Forecasting Remaining Useful Life of Large Diameter Wastewater Interceptors Using Multi-Sensor Inspection and Assessment Technologies

Large-diameter wastewater interceptor sewers are probably some of the most critical assets that are owned and operated by a utility. They are also and absolutely the most difficult to inspect and maintain. And the bigger they are, the harder they are to determine their remaining useful (or service) life (RUL). However, there is good news. During the past five years, technologies related to inspection, assessment and trenchless renewal of these monster wastewater conveyance assets have grown and improved dramatically. These changes come with the equal challenges of processing enormous quantities of detailed inspection data and other information regarding the condition of each of these very imposing assets. For wastewater conveyance systems, this can include information associated with its structural, hydraulic, and maintenance-related conditions.This paper will present a summary of the technologies that are now available for such big-pipe inspection platforms and how these multi-sensor inspection (MSI) technologies can be combined to give utilities a true and reliable basis for estimating critical condition parameters such as structural integrity, hydraulic reliability, RUL, and cost-effective engineered solutions for their long-term operation. Specifically, the paper will highlight the methods that are now being used by system owners to utilize advanced MSI platforms to determine their RUL, which we believe is the “holy grail” of large-diameter wastewater interceptor management and operations. We will describe, in detail, those technologies now available on sophisticated MSI platforms which include conventional CCTV, laser scanning, sonar imaging, LiDAR, H2S monitoring, and pipe-penetrating radar (PPR). Finally, we will look at how these results from the information provided by MSI platforms for large-diameter wastewater pipelines can be directly applied to predictive models to identify relative risk as a utility asset based on likelihood of failure scoring.