Mechanical Systems and Signal Processing, 145, 106951.
Chethana, B., Patil, A. K., and Chai, Y. H. “Development of an Efficient Pipeline Retrofitting Application for a Water Treatment Facility.” Proc., 2018 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia), IEEE, 206–212.
Faruk, D. Ö. (2010). “A hybrid neural network and ARIMA model for water quality time series prediction.” Engineering applications of artificial intelligence, 23(4), 586–594.
Ghoneim, S. S., and Taha, I. B. (2016). “A new approach of DGA interpretation technique for transformer fault diagnosis.” International Journal of Electrical Power & Energy Systems, 81, 265–274.
Liu, J., Li, G., Liu, B., Li, K., and Chen, H. (2019). “Knowledge discovery of data-driven-based fault diagnostics for building energy systems: a case study of the building variable refrigerant flow system.” Energy, 174, 873–885.
Lloyd, D. S. (1987). “Turbidity as a water quality standard for salmonid habitats in Alaska.” North American journal of fisheries management, 7(1), 34–45.
Longo, S., d’Antoni, B. M., Bongards, M., Chaparro, A., Cronrath, A., Fatone, F., Lema, J. M., Mauricio-Iglesias, M., Soares, A., and Hospido, A. (2016). “Monitoring and diagnosis of energy consumption in wastewater treatment plants. A state of the art and proposals for improvement.” Applied energy, 179, 1251–1268.
Marzouk, M., and Ahmed, R. (2019). “BIM-Based Facility management for water treatment plants using laser scanning.” Water Practice and Technology, 14(2), 325–330.
McGlohorn, G., By, E., Trofatter, G., Kinard, D., Randolph, P. B., and Welch, R. (2003). “Filter assessment manual.” <https://scdhec.gov/sites/default/files/docs/Environment/docs/filter%20manual.pdf>.
Moritani, R., Kanai, S., Date, H., Watanabe, M., Nakano, T., and Yamauchi, Y. (2019). “Cylinder-based efficient and robust registration and model fitting of laser-scanned point clouds for as-built modeling of piping systems.” Comput. Aided Des. Appl, 16, 396–412.
Nix, D. K., and Taylor, J. S. (2003). Filter evaluation procedures for granular media, American Water Works Association.
Piri, I., Homayoonnezhad, I., and Amirian, P. “Investigation on optimization of conventional drinking water treatment plant.” Proc., 2010 2nd International Conference on Chemical, Biological and Environmental Engineering, IEEE, 304–310.
Wang, Q., and Kim, M.-K. (2019). “Applications of 3D point cloud data in the construction industry: A fifteen-year review from 2004 to 2018.” Advanced Engineering Informatics, 39, 306–319.
Yu, P., Cao, J., Jegatheesan, V., and Shu, L. (2019). “Activated sludge process faults diagnosis based on an improved particle filter algorithm.” Process Safety and Environmental Protection, 127, 66–72.
Yu, P., Wu, H., Liu, C., and Xu, Z. (2018). “Water leakage diagnosis in metro tunnels by intergration of laser point cloud and infrared thermal imaging.” ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 2167–2171.

Information & Authors

Information

Published In

Go to ASCE Inspire 2023
ASCE Inspire 2023
Pages: 932 - 940

History

Published online: Nov 14, 2023

Permissions

Request permissions for this article.

ASCE Technical Topics:

Authors

Affiliations

Pengkun Liu [email protected]
1Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA. Email: [email protected]
Jinding Xing [email protected]
2Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA. Email: [email protected]
Jinghua Xiao [email protected]
3Water Quality Engineering Manager, Aqua America, Bryn Mawr, PA. Email: [email protected]
Christopher Miller [email protected]
4Associate Professor, Dept. of Civil Engineering, Univ. of Akron. Email: [email protected]
Pingbo Tang [email protected]
5Associate Professor, Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$230.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$230.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share