E2.09 Newhart 2019 ReNUWIt Annual Meeting Poster

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Abstract/Contents

Abstract: Water and wastewater treatment are complex and dynamic processes, with performance tightly linked to influent quality, sensor accuracy, and system resiliency. Large facilities can buffer against influent changes or mechanical faults, but small, decentralized treatment plants are vulnerable to even minor or short- lived perturbations. Early fault detection is crucial for decentralized systems: preventing downtime, avoiding effluent limit exceedances, and reducing the cost of operation. If statistical process control was implemented, wastewater treatment plants (WWTP) could detect changes in the relationships between multiple variables, detecting the fault before a serious failure occurs. In this work, a modified principal component analysis (PCA) program is developed to detect faults for decentralized wastewater treatment systems. Mechanical, biological, and sensor faults from a 7,000 GPD demonstration-scale WWTP are analyzed using the PCA program in real-time. Future work on the program includes fault diagnosis and automated corrective control for real-time WWTP optimization.

Type of resource	other
Date created	May 2019

Subject	Re-inventing the Nation’s Urban Water Infrastructure
Subject	ReNUWIt
Subject	E2.09
Subject	Efficient Engineered Systems
Subject	Energy and resource recovery
Subject	Mines Park
Subject	Golden
Subject	Colorado
Subject	fault detection
Subject	management
Subject	optimization
Subject	sensors
Subject	statistical process control
Subject	wastewater treatment

Related Publication	Newhart, K. B., Holloway, R. W., Hering, A. S., & Cath, T. Y. (2019). Data-driven performance analyses of wastewater treatment plants: A review. Water Research, 157, 498-513. http://doi.org/10.1016/j.watres.2019.03.030 Y9
Related Publication	Newhart, K. B., Marks, C. A., Rauch-Williams, T., Cath, T. Y., & Hering, A. S. (2020). Hybrid statistical-machine learning ammonia forecasting in continuous activated sludge treatment for improved process control. Journal of Water Process Engineering, 37, 101389. https://doi.org/10.1016/j.jwpe.2020.101389
Location	https://purl.stanford.edu/rs532jd8752

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Preferred Citation: Newhart, K. B., Hering, A. S., & Cath, T. Y. (2019). E2.09 Newhart 2019 ReNUWIt Annual Meeting Poster. Stanford Digital Repository. Available at: https://purl.stanford.edu/rs532jd8752

Re-inventing the Nation's Urban Water Infrastructure (ReNUWIt)

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