ABSTRACT
In urban drainage systems, sensors are used for process monitoring, maintenance, planning, and control. The safety, reliability and performance of the systems are therefore largely dependent on the accuracy and reliability of the sensors. Faulty sensors may lead to poor operational performances in terms of flood and pollution control. An innovative real-time sensor fault detection approach based on the statistical properties of redundant measurements is proposed herein to improve the operation and maintenance of urban drainage systems. This approach is easy to implement, does not require estimates of the process variables and can be configured to detect a large set of anomalies, including incipient failures. The Louisville and Jefferson County Metropolitan Sewer District’s urban drainage system in Kentucky, USA, illustrates the performance of the algorithm.
Acknowledgements
The authors are particularly grateful to Mr. Wolffie Miller, Project Manager, Louisville Metropolitan Sewer District, for his support and advice during the elaboration of the case study.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Data supporting the case study is available from the Louisville Metropolitan Sewer District providing agreements for use are entered into. It is not accessible to the public or the research community directly. Access may be requested through an official data sharing agreement (https://louisvillemsd.org/contact).