Detection of water quality failure events at treatment works using a hybrid two-stage method with CUSUM and random forest algorithms

Gerald Riss,Zoran Kapelan,Michele Romano,Fayyaz Ali Memon

doi:10.2166/ws.2021.062

Gerald Riss, Zoran Kapelan + Show 2 more

Open Access

https://doi.org/10.2166/ws.2021.062

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Abstract

Abstract Near-real-time event detection is crucial for water utilities to be able to detect failure events in their water treatment works (WTW) quickly and efficiently. This paper presents a new method for an automated, near-real-time recognition of failure events at WTWs by the application of combined statistical process control and machine-learning techniques. The resulting novel hybrid CUSUM event recognition system (HC-ERS) uses two distinct detection methodologies: one for fault detection at the level of individual water quality signals and the second for the recognition of faulty processes at the WTW level. HC-ERS was tested and validated on historical failure events at a real-life UK WTW. The new methodology proved to be effective in the detection of failure events, achieving a high true-detection rate of 82% combined with a low false-alarm rate (average 0.3 false alarms per week), reaching a peak F1 score of 84% as a measure of accuracy. The new method also demonstrated higher accuracy compared with the CANARY detection methodology. When applied to real-world data, the HC-ERS method showed the capability to detect faulty processes at WTW automatically and reliably, and hence potential for practical application in the water industry.

Highlights

Water utilities around the world face considerable challenges in ensuring that their water treatment works (WTW) produce water of the required quality and quantity
We investigate the application of the novel hybrid CUSUM event recognition system (HC-event recognition systems (ERS)) for the detection of failure events at WTWs and demonstrate improvements achieved by evaluating the detection performance of the HC-ERS for real sensor data and historical events
The work presented in this paper introduces a new methodology for near-real-time detection of failure events at WTWs

Summary

INTRODUCTION

Water utilities around the world face considerable challenges in ensuring that their WTWs produce water of the required quality and quantity. In the UK, most WTWs use event recognition systems (ERS), which apply thresholds to generate alarms and detect abnormal behaviour in observed signals. More sophisticated applications for event detection at WTWs have already been developed, such as CANARY (Hart et al ) released by the United States Environmental Protection Agency (USEPA) (USEPA ) or GuardianBlue from Hach Lange (Hach Homeland Security Technologies ). This first generation of software packages still suffers from a number of shortcomings, such as insufficient real detection capability or too many false alarms (Bernard et al ). We compare HC-ERS’s performance to the performance of (i) the threshold-based WTWs event detection system currently used by one of the largest water companies in the UK and (ii) the well-known CANARY event detection algorithms

BACKGROUND

RESULTS AND DISCUSSION

CONCLUSION AND FUTURE WORK