Modelling sewer failure by evolutionary computing
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The sewer system is a service that is expected to function without interruptions. Continuous assessment, maintenance and rehabilitation are the key to maintaining a required level of service at an acceptable cost. An appropriate and cost effective prioritisation scheme for periodical surveys could be built based on failure data collected by sewerage companies over time. Such a scheme could be achieved using data-driven modelling techniques jointly with engineering knowledge of the failure mechanisms. This paper presents a descriptive analysis performed on a real database containing collapse and blockage incident records for a large sewer system in the UK. Starting from a statistical study of both failure types, the most important variables are identified and a classification scheme is suggested. Then, using a hybrid modelling technique, evolutionary polynomial regression, two different formulas for blockage events and collapse failures are obtained and their engineering interpretation is offered.
