Assessment of the suitability of degradation models for the planning of
  CCTV inspections of sewer pipes
Fidae El Morer Stefan Wittek Andreas Rausch
The degradation of sewer pipes poses significant economical, environmental
and health concerns. The maintenance of such assets requires structured plans
to perform inspections, which are more efficient when structural and
environmental features are considered along with the results of previous
inspection reports. The development of such plans requires degradation models
that can be based on statistical and machine learning methods. This work
proposes a methodology to assess their suitability to plan inspections
considering three dimensions: accuracy metrics, ability to produce long-term
degradation curves and explainability. Results suggest that although ensemble
models yield the highest accuracy, they are unable to infer the long-term
degradation of the pipes, whereas the Logistic Regression offers a slightly
less accurate model that is able to produce consistent degradation curves with
a high explainability. A use case is presented to demonstrate this methodology
and the efficiency of model-based planning compared to the current inspection
plan.